Co-reporter:Lanlan Li, Yongchang Zhu, Shuangyan Zhou, Xiaoli An, Yan Zhang, Qifeng Bai, Yong-Xing He, Huanxiang Liu, and Xiaojun Yao
ACS Chemical Neuroscience December 20, 2017 Volume 8(Issue 12) pp:2698-2698
Publication Date(Web):August 17, 2017
DOI:10.1021/acschemneuro.7b00240
Resveratrol and its derivatives have been shown to display beneficial effects to neurodegenerative diseases. However, the molecular mechanism of resveratrol and its derivatives on prion conformational conversion is poorly understood. In this work, the interaction mechanism between prion and resveratrol as well as its derivatives was investigated using steady-state fluorescence quenching, Thioflavin T binding assay, Western blotting, and molecular dynamics simulation. Protein fluorescence quenching method and Thioflavin T assay revealed that resveratrol and its derivatives could interact with prion and interrupt prion fibril formation. Molecular dynamics simulation results indicated that resveratrol can stabilize the PrP127–147 peptide mainly through π–π stacking interactions between resveratrol and Tyr128. The hydrogen bonds interactions between resveratrol and the PrP127–147 peptide could further reduce the flexibility and the propensity to aggregate. The results of this study not only can provide useful information about the interaction mechanism between resveratrol and prion, but also can provide useful clues for further design of new inhibitors inhibiting prion aggregation.Keywords: aggregation; molecular dynamics simulations; Prion; resveratrol; ThT;
Co-reporter:Xing Yang, Fan Yang, Rui-Zhi Wu, Chao-Xian Yan, Da-Gang Zhou, Pan-Pan Zhou, Xiaojun Yao
Journal of Molecular Graphics and Modelling 2017 Volume 76(Volume 76) pp:
Publication Date(Web):1 September 2017
DOI:10.1016/j.jmgm.2017.07.026
•Linear X(Y)⋯CO⋯X(Y) complexes form between CO and two dihalogen molecules XY (X, Y = Cl, Br).•The positive MEP regions of two XY (X, Y = Cl, Br) molecules interact with negative MEP regions of CO.•The electrostatic interaction is the dominant net driving force in the formation of each trimer.Carbon monoxide can interact with two dihalogen molecules XY (X, Y = Cl, Br) in the form of X(Y)⋯COX(Y)⋯CO⋯X(Y)X(Y) trimeric complex, and their nature and characteristics were investigated at MP2/aug-cc-pVDZ level without and with counterpoise method, together with single point calculations at CCSD(T)/aug-cc-pVDZ level. The optimized geometries, stretching modes and interaction energies of a series of X(Y)⋯COX(Y)⋯CO⋯X(Y)X(Y) trimeric complexes were obtained and discussed. The cooperativity in these complexes was evaluated. EDA analyses reveal that the electrostatic interaction is the dominant net driving force in each trimer, but the contributions of other interactions like exchange, dispersion and polarization interactions are also important. QTAIM and NCI analyses confirm the existence of attractive halogen-bonding interactions. Additionally, EDDMF analysis was employed for the component dimers of these trimers, which indicates that the formation of halogen-bonding interactions is closely related to the charge shift and the rearrangement of electronic density in the formation of these complexes. The results would provide valuable insight into for these linear halogen bonds.CO can interact with two dihalogen molecules XY (X, Y = Cl, Br) in the form of linearly X(Y)⋯CO⋯X(Y) trimeric complex due to the electron-donating ability of both C and O and the electron-accepting ability of the σ-hole of X or Y halogen atom.Download high-res image (106KB)Download full-size image
Co-reporter:Wenyan Zan, Wei Geng, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2016 vol. 18(Issue 4) pp:3159-3164
Publication Date(Web):17 Dec 2015
DOI:10.1039/C5CP06029J
Vertical heterostructures of MoS2/h-BN/graphene have been successfully fabricated in recent experiments. Using first-principles analysis, we show that the structural and electronic properties of such vertical heterostructures are sensitive to applied vertical electric fields and strain. The applied electric field not only enhances the interlayer coupling but also linearly controls the charge transfer between graphene and MoS2 layers, leading to a tunable doping in graphene and controllable Schottky barrier height. Applied biaxial strain could weaken the interlayer coupling and results in a slight shift of graphene's Dirac point with respect to the Fermi level. It is of practical importance that the tunable electronic properties by strain and electric fields are immune to the presence of sulfur vacancies, the most common defect in MoS2.
Co-reporter:Yuzhen Niu, Shuyan Li, Dabo Pan, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2016 vol. 18(Issue 7) pp:5622-5629
Publication Date(Web):21 Jan 2016
DOI:10.1039/C5CP06257H
B-RAF kinase is a clinically validated target implicated in melanoma and advanced renal cell carcinoma (RCC). PLX4720 and TAK-632 are promising inhibitors against B-RAF with different dissociation rate constants (koff), but the specific mechanism that determines the difference of their dissociation rates remains unclear. In order to understand the kinetically different behaviors of these two inhibitors, their unbinding pathways were explored by random acceleration and steered molecular dynamics simulations. The random acceleration molecular dynamics (RAMD) simulations show that PLX4720 dissociates along the ATP-channel, while TAK-632 dissociates along either the ATP-channel or the allosteric-channel. The steered molecular dynamics (SMD) simulations reveal that TAK-632 is more favorable to escape from the binding pocket through the ATP-channel rather than the allosteric-channel. The PMF calculations suggest that TAK-632 presents longer residence time, which is in qualitative agreement with the experimental koff(koff = 3.3 × 10−2 s−1 and ΔGoff = −82.17 ± 0.29 kcal mol−1 for PLX4720; koff = 1.9 × 10−5 s−1 and ΔGoff = −39.73 ± 0.79 kcal mol−1 for PLX4720). Furthermore, the binding free decomposition by MM/GBSA illustrates that the residues K36, E54, V57, L58, L120, I125, H127, G146 and D147 located around the allosteric binding pocket play important roles in determining the longer residence time of TAK-632 by forming stronger hydrogen bond and hydrophobic interactions. Our simulations provide valuable information to design selective B-RAF inhibitors with long residence time in the future.
Co-reporter:Wenyan Zan, Wei Geng, Huanxiang Liu, Xiaojun Yao
Journal of Alloys and Compounds 2016 Volume 658() pp:152-156
Publication Date(Web):15 February 2016
DOI:10.1016/j.jallcom.2015.10.145
•The mechanism of field emission properties of two-dimensional VS2–ZnO composites was revealed at atomic scales.•VS2 and ZnO (ZnO cluster and S-doped ZnO cluster) systems were studied.•Zn4O3S/VS2 composites may produce better performance with stronger external electric field than Zn4O4/VS2.The electronic structures and field emission properties of VS2–ZnO composites were studied using density functional theory calculations. The possible effect of the external electric field on the important electronic parameters including binding energies, charge transfer, distributions of near-gap electronic states, work functions and ionization potentials of VS2–ZnO composites were also investigated. The calculation results prove that binding energies gradually increase with the increasing of the electric field and the composites have field-enhanced stability. The charge accumulation of S atoms from VS2 contributes directly to the field emission properties of the two dimensional VS2 materials. Moreover, the electric field can induce the decrease of work function and ionization potential for VS2–ZnO composites. These results prove that VS2–ZnO composites could be used as a promising candidate for applications in field emission devices.
Co-reporter:Wenyan Zan, Wei Geng, Huanxiang Liu, Xiaojun Yao
Journal of Alloys and Compounds 2016 Volume 666() pp:204-208
Publication Date(Web):5 May 2016
DOI:10.1016/j.jallcom.2016.01.108
•The structure and electronic properties of MoS2/SiC composites were investigated.•The electronic property of MoS2 can be modulated by SiC with different thickness.•The MoS2/Si-terminated SiC has higher stability than MoS2/C-terminated SiC.The structure and electronic properties of MoS2 and SiC (single-layer SiC, double layer SiC, C-terminated SiC and Si-terminated SiC) composites were investigated by using density functional theory calculations. The calculation results show that the electronic properties of MoS2 are modified at different levels by combining with different thickness of SiC. The heterostructures (MoS2/C-terminated SiC and MoS2/Si-terminated SiC) possess larger binding energies than MoS2/single-layer SiC and MoS2/bilayer SiC, suggesting the higher stability for MoS2/C-terminated SiC and MoS2/Si-terminated SiC composites. It is found that charge transfer is from SiC to MoS2 in these heterostructures. MoS2/single-layer SiC, MoS2/double-layer SiC and MoS2/C-terminated SiC are semiconductors, whereas MoS2/Si-terminated SiC has no gap.
Co-reporter:Dabo Pan, Yuzhen Niu, Weiwei Xue, Qifeng Bai, Huanxiang Liu, Xiaojun Yao
Chemometrics and Intelligent Laboratory Systems 2016 Volume 154() pp:185-193
Publication Date(Web):15 May 2016
DOI:10.1016/j.chemolab.2016.03.015
•We successfully predicted the rank of drug resistance by MM/GBSA and ABF.•The hydrophobic interaction plays a primary role in BMS-791325 binding to NS5B.•P495L mutation makes more flexibility of NS5B binding pocket.•A421V and L392I mutations disrupt hydrophilic interactions.Hepatitis C Virus (HCV) NS5B RNA-dependent RNA polymerase is an attractive target for anti-HCV development. Several mutations such as A421V, L392I and P495L in thumb I pocket of HCV NS5B polymerase have been proved to be resistant to BMS-791325 (Phase III clinical trial). A deep understanding of the resistance mechanism conferred by these mutations is important to the design and discovery of more new effective drugs against resistant HCV strains. We performed molecular dynamics (MD) simulations, free energy calculation and adaptive biasing force (ABF) simulation to study the possible resistance mechanism conferred by the above mutants. MD simulation results show the hydrophobic interaction is the driving force for BMS-791325 binding. ABF simulation proves that attenuation of the hydrophilic interaction between R503 and BMS-791325 is the first step for drug to escape from the binding site. Loss of the hydrophilic interaction makes drug easily to move out of the hydrophobic pocket. The simulation results further reveal that A421V, L392I and P495L mutants reduce drug binding affinity. P495L mutant makes the binding pocket more flexible and cannot anchor BMS-791325. The altered hydrophilic interactions of mutant residues are the essential reasons leading to drug resistance in A421V and L392I mutants. Our results will provide useful information to develop effective HCV NS5B inhibitors against resistance.
Co-reporter:Yuzhen Niu, Dabo Pan, Yongjiu Yang, Huanxiang Liu, Xiaojun Yao
Chemometrics and Intelligent Laboratory Systems 2016 Volume 158() pp:91-101
Publication Date(Web):15 November 2016
DOI:10.1016/j.chemolab.2016.08.002
•MM/GBSA calculations were used to identify the key residues for binding.•Enhanced sampling simulations are employed to calculate free energy barriers.•The unbinding mechanism of SCH772984 to ERK22 is found.•The molecular mechanism behind the difference in the residence time is revealed.SCH772984, VTX-11e, FR180204 and 5-iTU are four promising inhibitors targeting ERK2 kinase with high bioactivity. These four inhibitors also have different residence times and binding modes with the ERK2 kinase. Revealing the molecular mechanism of different residence times of ERK2 inhibitors is helpful for designing more efficient inhibitors. The molecular mechanics/generalized Born surface area (MM/GBSA) method was used to calculate the binding free energy and identify the key residues for the ERK2 protein binding to the four inhibitors. Steered molecular dynamics (SMD) and adaptive biasing force (ABF) simulations were employed to investigate the molecular mechanism behind this difference in residence time and binding mode. The binding free energy decomposition by the MM/GBSA method reveals the residues Y27, K45, I47, P49, Y55, R58, T59, Q96 and G160 located around the allosteric binding pocket play an important role in determining the longer residence time of SCH772984. The results from the SMD and the ABF simulations show SCH772984 has different unbinding mechanism compared with the other three inhibitors. SCH772984 needs to overcome two energy barriers: one is the π-π stacking interaction formed by the piperazine-phenyl-pyrimidine of SCH772984 and the residue Y55 of the ERK2 kinase; the other is the hydrophobic interaction at the ATP active site. VTX-11e, FR180204 and 5-iTU just need to overcome the hydrophobic interaction at the ATP active site. Our simulation results are useful to understand the interaction mechanism between four inhibitors and ERK2 kinase and are helpful for designing more potent ERK2 inhibitors.
Co-reporter:Dabo Pan, Yuzhen Niu, Lulu Ning, Yang Zhang, Huanxiang Liu, Xiaojun Yao
Chemometrics and Intelligent Laboratory Systems 2016 Volume 156() pp:72-80
Publication Date(Web):15 August 2016
DOI:10.1016/j.chemolab.2016.05.015
•The competitive mechanism between GS-461203 and UTP to NS5B was studied.•The resistance mechanism to GS-461203 conferred by S282T mutant was explored.•The unbinding pathway of GS-461203 to NS5B was studied using random acceleration molecular dynamics simulation•The potential of mean force profile of GS-461203 to NS5B was calculated based on steered molecular dynamics simulation.The active metabolite GS-461203 of hepatitis C virus (HCV) non-structural protein 5B (NS5B) inhibitor sofosbuvir can stall RNA synthesis or replication by competitively inhibiting the natural substrate nucleoside triphosphate like UTP. Unfortunately, S282T mutant can lead to the resistance to sofosbuvir. Here, the detailed binding mechanism and unbinding process of GS-461203 and UTP to HCV NS5B were unraveled by using conventional molecular dynamics (MD) simulation and steered molecular dynamics (SMD) simulation. Our simulation results demonstrate that both polar and nonpolar interactions are favorable for GS-461203 and UTP binding. Meanwhile, we also identified the key residues responsible for GS-461203 and UTP binding in NS5B-RNA together with the three unbinding process steps including translation, reversal of base and ribose and complete divorce. The 2′-fluoro-2′-C-methyl ribose of GS-461203 can form stronger polar and nonpolar interactions with residues S282 and I160 than UTP. The results can also explain the reason why GS-461203 can effectively be incorporated into RNA synthesis or replication. In the S282T mutant system, the binding affinity attenuation of UTP relative to wild type HCV NS5B is less than that of GS-461203. The obtained binding and unbinding mechanism of HCV NS5B with the inhibitor GS-461203 and substrate in our work will provide useful guidance for the development of new and effective HCV NS5B inhibitors with low resistance.
Co-reporter:Lulu Ning, Qianqian Wang, Yang Zheng, Huanxiang Liu and Xiaojun Yao
Molecular BioSystems 2015 vol. 11(Issue 2) pp:647-655
Publication Date(Web):01 Dec 2014
DOI:10.1039/C4MB00546E
The palindromic region AGAAAAGA (PrP113–120) in prion is highly amyloidogenic and very critical in the structural conversion of cellular prion protein to its pathogenetic form. In this region, there is an important point mutation A117V, which is closely related to the occurrence of Gerstmann–Straussler–Scheinker Syndrome. However, the detailed knowledge about the effects of the A117V mutation on the folding and aggregation of the palindromic sequences is still lacking. To investigate the impacts of A117V mutation on the earliest steps along the PrP113–120 aggregation pathway, replica exchange molecular dynamics simulations of the monomer, 2- and 4-peptide systems of PrP113–120 and its A117V mutant were carried out. The simulations of monomers indicate that both WT and the A117V mutated PrP113–120 are mostly random coils with helical structures transiently populated. Differently, the A117V mutation enhances the intrinsic disorder of PrP113–120. The simulations of 2- and 4-peptide systems of the two species show that the A117V mutation increases the sheet contents and the populations of oligomers, which may be attributed to the enhancement of inter-peptide backbone hydrogen bonding interactions and side chain hydrophobic interactions. Overall, the study provides structural insights into the impacts of the A117V mutation on the folding and assembly of the palindromic sequences, which might be helpful to elucidate the mechanism underlying prion disease and the origin of the Gerstmann–Straussler–Scheinker Syndrome.
Co-reporter:Xiaojie Jin, Qifeng Bai, Weiwei Xue, Huanxiang Liu, Xiaojun Yao
Chemometrics and Intelligent Laboratory Systems 2015 Volume 149(Part B) pp:81-88
Publication Date(Web):15 December 2015
DOI:10.1016/j.chemolab.2015.10.013
•MD, cross-correlation, PMF, dynamical community analysis and ABF were used in this study.•In the apo system, PfMATE adopts a more out-open conformation and TM1 tends to bend.•In the Mad5-bound state, PfMATE experiences smaller conformational change.•MaD5 blocks some allosteric pathways between TMs of PfMATE.Multidrug and toxic compound extrusion (MATE) family transporters confer multiple-drug resistance (MDR) to bacterial pathogens and cancer cells. Therefore, the development of molecules capable of antagonizing the functions of MATE transporters is urgent because of their clinical importance. Recently, macrocyclic peptide inhibitors of Pyrococcus furiosus multidrug and toxic compound extrusion (PfMATE) transporter have been reported. However, the detailed interaction and inhibition mechanism remains elusive. In this work, molecular dynamics (MD) simulations, cross-correlation analysis, potential of mean force (PMF) calculation, dynamical community analysis and free energy calculation were performed to investigate the allosteric inhibition mechanism of a macrocyclic peptide MaD5 on PfMATE. Our simulation results demonstrate that TM1 of PfMATE tends to bend in the apo system during the simulation. In the inhibitor-bound system, PfMATE experiences a small conformational change in the inhibition process induced by MaD5. Dynamical community analysis shows that there are allosteric regulation pathways between different TMs, such as TM1 and TM8, TM8 and TM6, TM4 and TM8. These allosteric pathways may play an important role for substrate transporting of PfMATE. In contrast, the inhibitor MaD5 blocks the allosteric pathways between TMs including TM1 and TM8, TM8 and TM6 in the inhibitor-bound system. The free energy calculations indicate that interactions between the minicycle head of MaD5 and the binding pocket in the N-lope of PfMATE are mainly responsible for binding of MaD5. Our simulation results can provide an important insight for the design of more potent macrocyclic peptide inhibitors.
Co-reporter:Hai-E. Ding, Zhong-Duo Yang, Li Sheng, Shuang-Yan Zhou, Shuo Li, Xiao-Jun Yao, Kang-Kang Zhi, Yong-Gang Wang, Fei Zhang
Tetrahedron Letters 2015 Volume 56(Issue 48) pp:6754-6757
Publication Date(Web):2 December 2015
DOI:10.1016/j.tetlet.2015.10.063
Secovironolide (1) was purified from the culture broth of Talaromyces wortmanni and is the first example of a furanosteroid scaffold bearing a five-membered B ring. The structure of 1 was elucidated by comprehensive NMR spectroscopy and single-crystal X-ray crystallography. Additional known viridian derivatives (2–5, 7) were isolated, including the new epoxide containing compound, epoxyvirone (6). Isolates were tested for monoamine oxidase (MAO) inhibitory activity and showed only weak activity.
Co-reporter:Qifeng Bai, Yang Zhang, Xiaomeng Li, Wenbo Chen, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2014 vol. 16(Issue 44) pp:24332-24338
Publication Date(Web):29 Sep 2014
DOI:10.1039/C4CP03331K
C–C chemokine receptor type 5 (CCR5) is the co-receptor of human immunodeficiency virus type 1 (HIV-1) and plays an important role in HIV-1 virus infection. Maraviroc has been proved to be effective for anti-HIV-1 by targeting CCR5. Understanding the detailed interaction mechanism between CCR5 and Maraviroc will be of great help to the rational design of a more potential inverse agonist to block HIV-1 infection. Here, we performed molecular dynamics (MD) simulation and accelerated MD simulation (aMD) to study the interaction mechanism between CCR5 and Maraviroc based on a recently reported crystal structure. The results of MD simulation demonstrate that Maraviroc can form stable hydrogen bonds with residues Tyr371.39, Tyr2516.51 and Glu2837.39. The results of aMD simulation indicate that the carboxamide moiety is more flexible than the tropane group of Maraviroc in the pocket of CCR5. The electrostatic potential analysis proves that Maraviroc can escape from the pocket of CCR5 along the negative electrostatic potential pathway during the dissociation process. The free energy calculation illustrates that there exist three binding pockets during the dissociation process of Maraviroc. Our results will be useful for understanding the interaction mechanism between CCR5 and Maraviroc as well as for the rational design of a more potent inverse agonist.
Co-reporter:Qifeng Bai, Horacio Pérez-Sánchez, Yang Zhang, Yonghua Shao, Danfeng Shi, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2014 vol. 16(Issue 30) pp:15874-15885
Publication Date(Web):12 May 2014
DOI:10.1039/C4CP01185F
The reported crystal structures of β2 adrenergic receptor (β2AR) reveal that the open and closed states of the water channel are correlated with the inactive and active conformations of β2AR. However, more details about the process by which the water channel states are affected by the active to inactive conformational change of β2AR remain illusive. In this work, molecular dynamics simulations are performed to study the dynamical inactive and active conformational change of β2AR induced by inverse agonist ICI 118,551. Markov state model analysis and free energy calculation are employed to explore the open and close states of the water channel. The simulation results show that inverse agonist ICI 118,551 can induce water channel opening during the conformational transition of β2AR. Markov state model (MSM) analysis proves that the energy contour can be divided into seven states. States S1, S2 and S5, which represent the active conformation of β2AR, show that the water channel is in the closed state, while states S4 and S6, which correspond to the intermediate state conformation of β2AR, indicate the water channel opens gradually. State S7, which represents the inactive structure of β2AR, corresponds to the full open state of the water channel. The opening mechanism of the water channel is involved in the ligand-induced conformational change of β2AR. These results can provide useful information for understanding the opening mechanism of the water channel and will be useful for the rational design of potent inverse agonists of β2AR.
Co-reporter:Weiwei Xue, Yihe Ban, Huanxiang Liu, and Xiaojun Yao
Journal of Chemical Information and Modeling 2014 Volume 54(Issue 2) pp:621-633
Publication Date(Web):June 9, 2013
DOI:10.1021/ci400060j
Hepatitis C virus (HCV) NS3/4A protease is an important and attractive target for anti-HCV drug development and discovery. Vaniprevir (phase III clinical trials) and MK-5172 (phase II clinical trials) are two potent antiviral compounds that target NS3/4A protease. However, the emergence of resistance to these two inhibitors reduced the effectiveness of vaniprevir and MK-5172 against viral replication. Among the drug resistance mutations, three single-site mutations at residues Arg155, Ala156, and Asp168 in NS3/4A protease are especially important due to their resistance to nearly all inhibitors in clinical development. A detailed understanding of drug resistance mechanism to vaniprevir and MK-5172 is therefore very crucial for the design of novel potent agents targeting viral variants. In this work, molecular dynamics (MD) simulation, binding free energy calculation, free energy decomposition, residue interaction network (RIN), and substrate envelope analysis were used to study the detailed drug resistance mechanism of the three mutants R155K, A156T, and D168A to vaniprevir and MK-5172. MD simulation was used to investigate the binding mode for these two inhibitors to wild-type and resistant mutants of HCV NS3/4A protease. Binding free energy calculation and free energy decomposition analysis reveal that drug resistance mutations reduced the interactions between the active site residues and substituent in the P2 to P4 linker of vaniprevir and MK-5172. Furthermore, RIN and substrate envelope analysis indicate that the studied mutations of the residues are located outside the substrate (4B5A) binding site and selectively decrease the affinity of inhibitors but not the activity of the enzyme and consequently help NS3/4A protease escape from the effect of the inhibitors without influencing the affinity of substrate binding. These findings can provide useful information for understanding the drug resistance mechanism against vaniprevir and MK-5172. The results can also provide some potential clues for further design of novel inhibitors that are less susceptible to drug resistance.
Co-reporter:Wei Geng, Xuefei Zhao, Wenyan Zan, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2014 vol. 16(Issue 8) pp:3542-3548
Publication Date(Web):11 Nov 2013
DOI:10.1039/C3CP52841C
In this work, the effects of the electric field on the properties of ZnO–graphene composites were theoretically studied using density functional theory calculations. Three types of ZnO–graphene composites including composites of pristine graphene, graphene with defects as well as graphene oxide and a ZnO bilayer were studied. We calculated and analyzed the binding energies, charge transfer, band structures and work functions of the above composites under the external electric fields. The DFT calculation results demonstrate that the binding energies are sensitive to the electric field, and increasing the external electric field gives rise to stronger binding energies. The extent of charge transfer is correlated with the magnitude of the external electric field, but the band gaps are hardly affected by the external electric field. The work functions vary depending on the different structures of the composites and surface sides, and they are also tunable by the external electric field.
Co-reporter:Qifeng Bai, Danfeng Shi, Yang Zhang, Huanxiang Liu and Xiaojun Yao
Molecular BioSystems 2014 vol. 10(Issue 7) pp:1958-1967
Publication Date(Web):28 Mar 2014
DOI:10.1039/C4MB00037D
Corticotropin-releasing factor receptor 1 (CRF1R), a member of class B G-protein-coupled receptors (GPCRs), plays an important role in the treatment of osteoporosis, diabetes, depression, migraine and anxiety. To explore the escape pathway of the antagonist CP-376395 in the binding pocket of CRF1R, molecular dynamics (MD) simulations, dynamical network analysis, random acceleration molecular dynamics (RAMD) simulations and adaptive biasing force (ABF) calculations were performed on the crystal structure of CRF1R in complex with CP-376395. The results of dynamical network analysis show that TM7 of CRF1R has the strongest edges during MD simulation. The bent part of TM7 forms a V-shape pocket with Gly3567.50. Asn2835.50 has high hydrogen bond occupancy during 100 ns MD simulations and is the key interaction residue with the antagonist in the binding pocket of CRF1R. RAMD simulation has identified three possible pathways (PW1, PW2 and PW3) for CP-376395 to escape from the binding pocket of CRF1R. The PW3 pathway was proved to be the most likely escape pathway for CP-376395. The free energy along the PW3 pathway was calculated by using ABF simulations. Two energy barriers were found along the reaction coordinates. Residues Leu3236.49, Asn2835.50 and Met2063.47 contribute to the steric hindrance for the first energy barrier. Residues His1993.40 and Gln3557.49 contribute to the second energy barrier through the hydrogen bonding interaction between CP-376395 and CRF1R. The results of our study can not only provide useful information to understand the interaction mechanism between CP-376395 and CRF1R, but also provide the details about the possible escape pathway and the free energy profile of CP-376395 in the pocket of CRF1R.
Co-reporter:Weiwei Xue, Xiaojie Jin, Lulu Ning, Meixia Wang, Huanxiang Liu, and Xiaojun Yao
Journal of Chemical Information and Modeling 2013 Volume 53(Issue 1) pp:210-222
Publication Date(Web):December 11, 2012
DOI:10.1021/ci300541c
The rapid emergence of cross-resistance to the integrase strand transfer inhibitors (INSTIs) has become a serious problem in the therapy of human immunodeficiency virus type 1 (HIV-1) infection. Understanding the detailed molecular mechanism of INSTIs cross-resistance is therefore critical for the development of new effective therapy against cross-resistance. On the basis of the homology modeling constructed structure of tetrameric HIV-1 intasome, the detailed molecular mechanism of the cross-resistance mutation E138K/Q148K to three important INSTIs (Raltegravir (RAL, FDA approved in 2007), Elvitegravir (EVG, FDA approved in 2012), and Dolutegravir (DTG, phase III clinical trials)) was investigated by using molecular dynamics (MD) simulation and residue interaction network (RIN) analysis. The results from conformation analysis and binding free energy calculation can provide some useful information about the detailed binding mode and cross-resistance mechanism for the three INSTIs to HIV-1 intasome. Binding free energy decomposition analysis revealed that Pro145 residue in the 140s 1oop (Gly140 to Gly149) of the HIV-1 intasome had strong hydrophobic interactions with INSTIs and played an important role in the binding of INSTIs to HIV-1 intasome active site. A systematic comparison and analysis of the RIN proves that the communications between the residues in the resistance mutant is increased when compared with that of the wild-type HIV-1 intasome. Further analysis indicates that residue Pro145 may play an important role and is relevant to the structure rearrangement in HIV-1 intasome active site. In addition, the chelating ability of the oxygen atoms in INSTIs (e.g., RAL and EVG) to Mg2+ in the active site of the mutated intasome was reduced due to this conformational change and is also responsible for the cross-resistance mechanism. Notably, the cross-resistance mechanism we proposed could give some important information for the future rational design of novel INSTIs overcoming cross-resistance. Furthermore, the combination use of molecular dynamics simulation and residue interaction network analysis can be generally applicable to investigate drug resistance mechanism for other biomolecular systems.
Co-reporter:Wei Geng, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2013 vol. 15(Issue 16) pp:6025-6033
Publication Date(Web):25 Feb 2013
DOI:10.1039/C3CP43720E
In this work, we systematically studied the mechanism for the enhanced photocatalytic activities of TiO2–graphene composites by using density functional theory (DFT) calculations. The studied composites include: TiO2–pristine graphene, TiO2–graphene with defect, as well as TiO2–graphene oxide. The results from geometry optimization can reveal information about the interface structure and anchoring orientation of the composites. The calculated electronic properties including total and difference charge density, as well as charge population, demonstrate the polarization and electron redistribution for the composites. Projected density of states and energy bands can provide some useful information about the photocatalytic mechanism involving the electrons excitation from the O-2p orbital on the valence band to the C-2p on the conduction band maximum for the composites. The results of our study can provide some useful information for understanding the detailed molecular mechanism of the better performance of composites compared to the individual components.
Co-reporter:Shuzhen He, Yonghua Shao, Lingling Fan, Zhiping Che, Hui Xu, Xiaoyan Zhi, Juanjuan Wang, Xiaojun Yao, and Huan Qu
Journal of Agricultural and Food Chemistry 2013 Volume 61(Issue 3) pp:618-625
Publication Date(Web):January 1, 2013
DOI:10.1021/jf305011n
In continuation of our program aimed at the discovery and development of natural-product-based insecticidal agents, we have synthesized three series of novel 4-acyloxy compounds derived from podophyllotoxin modified in the A and C rings, which is isolated as the main secondary metabolite from the roots and rhizomes of Podophyllum hexandrum. Their insecticidal activity was preliminarily evaluated against the pre-third-instar larvae of Mythimna separata in vivo. Compound 9g displayed the best promising insecticidal activity. It revealed that cleavage of the 6,7-methylenedioxy group of podophyllotoxin will lead to a less active compound and that the C-4 position of podophyllotoxin was the important modification location. A quantitative structure–activity relationship (QSAR) model was developed by genetic algorithm combined with multiple linear regression (GA-MLR). For this model, the squared correlation coefficient (R2) is 0.914, the leave-one-out cross-validation correlation coefficient (Q2LOO) is 0.881, and the root-mean-square error (RMSE) is 0.024. Five descriptors, BEHm2, Mor14v, Wap, G1v, and RDF020e, are likely to influence the biological activity of these compounds. Among them, two important ones are BEHm2 and Mor14v. This study will pave the way for further design, structural modification, and development of podophyllotoxin derivatives as insecticidal agents.
Co-reporter:Guofei Jin;Zhongduo Yang;Weiwei Xue;Jie Sheng;Yin Shi;Xiaojun Yao
Chinese Journal of Chemistry 2013 Volume 31( Issue 9) pp:1228-1233
Publication Date(Web):
DOI:10.1002/cjoc.201300441
Abstract
New isoconessimine derivatives were synthesized from conessine (1) and evaluated as acetylcholinesterase (AChE) inhibitors. The derivatives were prepared via two reaction steps, N-demethylation and nucleophilic substitution. All of the synthesized derivatives exhibited more potential anti-acetylcholinesterase activities than conessine (1) (IC50=16 µmol·L−1) and isoconessimine (2) (IC50>300 µmol·L−1). Compound 7b (3β-[methyl-[2-(4-nitrophenoxy)ethyl]amino]con-5-enine) showed the most potent inhibitory activity with an IC50 of 110 nmol/L which is close to that of reference compound huperzine A (IC50=70 nmol/L). The mode of AChE inhibition by 7b was reversible and non-competitive. In addition, molecular modeling was performed to explore the binding mode of inhibitor 7b at the active site of AChE and the results showed that 7b could be docked into the acetylcholinesterase active site and compound 7b had hydrophobic interactions with Trp279 and Leu282.
Co-reporter:Lili Xi, Shuyan Li, Yuhui Wei, Xin'an Wu, Huanxiang Liu, Xiaojun Yao
Chemometrics and Intelligent Laboratory Systems 2013 Volume 126() pp:76-82
Publication Date(Web):15 July 2013
DOI:10.1016/j.chemolab.2013.04.019
•Features weighted by amino acid properties are used to represent protein sequence.•A stable and predictive model is built to recognize two folding kinetics pathways.•The amino acid properties affecting folding kinetics pathways are explored.Recognition of protein folding kinetics pathways is an effective approach for the study of protein folding behaviors, and thereby to get a better understanding of mechanism that how a protein folds into a functional structure. In this study, we presented a novel method for the classification of protein folding kinetics pathways based on a new class of features weighted by amino acid properties, which were derived from protein primary sequence. According to the leave-one-out and bootstrap cross-validation results, the model with eight features was the best one, and it achieved a satisfactory prediction accuracy of 91.67% for training set; while n-fold cross-validation had also been performed and the results showed that the built model was stable. Besides, the external test set was employed to evaluate the predictive ability of the built model. The accuracy for external test set achieved 88.24% and MCC was 0.79. Next, the selected important features were analyzed for a better understanding of the protein folding mechanisms. The analysis suggests that long-range interaction and unfolding Gibbs free energy change are important factors in determining the protein folding kinetics pathways. Besides, hydrophobicity, secondary structure and charges are also implied to be the important properties that affect the behavior of protein folding.
Co-reporter:Wei Geng, Xuefei Zhao, Huanxiang Liu, and Xiaojun Yao
The Journal of Physical Chemistry C 2013 Volume 117(Issue 20) pp:10536-10544
Publication Date(Web):April 30, 2013
DOI:10.1021/jp401733h
The structures as well as electronic and optical properties of the ZnO/graphene composites were theoretically studied by density functional theory calculations. Graphene was composited on monolayer and bilyer ZnO as well as wurtzite ZnO thick slab (0001) surface with zinc and oxygen terminated. We calculated and analyzed the binding energies, difference charge densities, PDOSs, work functions, and optical properties of the composites. It was found that the electronic properties of graphene were retained when graphene combined with ZnO layers. Graphene on the ZnO thick slab (0001) surface with zinc terminated shows obvious electronic doping and enhanced work function. On the contrary, graphene on the ZnO thick slab (0001) surface with oxygen terminated suggested hole doping and decreased work function. The optical properties were also tunable by changing interface structure.
Co-reporter:Weiwei Xue, Ji Qi, Ying Yang, Xiaojie Jin, Huanxiang Liu and Xiaojun Yao
Molecular BioSystems 2012 vol. 8(Issue 8) pp:2135-2144
Publication Date(Web):20 Apr 2012
DOI:10.1039/C2MB25114K
Raltegravir is the first FDA-approved drug targeting the strand transfer step of HIV-1 integration. However, the rapid emergence of viral strains that are highly resistant to raltegravir has become a critical problem. Unfortunately, the detailed molecular mechanism of how HIV-1 integrase (IN) mutations actually confer drug resistance is not well understood. In the present study, starting from our previously constructed complex of HIV-1 IN and viral DNA, we employed molecular dynamics (MD) simulation and molecular mechanics generalized Born surface area (MM-GBSA) calculation, to uncover the molecular mechanism behind the resistant mechanism of HIV-1 IN to raltegravir. The values of the calculated binding free energy follow consistently the experimentally observed ranking of resistance levels. A detailed analysis of the results of MD simulation suggests that the Tyr143 located in the 140s loop (e.g., residues from Gly140 to Gly149) is a key anchoring residue that leads to stable raltegravir binding. The decrease in the interaction at this residue is one of the key reasons responsible for the resistance of HIV-1 IN to raltegravir. Additionally, the calculation results also proved that the 3′ adenosine flip in different conformations in the wild-type and mutant HIV-1 IN–viral DNA complexes play an important role in raltegravir binding. Our results could provide a structural and energetic understanding of the raltegravir-resistant mechanism at the atomic level and provide some new clues on how to design new drugs that may circumvent the known resistance mutations.
Co-reporter:Ying Yang, Huanxiang Liu and Xiaojun Yao
Molecular BioSystems 2012 vol. 8(Issue 8) pp:2106-2118
Publication Date(Web):17 Apr 2012
DOI:10.1039/C2MB25042J
The formation of a p38 MAPK and MAPK-activated protein kinase 2 (MK2) signaling complex is physiologically relevant to cellular responses such as the proinflammatory cytokine production. The interaction between p38α isoform and MK2 is of great importance for this signaling. In this study, molecular dynamics simulation and binding free energy calculation were performed on the MK2–p38α signaling complex to investigate the protein–protein interaction between the two proteins. Dynamic domain motion analyses were performed to analyze the conformational changes between the unbound and bound states of proteins during the interaction. The activation loop, αF–I helices, and loops among α helices in the C-lobe of MK2 are found to be highly flexible and exhibit significant changes upon p38α binding. The results also show that after the binding of p38α, the N- and C-terminal domains of MK2 display an opening and twisting motion centered on the activation loop. The molecular mechanics Poisson–Boltzmann and generalized-Born surface area (MM-PB/GBSA) methods were used to calculate binding free energies between MK2 and p38α. The analysis of the components of binding free energy calculation indicates that the van der Waals interaction and the nonpolar solvation energy provide the driving force for the binding process, while the electrostatic interaction contributes critically to the specificity, rather than to MK2–p38α binding affinity. The contribution of each residue at the interaction interface to the binding affinity of MK2 with p38α was also analyzed by free energy decomposition. Several important residues responsible for the protein–protein interaction were also identified.
Co-reporter:Weiwei Xue, Meixia Wang, Xiaojie Jin, Huanxiang Liu and Xiaojun Yao
Molecular BioSystems 2012 vol. 8(Issue 10) pp:2753-2765
Publication Date(Web):13 Jun 2012
DOI:10.1039/C2MB25157D
Hepatitis C virus (HCV) bifunctional NS3/4A is an attractive anti-HCV drug target, as both the protease and helicase functions are required for viral infection and replication. Although the first generation of NS3/4A protease inhibitors (PIs) has focused almost exclusively on the interaction with the protease domain alone, recent studies have shown that PIs also inhibit the full-length NS3/4A protein. However, the detailed molecular mechanism of the interaction between protease inhibitors, as well as the peptide substance with the full-length NS3/4A protein, remains poorly understood. Herein, starting from the recently determined crystal structure of an inhibitor (inhibitor 1) bound to the full-length NS3/4A protein, the structures of the full-length NS3/4A complexed with inhibitor ITMN-191 (by InterMune/Roche; Phase II) and substrate 4B5A (the viral cleavage product peptide) were built. Then, residue interaction network (RIN) analysis, molecular dynamics (MD) simulation, binding free energy calculation, decomposition of free energies on per-residue and dynamic substrate recognition pattern analysis were employed to uncover the structural and energetic basis of inhibitor and substrate binding mode in the binding cleft located at the interface of the protease and helicase domains of the full-length NS3/4A. The results from our study reveal that both the protease and helicase residues of the NS3/4A participate in the interactions with the inhibitor 1, ITMN-191 and 4B5A. Additional analysis of the NS3/4A substrate and inhibitor envelopes reveals the areas where the consensus inhibitor volume extended beyond the substrate envelope. These areas correspond to drug resistance mutations including Arg155, Ala156 and Asp168 at the protease active site as well as the two conserved helicase residues Gln526 and His528 that strongly interact with the inhibitors. Thus, the findings of this study will be very useful for understanding the interaction mechanism between the inhibitor (substrate) and NS3/4A and also for the rational design and development of new potent molecules targeting the full-length NS3/4A.
Co-reporter:Jingjing Guo;Xiaoting Wang;Huijun Sun;Huanxiang Liu;Yulin Shen;Xiaojun Yao
Chemical Biology & Drug Design 2012 Volume 79( Issue 6) pp:1025-1032
Publication Date(Web):
DOI:10.1111/j.1747-0285.2012.01357.x
Virus-specific cytotoxic T lymphocytes contribute to the control of virus infections including those caused by influenza viruses. However, during the evolution of influenza A viruses, variations in cytotoxic T lymphocytes epitopes have been observed and it will affect the recognition by virus-specific cytotoxic T lymphocytes and the human virus-specific cytotoxic T lymphocytes response in vitro. Here, to gain further insights into the molecular mechanism of the virus-specific cytotoxic T lymphocytes immunity, the class I major histocompatibility complex-encoded HLA-B*3501 protein with six different NP418-426 antigenic peptides emerging from 1918 to 2009 pandemic influenza A virus were studied by molecular dynamics simulation. Dynamical and structural properties (such as atomic fluctuations, solvent-accessible surface areas, binding free energy), based on the solvated protein-peptide complexes, were compared. Free energy calculations emphasized the important role of the secondary anchors (positions 2 and 9) in influencing the binding of MHC-I with antigenic non-apeptides. Furthermore, major interactions with peptides were gained from HLA-B*3501 residues: Tyr7, Ile66, Lys146, Trp147, and Tyr159. Detailed analysis could help to understand how different NP418-426 mutants effectively bind with the HLA-B*3501.
Co-reporter:Yi Wang, Yonghua Shao, Yangyang Wang, Lingling Fan, Xiang Yu, Xiaoyan Zhi, Chun Yang, Huan Qu, Xiaojun Yao, and Hui Xu
Journal of Agricultural and Food Chemistry 2012 Volume 60(Issue 34) pp:8435-8443
Publication Date(Web):August 14, 2012
DOI:10.1021/jf303069v
In continuation of our program aimed at the discovery and development of natural-product-based insecticidal agents, 33 isoxazoline and oxime derivatives of podophyllotoxin modified in the C and D rings were synthesized and their structures were characterized by Proton nuclear magnetic resonance (1H NMR), high-resolution mass spectrometry (HRMS), electrospray ionization–mass spectrometry (ESI–MS), optical rotation, melting point (mp), and infrared (IR) spectroscopy. The stereochemical configurations of compounds 5e, 5f, and 9f were unambiguously determined by X-ray crystallography. Their insecticidal activity was evaluated against the pre-third-instar larvae of northern armyworm, Mythimna separata (Walker), in vivo. Compounds 5e, 9c, 11g, and 11h especially exhibited more promising insecticidal activity than toosendanin, a commercial botanical insecticide extracted from Melia azedarach. A genetic algorithm combined with multiple linear regression (GA–MLR) calculation is performed by the MOBY DIGS package. Five selected descriptors are as follows: one two-dimensional (2D) autocorrelation descriptor (GATS4e), one edge adjacency indice (EEig06x), one RDF descriptor (RDF080v), one three-dimensional (3D) MoRSE descriptor (Mor09v), and one atom-centered fragment (H-052) descriptor. Quantitative structure–activity relationship studies demonstrated that the insecticidal activity of these compounds was mainly influenced by many factors, such as electronic distribution, steric factors, etc. For this model, the standard deviation error in prediction (SDEP) is 0.0592, the correlation coefficient (R2) is 0.861, and the leave-one-out cross-validation correlation coefficient (Q2loo) is 0.797.
Co-reporter:Ying Yang, Yulin Shen, Shuyan Li, Nengzhi Jin, Huanxiang Liu and Xiaojun Yao
Molecular BioSystems 2012 vol. 8(Issue 11) pp:3049-3060
Publication Date(Web):24 Aug 2012
DOI:10.1039/C2MB25217A
Because of the high conservation of ATP-binding sites in kinases, the quest for selective kinase inhibitors has been increasingly urgent in recent years. The Aurora kinase family represents attractive targets in cancer therapy and several small molecule inhibitors targeting Aurora kinases are undergoing clinical trials. Among them, MLN8054 has been proved to be a selective Aurora-A inhibitor, and is currently being evaluated in a phase I trial for patients with advanced solid tumors. But the detailed selectivity mechanism of MLN8054 towards Aurora-A over Aurora-B is still not resolved. In the present work, this selectivity mechanism was investigated using molecular dynamics simulations and binding free energy calculations. The predicted binding conformations and binding affinities of MLN8054 to Aurora-A and its mutant that mimics Aurora-B suggest that there exists stronger interaction between MLN8054 and Aurora-A through an induced DFG-up conformation. Further analyses can provide some information about the structural basis for the selectivity mechanism. Binding of MLN8054 to Aurora-A induces the conformation of the activation loop to adopt an unusual DFG-up conformation and opens the hydrophobic pocket of the active site, thus increasing the interaction between MLN8054 and the residue Val279. The residue Glu177 in Aurora-B displays electrostatic repulsion with MLN8054, while the corresponding Thr217 in Aurora-A has favorable interactions with MLN8054. The conformation change and the difference between the binding pockets for Aurora-A and B are key factors responsible for the selectivity. The results could be helpful for the rational design of selective inhibitors of Aurora-A kinase.
Co-reporter:Jingjing Guo;Xiaoting Wang;Huijun Sun;Huanxiang Liu
Journal of Molecular Modeling 2012 Volume 18( Issue 4) pp:1421-1430
Publication Date(Web):2012/04/01
DOI:10.1007/s00894-011-1159-4
Insulin-like growth factor-II (IGF-II) is a key regulator of cell growth, survival, migration and differentiation, and is thus pivotal in many cancers. An individual with a high IGF-II level is at high risk of developing cancer, whereas IGF2R is implicated as being important in tumor suppression. Thus, uncovering the essence of the IGF-II/IGF2R interaction is very important to understanding the origin of the tumor-suppressing effect of IGF2R. In this study, in order to investigate the interaction of the IGF-II/IGF2R complex and to characterize the binding hot spots of this interaction, a 10 ns molecular dynamics simulation combined with MM-PBSA/MM-GBSA computations and computational alanine scanning was performed on the IGF-II/IGF2R complex. From the results of the free-energy decomposition and the computational alanine scanning calculation, we identified the key residues in the IGF-II/IGF-2R interaction. The results from the calculation were consistent with reported experimental mutagenesis studies. The information on the interaction of IGF-II and IGF2R obtained is vital for understanding how the structure of IGF2R influences the function of IGF-II in growth and development. This study will also lead to new opportunities to develop molecular probes that can assist in diagnostic screening, and even novel approaches to controlling tumor development.
Co-reporter:Ying Yang, Jin Qin, Huanxiang Liu, and Xiaojun Yao
Journal of Chemical Information and Modeling 2011 Volume 51(Issue 3) pp:680-692
Publication Date(Web):February 22, 2011
DOI:10.1021/ci100427j
V600EB-RAF kinase is the most frequent onco-genic protein kinase mutation in melanoma and is a promising target to treat malignant melanoma. In this work, a molecular modeling study combining QM-polarized ligand docking, molecular dynamics, free energy calculation, and three-dimensional quantitative structure−activity relationships (3D-QSAR) was performed on a series of pyridoimidazolone compounds as the inhibitors of V600EB-RAF kinase to understand the binding mode between the inhibitors and V600EB-RAF kinase and the structural requirement for the inhibiting activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by QM-polarized ligand docking strategy. The obtained models have a good predictive ability in both internal and external validation. Furthermore, molecular dynamics simulation and free energy calculations were employed to determine the detailed binding process and to compare the binding mode of the inhibitors with different activities. The binding free energies calculated by MM/PBSA gave a good correlation with the experimental biological activity. The decomposition of free energies by MM/GBSA indicates the van der Waals interaction is the major driving force for the interaction between the inhibitors and V600EB-RAF kinase. The hydrogen bond interactions between the inhibitors with Glu501 and Asp594 of the V600EB-RAF kinase help to stabilize the DFG-out conformation. The results from this study can provide some insights into the development of novel potent V600EB-RAF kinase inhibitors.
Co-reporter:Ying Yang, Yulin Shen, Huanxiang Liu, and Xiaojun Yao
Journal of Chemical Information and Modeling 2011 Volume 51(Issue 12) pp:3235-3246
Publication Date(Web):November 18, 2011
DOI:10.1021/ci200159g
p38 MAP kinase is a promising target for anti-inflammatory treatment. The classical kinase inhibitors imatinib and sorafenib as well as BI-1 and BIRB-796 were reported to bind in the DFG-out form of human p38α, known as type II or allosteric kinase inhibitors. Although DFG-out conformation has attracted great interest in the design of type II kinase inhibitors, the structural requirements for binding and mechanism of stabilization of DFG-out conformation remain unclear. As allosteric inhibition is important to the selectivity of kinase inhibitor, herein the binding modes of imatinib, sorafenib, BI-1 and BIRB-796 to p38α were investigated by molecular dynamics simulation. Binding free energies were calculated by molecular mechanics/Poisson–Boltzmann surface area method. The predicted binding affinities can give a good explanation of the activity difference of the studied inhibitors. Furthermore, binding free energies decomposition analysis and further structural analysis indicate that the dominating effect of van der Waals interaction drives the binding process, and key residues, such as Lys53, Gly71, Leu75, Ile84, Thr106, Met109, Leu167, Asp168, and Phe169, play important roles by forming hydrogen bond, salt bridge, and hydrophobic interactions with the DFG-out conformation of p38α. Finally, we also conducted a detailed analysis of BI-1, imatinib, and sorafenib binding to p38α in comparison with BIRB-796 exploited for gaining potency as well as selectivity of p38 inhibitors. These results are expected to be useful for future rational design of novel type II p38 inhibitors.
Co-reporter:Juan Du;Lili Xi;Beilei Lei;Huanxiang Liu;Xiaojun Yao
Chemical Biology & Drug Design 2011 Volume 77( Issue 4) pp:248-254
Publication Date(Web):
DOI:10.1111/j.1747-0285.2010.01068.x
The c-Jun N-terminal kinases are attractive targets because of their involvement in several diseases. In this work, a combined molecular modeling study for a set of isoquinolones as inhibitors of JNK1 was performed by molecular docking, genetic algorithm–multiple linear regression and comparative molecular field analysis to rationalize the structural requirements responsible for the inhibitory activity of these compounds. Molecular docking study was employed to explore the binding mode of the active compound at the active site of JNK1. Based on the docked conformations, highly predictive 2D, 3D quantitative structure–activity relationship models were developed. The best 2D quantitative structure–activity relationship model was established using genetic algorithm–multiple linear regression method containing four molecular descriptors. The best comparative molecular field analysis model was obtained with a cross-validated coefficient q2 of 0.562, non-cross-validated r2 values of 0.994. The information from quantitative structure–activity relationship models and molecular docking is useful for the design of novel JNK1 inhibitors with improved activities.
Co-reporter:Hai-Long Jiang, Jia Chen, Xiao-Jie Jin, Jun-Li Yang, Ya Li, Xiao-Jun Yao, Quan-Xiang Wu
Tetrahedron 2011 67(47) pp: 9193-9198
Publication Date(Web):
DOI:10.1016/j.tet.2011.09.070
Co-reporter:Ying Yang;Huanxiang Liu;Juan Du;Jin Qin;Xiaojun Yao
Journal of Molecular Modeling 2011 Volume 17( Issue 12) pp:3241-3250
Publication Date(Web):2011 December
DOI:10.1007/s00894-011-1011-x
Inhibition of the protein chaperone Hsp90α is a promising approach for cancer therapy. In this work, a molecular modeling study combining pharmacophore model, molecular docking and three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed to investigate a series of pyrazole/isoxazole scaffold inhibitors of human Hsp90α. The pharmacophore model can provide the essential features required for the biological activities of the inhibitors. The molecular docking study can give insight into the binding mode between Hsp90α and its inhibitors. 3D-QSAR based on CoMFA and CoMSIA models were performed from three different strategies for conformational selection and alignment. The receptor-based models gave the most statistically significant results with cross-validated q2 values of 0.782 and 0.829 and r2 values of 0.909 and 0.968, for CoMFA and CoMSIA respectively. Furthermore, the 3D contour maps superimposed within the binding site of Hsp90α could help to understand the pivotal interaction and the structural requirements for potent Hsp90α inhibitors. The results show 4-position of pyrazole/isoxazole ring requires bulky and hydrophobic groups, and bulky and electron repulsion substituent of 5-amides is favorable for enhancing activity. This study will be helpful for the rational design of new potent Hsp90α inhibitors.
Co-reporter:Jin Qin, Beilei Lei, Lili Xi, Huanxiang Liu, Xiaojun Yao
European Journal of Medicinal Chemistry 2010 Volume 45(Issue 7) pp:2768-2776
Publication Date(Web):July 2010
DOI:10.1016/j.ejmech.2010.02.059
Rho kinase (ROCK) has become an attractive target for the treatment of many diseases such as hypertension, stroke and cancer. In this work, molecular docking and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of ROCK inhibitors. Molecular docking was used to explore the binding mode between the ligands and the receptor. Based on the docked conformations, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed to gain insights into the key structural factors affecting the activity. The results of the molecular modeling studies suggested that further modification of these inhibitors with bulky and hydrophobic groups that accommodated in the distal region of the ROCK binding pocket would improve the activity.
Co-reporter:Yuhui Wei;Lili Xi;Dongxia Chen;Xin'an Wu;Huanxiang Liu;Xiaojun Yao
Journal of Separation Science 2010 Volume 33( Issue 13) pp:1980-1990
Publication Date(Web):
DOI:10.1002/jssc.201000105
Abstract
The essential oils extracted from three kinds of herbs were separated by a 5% phenylmethyl silicone (DB-5MS) bonded phase fused-silica capillary column and identified by MS. Seventy-four of the compounds identified were selected as origin data, and their chemical structure and gas chromatographic retention times (RT) were performed to build a quantitative structure–retention relationship model by genetic algorithm and multiple linear regressions analysis. The predictive ability of the model was verified by internal validation (leave-one-out, fivefold, cross-validation and Y-scrambling). As for external validation, the model was also applied to predict the gas chromatographic RT of the 14 volatile compounds not used for model development from essential oil of Radix angelicae sinensis. The applicability domain was checked by the leverage approach to verify prediction reliability. The results obtained using several validations indicated that the best quantitative structure–retention relationship model was robust and satisfactory, could provide a feasible and effective tool for predicting the gas chromatographic RT of volatile compounds and could be also applied to help in identifying the compound with the same gas chromatographic RT.
Co-reporter:Jin Qin;Lili Xi;Juan Du;Huanxiang Liu;Xiaojun Yao
Chemical Biology & Drug Design 2010 Volume 76( Issue 6) pp:527-537
Publication Date(Web):
DOI:10.1111/j.1747-0285.2010.01030.x
Quantitative structure–activity relationship studies on 54 aminothiazole derivatives as Aurora A kinase inhibitors were performed to explore the important factors affecting their biologic activity. For 2D-quantitative structure–activity relationship study, genetic algorithm combined with multiple linear regression was used to select significant molecular descriptors. The MLR model gave squared correlation coefficient of 0.828 and squared cross-validated correlation coefficient of 0.771 for the training set compounds. Comparative molecular field analysis and comparative molecular similarity indices analysis were used to develop 3D-quantitative structure–activity relationship models. The comparative molecular field analysis model gave cross-validated correlation coefficient q 2 of 0.695 and non-cross-validated correlation coefficient r 2 of 0.977. For comparative molecular similarity indices analysis model, the corresponding q 2 and r 2 were 0.698 and 0.960, respectively. The proposed 3D-quantitative structure–activity relationship models were validated by the test set compounds not used in the modeling process, with values of 0.788 for comparative molecular field analysis and 0.798 for comparative molecular similarity indices analysis. The 3D contour maps suggested that further modification of the aniline group of compound 22 considering electrostatic, hydrophobic and hydrogen bond properties would influence the inhibitory activity. The results from quantitative structure–activity relationship models would be very useful to understand the structure–activity relationship of these inhibitors and to guide the further structural modification of new potential inhibitors.
Co-reporter:Beilei Lei, Lili Xi, Jiazhong Li, Huanxiang Liu, Xiaojun Yao
Analytica Chimica Acta 2009 Volume 644(1–2) pp:17-24
Publication Date(Web):30 June 2009
DOI:10.1016/j.aca.2009.04.019
Quantitative structure-activity relationship (QSAR) studies on a series of selective inhibitors of the cyclin-dependent kinase 4 (CDK4) were performed by using two conventional global modeling methods (multiple linear regression (MLR) and support vector machine (SVM)), local lazy regression (LLR) as well as three consensus models. It is remarkable that the LLR model could improve the performance of the QSAR model significantly. In addition, due to the fact that each model can predict certain compounds more accurately than other models, the above three derived models were all used as submodels to build consensus models using three different strategies: average consensus model (ACM), simple weighted consensus model (SWCM) and hat weighted consensus model (HWCM). Through the analysis of the results, the HWCM consensus strategy, firstly proposed in this work, proved to be more reliable and robust than the best single LLR model, ACM and SWCM models.
Co-reporter:Jiazhong Li, Juan Du, Lili Xi, Huanxiang Liu, Xiaojun Yao, Mancang Liu
Analytica Chimica Acta 2009 Volume 631(Issue 1) pp:29-39
Publication Date(Web):5 January 2009
DOI:10.1016/j.aca.2008.10.026
In this study, the quantitative structure–activity relationship (QSAR) of a series of 2-aminothiazole based Lck inhibitors was investigated. The key structural features responsible for the inhibition activities were discussed in detail. A population of 100 rigorously validated linear QSAR models were established based on the descriptors calculated in DRAGON program and selected by genetic algorithm (GA). A total of 36 descriptors were involved in all the QSAR models. Then the common descriptors appeared in all the models were extracted to build the final QSAR model. As a result, the final 8-parameter QSAR model was established. After analysis of the eight descriptors, some advice was proposed to help the design of possible novel inhibitors with higher bioactivity.
Co-reporter:Jian-Jun Chen, Zheng-Ming Li, Kun Gao, Jin Chang and Xiao-Jun Yao
Journal of Natural Products 2009 Volume 72(Issue 6) pp:1128-1132
Publication Date(Web):May 8, 2009
DOI:10.1021/np900120q
Two new steroids, vladimuliecins A (1) and B (2), were isolated by bioassay-guided fractionation from the rhizome of Vladimiria muliensis. Compounds 1 and 2 are the first examples possessing a pentacyclic 3α,5α-cyclopregnane-type framework. The structures of vladimuliecins A (1) and B (2) and their deacetylated derivative (3) were determined on the basis of IR, MS, 1D NMR, 2D NMR, and X-ray data analyses. The absolute configuration of the 10 stereogenic centers of compounds 1 and 2 was determined to be 3R,5R,6R,8S,9R,10R,13R,14R,17S,20R by means of auxiliary chiral MTPA derivatives and optical rotation calculation. A probable biosynthesis pathway to 1 and 2 is also proposed and discussed. In addition, the cytotoxicity of compounds 1, 2, and 3 was evaluated against selected cancer cell lines, including human leukemia cell (HL-60), human hepatoma cell (SMMC-7721), and human cervical carcinoma cell (HeLa) lines.
Co-reporter:Beilei Lei, Shuyan Li, Lili Xi, Jiazhong Li, Huanxiang Liu, Xiaojun Yao
Journal of Chromatography A 2009 Volume 1216(Issue 20) pp:4434-4439
Publication Date(Web):15 May 2009
DOI:10.1016/j.chroma.2009.03.032
The base sequence autocorrelation (BSA) descriptors were used to describe structures of oligonucleotides and to develop accurate quantitative structure-retention relationship (QSRR) models of oligonucleotides in ion-pair reversed-phase high-performance liquid chromatography. Through the combination use of multiple linear regression (MLR) and genetic algorithm (GA), QSRR models were developed at temperatures of 30 °C, 40 °C, 50 °C, 60 °C and 80 °C, respectively. Satisfactory results were obtained for the single-temperature models (STM). Multi-temperature model (MTM) was also developed that can be used for predicting the retention time at any temperature. The correlation coefficients of retention time prediction for the test set based on the MTM model at 30 °C, 40 °C, 50 °C, 60 °C and 80 °C were 0.978, 0.982, 0.989, 0.988 and 0.996, respectively. The corresponding absolute average relative deviations (AARD) for the test set at each temperature were all less than 1%. The new strategy of feature representation and multi-temperatures modeling is a very promising tool for QSRR modeling with good predictive ability for predicting retention time of oligonucleotides at multiple temperatures under the studied condition.
Co-reporter:Jin Qin, Huanxiang Liu, Jiazhong Li, Yueying Ren, Xiaojun Yao, Mancang Liu
European Journal of Medicinal Chemistry 2009 Volume 44(Issue 7) pp:2888-2895
Publication Date(Web):July 2009
DOI:10.1016/j.ejmech.2008.12.006
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 68 inhibitors of AP-1 and NF-κB mediated transcriptional activations. The CoMFA model produced statistically significant results with the cross-validated q2 of 0.594 and the conventional correlation coefficient r2 of 0.968. The best CoMSIA model was obtained by the combination use of steric, electrostatic, hydrogen-bond donor and acceptor fields. The corresponding q2 and r2 of CoMSIA model were 0.703 and 0.932, respectively. From the cross-validated results, it can be seen that the CoMSIA model has a better predictive ability than CoMFA model due to the importance of the hydrogen bonds for the activity of these inhibitors. The predictive abilities of the two models were further validated by a test set of 15 compounds. The models gave predicted correlation coefficient rpred2 of 0.891 for CoMFA model and 0.810 for CoMSIA model. Based on the above results, we identified the key structural features that may help to design potent inhibitors with improved activities: (1) the NH linker at the position R4 acts as important hydrogen-bond donor and any group on phenyl or 2-thienyl ring of R1 substituent decreases inhibitory activity, (2)further structural modification of compound 50 on the phenyl ring of the quinazoline ring considering steric, electrostatic and hydrogen-bond acceptor properties will influence the inhibitory activity.
Co-reporter:Beilei Lei, Jiazhong Li, Jing Lu, Juan Du, Huanxiang Liu and Xiaojun Yao
Journal of Agricultural and Food Chemistry 2009 Volume 57(Issue 20) pp:9593-9598
Publication Date(Web):September 25, 2009
DOI:10.1021/jf902010g
Molecular docking-guided active conformation selection was used in a quantitative structure−activity relationship (QSAR) study of a series of novel protoporphyrinogen oxidase (PPO) inhibitors with herbicidal activities. The developed model can be used for the rational and accurate prediction of herbicidal activities of these inhibitors from their molecular structures. Molecular docking study was carried out to dock the inhibitors into the PPO active site and to obtain the rational active conformations. Based on the conformations generated from molecular docking, satisfactory predictive results were obtained by a genetic algorithm-multiple linear regression (GA-MLR) model according to the internal and external validations. The model gave a correlation coefficient R2 of 0.972 and 0.953 and an absolute average relative deviation AARD of 2.24% and 2.75% for the training set and test set, respectively. The results from this work demonstrate that the molecular docking-guided active conformation selection strategy is rational and useful in the QSAR study of these PPO inhibitors and for the quantitative prediction of their herbicidal activities. The results obtained could be helpful to the design of new derivatives with potential herbicidal activities.
Co-reporter:Hui Xu, Juanjuan Wang, Huijun Sun, Min Lv, Xuan Tian, Xiaojun Yao and Xing Zhang
Journal of Agricultural and Food Chemistry 2009 Volume 57(Issue 17) pp:7919-7923
Publication Date(Web):August 18, 2009
DOI:10.1021/jf9020812
By using podophyllotoxin as a phytoinsecticidal lead compound, 15 novel aromatic esters of 4′-demethyl-4-deoxypodophyllotoxin were semisynthesized and preliminarily tested for their insecticidal activity against the pre-third-instar larvae of Mythimna separata Walker in vivo for the first time. Among all of the tested compounds, especially two compounds, 4m and 4o, containing a pyridinyl group, for which final corrected mortality rates against M. separata at 1 mg/mL were 62.9 and 59.2%, respectively, showed the most promising and pronounced insecticidal activity as compared with toosendanin, a commercial insecticide derived from Melia azedarach. The quantitative structure−activity relationships (QSAR) of compounds 4a−4o showed that the relative number of benzene rings and final heat of formation were very important descriptors to their insecticidal activity.
Co-reporter:Juan Du, Beilei Lei, Jin Qin, Huanxiang Liu, Xiaojun Yao
Journal of Molecular Graphics and Modelling 2009 Volume 27(Issue 5) pp:642-654
Publication Date(Web):January 2009
DOI:10.1016/j.jmgm.2008.10.006
The vascular endothelial growth factor (VEGF) and its receptor tyrosine kinases VEGFR-2 or kinase insert domain receptor (KDR) are attractive targets for the development of novel anticancer agents. In the present work, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of selective inhibitors of KDR. Docking studies were performed to explore the binding mode between all of the inhibitors and the KDR and produce the bioactive conformation of each compound in the whole dataset. Two conformer-based alignment strategies were employed to construct reliable 3D-QSAR models. The docked conformer-based alignment strategy gave the best 3D-QSAR models. The best CoMFA and CoMSIA models gave a cross-validated coefficient q2 of 0.546 and 0.715, non-cross-validated r2 values of 0.936 and 0.961, predicted r2 values of 0.673 and 0.797, respectively. The information obtained from molecular modeling studies were very helpful to design some novel selective inhibitors of KDR with desired activity.
Co-reporter:Juan Du, Jin Qin, Huanxiang Liu, Xiaojun Yao
Journal of Molecular Graphics and Modelling 2008 Volume 27(Issue 2) pp:95-104
Publication Date(Web):September 2008
DOI:10.1016/j.jmgm.2008.03.003
Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor β (TRβ), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q2 (cross-validated) values 0.600 and 0.616 and non-cross-validated r2 values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (rpred2) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRβ. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor β but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.
Co-reporter:Beilei Lei;Juan Du;Shuyan Li;Huanxiang Liu
Journal of Computer-Aided Molecular Design 2008 Volume 22( Issue 10) pp:711-725
Publication Date(Web):2008 October
DOI:10.1007/s10822-008-9230-7
Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a series of thiazolone derivatives as novel inhibitors bound to the allosteric site of hepatitis C virus (HCV) NS5B polymerase were developed based on CoMFA and CoMSIA analyses. Two different conformations of the template molecule and the combinations of different CoMSIA field/fields were considered to build predictive CoMFA and CoMSIA models. The CoMFA and CoMSIA models with best predictive ability were obtained by the use of the template conformation from X-ray crystal structures. The best CoMFA and CoMSIA models gave q2 values of 0.621 and 0.685, and r2 values of 0.950 and 0.940, respectively for the 51 compounds in the training set. The predictive ability of the two models was also validated by using a test set of 16 compounds which gave rpred2 values of 0.685 and 0.822, respectively. The information obtained from the CoMFA and CoMSIA 3D contour maps enables the interpretation of their structure-activity relationship and was also used to the design of several new inhibitors with improved activity.
Co-reporter:Shuyan Li, Xiaojun Yao, Huanxiang Liu, Jiazhong Li, Botao Fan
Analytica Chimica Acta 2007 Volume 584(Issue 1) pp:37-42
Publication Date(Web):12 February 2007
DOI:10.1016/j.aca.2006.11.037
Co-reporter:Jiazhong Li, Huanxiang Liu, Xiaojun Yao, Mancang Liu, Zhide Hu, Botao Fan
Analytica Chimica Acta 2007 Volume 581(Issue 2) pp:333-342
Publication Date(Web):9 January 2007
DOI:10.1016/j.aca.2006.08.031
The least-squares support vector machines (LS-SVMs), as an effective modified algorithm of support vector machine, was used to build structure–activity relationship (SAR) models to classify the oxindole-based inhibitors of cyclin-dependent kinases (CDKs) based on their activity. Each compound was depicted by the structural descriptors that encode constitutional, topological, geometrical, electrostatic and quantum-chemical features. The forward-step-wise linear discriminate analysis method was used to search the descriptor space and select the structural descriptors responsible for activity. The linear discriminant analysis (LDA) and nonlinear LS-SVMs method were employed to build classification models, and the best results were obtained by the LS-SVMs method with prediction accuracy of 100% on the test set and 90.91% for CDK1 and CDK2, respectively, as well as that of LDA models 95.45% and 86.36%. This paper provides an effective method to screen CDKs inhibitors.
Co-reporter:Yueying Ren, Huanxiang Liu, Xiaojun Yao, Mancang Liu
Analytica Chimica Acta 2007 Volume 589(Issue 1) pp:150-158
Publication Date(Web):18 April 2007
DOI:10.1016/j.aca.2007.02.058
Quantitative structure–property relationship (QSPR) models were developed to predict degradation rate constants of ozone tropospheric and to study the degradation reactivity mechanism of 116 diverse compounds. DUPLEX algorithm was utilized to design the training and test sets. Seven molecular descriptors selected by the heuristic method (HM) were used as inputs to perform multiple linear regression (MLR), support vector machine (SVM) and projection pursuit regression (PPR) studies. The PPR model performs best both in the fitness and in the prediction capacity. For the test set, it gave a predictive correlation coefficient (R) of 0.955, root mean square error (RMSE) of 1.041 and absolute average relative deviation (AARD, %) of 4.663, respectively. The results proved that PPR is a useful tool that can be used to solve the nonlinear problems in QSPR. In addition, methods used in this paper are simple, practical and effective for chemists to predict the ozone degradation rate constants of compounds in troposphere.
Co-reporter:Yueying Ren, Huanxiang Liu, Xiaojun Yao, Mancang Liu
Journal of Chromatography A 2007 Volume 1155(Issue 1) pp:105-111
Publication Date(Web):29 June 2007
DOI:10.1016/j.chroma.2007.04.004
A novel approach is described for the prediction of gas chromatographic Kováts retention indices of 150 acyclic C5–C8 alkenes on two stationary phases (polydimethylsiloxane, PDMS, and squalane, SQ). The heuristic method was used to build multiple linear regression models using descriptors calculated by MODLESLAB software and CODESSA program. The resulting quantitative structure–retention relationship (QSRR) models were well-correlated, with predictive R2 values of 0.970 and 0.958 for retention indices on PDMS and SQ columns, respectively. 1Ωp, a three-dimensional (3D) topographic index, was found to play the most important role in the description of the chromatographic retention behavior of the alkenes in these two stationary phases. Moreover, this index could completely distinguish different isomers of alkene. Therefore, it can also be extended to distinguish different isomers of other compounds so that can well describe their quantitative structure–retention relationships.
Co-reporter:Jiazhong Li, Huanxiang Liu, Xiaojun Yao, Mancang Liu, Zhide Hu, Botao Fan
Chemometrics and Intelligent Laboratory Systems 2007 Volume 87(Issue 2) pp:139-146
Publication Date(Web):15 June 2007
DOI:10.1016/j.chemolab.2006.11.004
An effective quantitative structure–activity relationship (QSAR) model of a series of acyl ureas as inhibitors of human liver glycogen phosphorylase a (hlGPa), was built using a modified algorithm of support vector machine (SVM), least squares support vector machines (LS-SVMs). Each compound was depicted by structural descriptors that encode constitutional, topological, geometrical, electrostatic and quantum-chemical features. The Heuristic Method (HM) was used to search the feature space and select the structural descriptors responsible for activity. The LS-SVMs and multiple linear regression (MLR) methods were performed to build QSAR models. The LS-SVMs model gives better results with the predicted correlation coefficient (R) 0.899 and mean-square errors (MSE) 0.148 for the test set, as well as that 0.88 and 0.174 in the MLR model. The prediction results indicate that LS-SVMs is a potential method in QSAR study and can be used as a tool of drug screening.
Co-reporter:Yueying Ren, Huanxiang Liu, Shuyan Li, Xiaojun Yao, Mancang Liu
Bioorganic & Medicinal Chemistry Letters 2007 Volume 17(Issue 9) pp:2474-2482
Publication Date(Web):1 May 2007
DOI:10.1016/j.bmcl.2007.02.025
Quantitative structure–activity relationship (QSAR) has been applied to a set of thyroid hormone receptor β1 (TRβ1) antagonists, which are of special interest because of their potential role in safe therapies for nonthyroid disorders while avoiding the cardiac side effects. Using the calculated structural descriptors by CODESSA program, principal component analysis (PCA) was performed on the whole compounds to assist the separation of the data into the training set and the test set in QSAR analysis. Six molecular descriptors selected by genetic algorithm (GA) were used as inputs for a projection pursuit regression (PPR) study to develop a more accurate QSAR model. The PPR model performs well both in the fitting and prediction capacity. For the test set, it gave a predictive correlation coefficient (R) of 0.9450, root mean square error (RMSE) of 0.4498, and absolute average relative deviation (AARD) of 4.19%, respectively, confirming the ability of PPR for the prediction of the binding affinities of compounds to β1 isoform of human thyroid hormone receptor (TRβ1).Proportion of compounds within a given deviation from the experimental pIC50 by PPR.
Co-reporter:Yueying Ren;Huanxiang Liu;Xiaojun Yao
Analytical and Bioanalytical Chemistry 2007 Volume 388( Issue 1) pp:165-172
Publication Date(Web):2007 May
DOI:10.1007/s00216-007-1188-0
Quantitative structure–retention relationship (QSRR) models were constructed for the GC×GC–TOFMS retention time of 209 polychlorinated biphenyl (PCB) congeners. Principal component analysis (PCA) was used to recognize groups of samples with similar behavior and assist the separation of the data into training and test sets. The best multi-linear regression (BMLR) method was used for the systematic development of multi-linear regression equations; the best regression model involved four descriptors which were related to GC×GC–TOFMS chromatographic retention of PCBs. The obtained model has good predictive ability. For the test set, it gave a predictive correlation coefficient (R) of 0.988 and an average absolute relative deviation (AARD) of 3.08%. Results of a six-fold cross-validation procedure, which were in accordance with those from validation of training and test sets, demonstrated that this model was reliable. Additionally, this paper provides a simple, practical, and effective method for analytical chemists to predict the retention times of PCBs in GC.
Co-reporter:Huanxiang Liu, Xiaojun Yao, Mancang Liu, Zhide Hu, Botao Fan
Talanta 2007 Volume 71(Issue 1) pp:258-263
Publication Date(Web):15 January 2007
DOI:10.1016/j.talanta.2006.03.058
Multiple linear regression and projection pursuit regression were used to develop the linear and nonlinear models for predicting the gas-phase reduced ion mobility constant (K0) of 159 diverse compounds. The six descriptors selected by heuristic method were used as the inputs of the linear and nonlinear models. The linear and nonlinear models gave very satisfactory results; the square of correlation coefficient was 0.9082 and 0.9379, the squared standard error was 0.0043 and 0.0030, respectively for the whole data set. The proposed models can identify and provide some insight into what structural features are related to the K0 of compounds. They can also help to understand the separation mechanism in ion mobility spectrometry. Additionally, this paper provided two simple, practical and effective methods for analytical chemists to predict the K0 of compounds in ion mobility spectrometry.
Co-reporter:Yueying Ren, Huanxiang Liu, Chunxia Xue, Xiaojun Yao, Mancang Liu, Botao Fan
Analytica Chimica Acta 2006 Volume 572(Issue 2) pp:272-282
Publication Date(Web):21 July 2006
DOI:10.1016/j.aca.2006.05.027
The support vector machine (SVM), recently developed from machine learning community, was used to develop a nonlinear binary classification model of skin sensitization for a diverse set of 131 organic compounds. Six descriptors were selected by stepwise forward discriminant analysis (LDA) from a diverse set of molecular descriptors calculated from molecular structures alone. These six descriptors could reflect the mechanic relevance to skin sensitization and were used as inputs of the SVM model. The nonlinear model developed from SVM algorithm outperformed LDA, which indicated that SVM model was more reliable in the recognition of skin sensitizers. The proposed method is very useful for the classification of skin sensitizers, and can also be extended in other QSAR investigation.
Co-reporter:Huanxiang Liu, Xiaojun Yao, Mancang Liu, Zhide Hu, Botao Fan
Analytica Chimica Acta 2006 Volume 558(1–2) pp:86-93
Publication Date(Web):3 February 2006
DOI:10.1016/j.aca.2005.10.074
Based on calculated molecular descriptors from the solutes’ structure alone, the micelle–water partition coefficients of 103 solutes in micellar electrokinetic chromatography (MEKC) were predicted using the heuristic method (HM). At the same time, in order to show the influence of different molecular descriptors on the micelle–water partition of solute and to well understand the retention mechanism in MEKC, HM was used to build several multivariable linear models using different numbers of molecular descriptors. The best 6-parameter model gave the following results: the square of correlation coefficient R2 was 0.958 and the mean relative error was 3.98%, which proved that the predictive values were in good agreement with the experimental results. From the built model, it can be concluded that the hydrophobic, H-bond, polar interactions of solutes with the micellar and aqueous phases are the main factors that determine their partitioning behavior. In addition, this paper provided a simple, fast and effective method for predicting the retention of the solutes in MEKC from their structures and gave some insight into structural features related to the retention of the solutes.
Co-reporter:Yueying Ren, Huanxiang Liu, Xiaojun Yao, Mancang Liu, Zhide Hu, Botao Fan
Journal of Colloid and Interface Science 2006 Volume 302(Issue 2) pp:669-672
Publication Date(Web):15 October 2006
DOI:10.1016/j.jcis.2006.06.072
Quantitative structure–property relationship models were developed to predict cloud points and study the cloud phenomena of nonionic surfactants in aqueous solution. Four descriptors were selected by the heuristic method as the inputs of multiplier linear regression and support vector machine (SVM) models. Very satisfactory results were obtained. SVM models performed better both in fitness and in prediction capacity. For the test set, they gave a predictive correlation coefficient (R) of 0.9882, root mean squared error of 4.2727, and absolute average relative deviation of 9.5490, respectively. The proposed models can identify and provide some insight into what structural features are related to the cloud points of compounds, i.e., the molecular size, structure, and isomerism of the hydrocarbon moiety and the degree of oxyethylation. They can also help to understand the cloud phenomena of nonionic surfactants in aqueous solution. Additionally, this paper provides two simple, practical, and effective methods for analytical chemists to predict the cloud points of nonionic surfactants in aqueous solution.Plot of predicted CP values vs experimental CP values for the training set and test set based on the 4-parameter model by SVM.
Co-reporter:Bo Wei, Zhong-Duo Yang, Xiao-wei Chen, Shuang-Yan Zhou, Hai-Tao Yu, Jing-Yun Sun, Xiao-Jun Yao, Yong-gang Wang, Hong-Yan Xue
Fitoterapia (September 2016) Volume 113() pp:158-163
Publication Date(Web):1 September 2016
DOI:10.1016/j.fitote.2016.08.005
Four novel lactams, colletotrilactam A–D (1–4), along with six known compounds (5–10) were isolated from the culture broth of Colletotrichum gloeosporioides GT-7, a fungal endophyte of Uncaria rhynchophylla. The structures of these compounds were elucidated by comprehensive NMR spectroscopy. Isolates were tested for monoamine oxidase (MAO) inhibitory activity and compound 9 showed potent MAO inhibitory activity with IC50 value of 8.93 ± 0.34 μg/mL, when the IC50 value of iproniazid as a standard was 1.80 ± 0.5 μg/mL.Download high-res image (262KB)Download full-size image
Co-reporter:Yonghua Shao, Jining Liu, Meixia Wang, Lili Shi, Xiaojun Yao, Paola Gramatica
Atmospheric Environment (May 2014) Volume 88() pp:
Publication Date(Web):1 May 2014
DOI:10.1016/j.atmosenv.2013.12.018
•Integrated QSPR models were developed based on the larger dataset.•Different modeling methods were employed to build QSPR model.•The QSPR development and validation strictly followed the OECD principles.•The performance is superior to the previous reported QSPR models.The soil sorption coefficient (Koc) is a key physicochemical parameter to assess the environmental risk of organic compounds. To predict soil sorption coefficient in a more effective and economical way, here, quantitative structure-property relationship (QSPR) models were developed based on a large diverse dataset including 964 non-ionic organic compounds. Multiple linear regression (MLR), local lazy regression (LLR) and least squares support vector machine (LS-SVM) were utilized to develop QSPR models based on the four most relevant theoretical molecular descriptors selected by genetic algorithms-variable subset selection (GA-VSS) procedure. The QSPR development strictly followed the OECD principles for QSPR model validation, thus great attentions were paid to internal and external validations, applicability domain and mechanistic interpretation. The obtained results indicate that the LS-SVM model performed better than the MLR and the LLR models. For best LS-SVM model, the correlation coefficients (R2) for the training set was 0.913 and concordance correlation coefficient (CCC) for the prediction set was 0.917. The root-mean square errors (RMSE) were 0.330 and 0.426, respectively. The results of internal and external validations together with applicability domain analysis indicate that the QSPR models proposed in our work are predictive and could provide a useful tool for prediction soil sorption coefficient of new compounds.Download high-res image (203KB)Download full-size image
Co-reporter:Jian-Li Dong, Zhong-Duo Yang, Shuang-Yan Zhou, Hai-Tao Yu, Xiao-Jun Yao, Hong-Yan Xue, Zong-Mei Shu
Phytochemistry Letters (March 2017) Volume 19() pp:259-262
Publication Date(Web):March 2017
DOI:10.1016/j.phytol.2017.01.016
Co-reporter:Xiaojie Jin, Yonghua Shao, Qifeng Bai, Weiwei Xue, Huanxiang Liu, Xiaojun Yao
Biochimica et Biophysica Acta (BBA) - General Subjects (June 2016) Volume 1860(Issue 6) pp:1173-1180
Publication Date(Web):June 2016
DOI:10.1016/j.bbagen.2016.02.007
Co-reporter:Jingjing Guo, Hui Ren, Lulu Ning, Huanxiang Liu, Xiaojun Yao
Journal of Structural Biology (June 2012) Volume 178(Issue 3) pp:225-232
Publication Date(Web):1 June 2012
DOI:10.1016/j.jsb.2012.03.009
The central event in the pathogenesis of prion protein (PrP) is a profound conformational change from its α-helical (PrPC) to its β-sheet-rich isoform (PrPSc). Many single amino acid mutations of PrP are associated with familial prion diseases, such as D202N, E211Q, and Q217R mutations located at the third native α-helix of human PrP. In order to explore the underlying structural and dynamic effects of these mutations, we performed all-atom molecular dynamics (MD) simulations for the wild-type (WT) PrP and its mutants. The obtained results indicate that these amino acid substitutions have subtle effects on the protein structures, but show large changes of the overall electrostatic potential distributions. We can infer that the changes of PrP electrostatic surface due to the studied mutations may influence the intermolecular interactions during the aggregation process. In addition, the mutations also affect the thermodynamic stabilities of PrP.
Co-reporter:Weiwei Xue, Dabo Pan, Ying Yang, Huanxiang Liu, Xiaojun Yao
Antiviral Research (January 2012) Volume 93(Issue 1) pp:126-137
Publication Date(Web):January 2012
DOI:10.1016/j.antiviral.2011.11.007
Co-reporter:Weiwei Xue, Pingzu Jiao, Huanxiang Liu, Xiaojun Yao
Antiviral Research (April 2014) Volume 104() pp:40-51
Publication Date(Web):April 2014
DOI:10.1016/j.antiviral.2014.01.006
Co-reporter:Wei Geng, Xuefei Zhao, Wenyan Zan, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2014 - vol. 16(Issue 8) pp:NaN3548-3548
Publication Date(Web):2013/11/11
DOI:10.1039/C3CP52841C
In this work, the effects of the electric field on the properties of ZnO–graphene composites were theoretically studied using density functional theory calculations. Three types of ZnO–graphene composites including composites of pristine graphene, graphene with defects as well as graphene oxide and a ZnO bilayer were studied. We calculated and analyzed the binding energies, charge transfer, band structures and work functions of the above composites under the external electric fields. The DFT calculation results demonstrate that the binding energies are sensitive to the electric field, and increasing the external electric field gives rise to stronger binding energies. The extent of charge transfer is correlated with the magnitude of the external electric field, but the band gaps are hardly affected by the external electric field. The work functions vary depending on the different structures of the composites and surface sides, and they are also tunable by the external electric field.
Co-reporter:Qifeng Bai, Horacio Pérez-Sánchez, Yang Zhang, Yonghua Shao, Danfeng Shi, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2014 - vol. 16(Issue 30) pp:NaN15885-15885
Publication Date(Web):2014/05/12
DOI:10.1039/C4CP01185F
The reported crystal structures of β2 adrenergic receptor (β2AR) reveal that the open and closed states of the water channel are correlated with the inactive and active conformations of β2AR. However, more details about the process by which the water channel states are affected by the active to inactive conformational change of β2AR remain illusive. In this work, molecular dynamics simulations are performed to study the dynamical inactive and active conformational change of β2AR induced by inverse agonist ICI 118,551. Markov state model analysis and free energy calculation are employed to explore the open and close states of the water channel. The simulation results show that inverse agonist ICI 118,551 can induce water channel opening during the conformational transition of β2AR. Markov state model (MSM) analysis proves that the energy contour can be divided into seven states. States S1, S2 and S5, which represent the active conformation of β2AR, show that the water channel is in the closed state, while states S4 and S6, which correspond to the intermediate state conformation of β2AR, indicate the water channel opens gradually. State S7, which represents the inactive structure of β2AR, corresponds to the full open state of the water channel. The opening mechanism of the water channel is involved in the ligand-induced conformational change of β2AR. These results can provide useful information for understanding the opening mechanism of the water channel and will be useful for the rational design of potent inverse agonists of β2AR.
Co-reporter:Wenyan Zan, Wei Geng, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2016 - vol. 18(Issue 4) pp:NaN3164-3164
Publication Date(Web):2015/12/17
DOI:10.1039/C5CP06029J
Vertical heterostructures of MoS2/h-BN/graphene have been successfully fabricated in recent experiments. Using first-principles analysis, we show that the structural and electronic properties of such vertical heterostructures are sensitive to applied vertical electric fields and strain. The applied electric field not only enhances the interlayer coupling but also linearly controls the charge transfer between graphene and MoS2 layers, leading to a tunable doping in graphene and controllable Schottky barrier height. Applied biaxial strain could weaken the interlayer coupling and results in a slight shift of graphene's Dirac point with respect to the Fermi level. It is of practical importance that the tunable electronic properties by strain and electric fields are immune to the presence of sulfur vacancies, the most common defect in MoS2.
Co-reporter:Qifeng Bai, Yang Zhang, Xiaomeng Li, Wenbo Chen, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2014 - vol. 16(Issue 44) pp:
Publication Date(Web):
DOI:10.1039/C4CP03331K
Co-reporter:Wei Geng, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2013 - vol. 15(Issue 16) pp:NaN6033-6033
Publication Date(Web):2013/02/25
DOI:10.1039/C3CP43720E
In this work, we systematically studied the mechanism for the enhanced photocatalytic activities of TiO2–graphene composites by using density functional theory (DFT) calculations. The studied composites include: TiO2–pristine graphene, TiO2–graphene with defect, as well as TiO2–graphene oxide. The results from geometry optimization can reveal information about the interface structure and anchoring orientation of the composites. The calculated electronic properties including total and difference charge density, as well as charge population, demonstrate the polarization and electron redistribution for the composites. Projected density of states and energy bands can provide some useful information about the photocatalytic mechanism involving the electrons excitation from the O-2p orbital on the valence band to the C-2p on the conduction band maximum for the composites. The results of our study can provide some useful information for understanding the detailed molecular mechanism of the better performance of composites compared to the individual components.
Co-reporter:Yuzhen Niu, Shuyan Li, Dabo Pan, Huanxiang Liu and Xiaojun Yao
Physical Chemistry Chemical Physics 2016 - vol. 18(Issue 7) pp:NaN5629-5629
Publication Date(Web):2016/01/21
DOI:10.1039/C5CP06257H
B-RAF kinase is a clinically validated target implicated in melanoma and advanced renal cell carcinoma (RCC). PLX4720 and TAK-632 are promising inhibitors against B-RAF with different dissociation rate constants (koff), but the specific mechanism that determines the difference of their dissociation rates remains unclear. In order to understand the kinetically different behaviors of these two inhibitors, their unbinding pathways were explored by random acceleration and steered molecular dynamics simulations. The random acceleration molecular dynamics (RAMD) simulations show that PLX4720 dissociates along the ATP-channel, while TAK-632 dissociates along either the ATP-channel or the allosteric-channel. The steered molecular dynamics (SMD) simulations reveal that TAK-632 is more favorable to escape from the binding pocket through the ATP-channel rather than the allosteric-channel. The PMF calculations suggest that TAK-632 presents longer residence time, which is in qualitative agreement with the experimental koff(koff = 3.3 × 10−2 s−1 and ΔGoff = −82.17 ± 0.29 kcal mol−1 for PLX4720; koff = 1.9 × 10−5 s−1 and ΔGoff = −39.73 ± 0.79 kcal mol−1 for PLX4720). Furthermore, the binding free decomposition by MM/GBSA illustrates that the residues K36, E54, V57, L58, L120, I125, H127, G146 and D147 located around the allosteric binding pocket play important roles in determining the longer residence time of TAK-632 by forming stronger hydrogen bond and hydrophobic interactions. Our simulations provide valuable information to design selective B-RAF inhibitors with long residence time in the future.
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![PROPAN-2-YL (2S)-2-[[[(2R,3R,4R,5R)-5-(2,4-DIOXOPYRIMIDIN-1-YL)-4-FLUORO-3-HYDROXY-4-METHYLOXOLAN-2-YL]METHOXY-PHENOXYPHOSPHORYL]AMINO]PROPANOATE](http://img.cochemist.com/ccimg/1190400/1190307-88-0.png)
![PROPAN-2-YL (2S)-2-[[[(2R,3R,4R,5R)-5-(2,4-DIOXOPYRIMIDIN-1-YL)-4-FLUORO-3-HYDROXY-4-METHYLOXOLAN-2-YL]METHOXY-PHENOXYPHOSPHORYL]AMINO]PROPANOATE](http://img.cochemist.com/ccimg/1190400/1190307-88-0_b.png)
![4H-Furo[2',3':3,4]pyrrolo[1,2-a]indole-4,10(2H)-dione, 3,3a,10a,10b-tetrahydro-3,3a-dihydroxy-2-(hydroxymethyl)-10a-1H-indol-3-yl-, (2R,3R,3aR,10aS,10bS)-](/data/chemimg/103100/953786-75-9.png)
![4H-Furo[2',3':3,4]pyrrolo[1,2-a]indole-4,10(2H)-dione, 3,3a,10a,10b-tetrahydro-3,3a-dihydroxy-2-(hydroxymethyl)-10a-1H-indol-3-yl-, (2R,3R,3aR,10aS,10bS)-](/data/chemimg/103100/953786-75-9_b.png)
![Phenol, 2-[[(4S)-4,5-dihydro-4-phenyl-2-oxazolyl]methyl]-](/data/chemimg/3721600/1803433-76-2.png)
![Phenol, 2-[[(4S)-4,5-dihydro-4-phenyl-2-oxazolyl]methyl]-](/data/chemimg/3721600/1803433-76-2_b.png)
![(3R)-1-[2-oxo-2-[4-(4-pyrimidin-2-ylphenyl)piperazin-1-yl]ethyl]-N-(3-pyridin-4-yl-1H-indazol-5-yl)pyrrolidine-3-carboxamide](http://img.cochemist.com/ccimg/942200/942183-80-4.png)
![(3R)-1-[2-oxo-2-[4-(4-pyrimidin-2-ylphenyl)piperazin-1-yl]ethyl]-N-(3-pyridin-4-yl-1H-indazol-5-yl)pyrrolidine-3-carboxamide](http://img.cochemist.com/ccimg/942200/942183-80-4_b.png)
![N-[3-[(5-Chloro-1H-pyrrolo[2,3-b]pyridin-3-yl)carbonyl]-2,4-difluorophenyl]-1-propanesulfonamide](http://img.cochemist.com/ccimg/918600/918505-84-7.png)
![N-[3-[(5-Chloro-1H-pyrrolo[2,3-b]pyridin-3-yl)carbonyl]-2,4-difluorophenyl]-1-propanesulfonamide](http://img.cochemist.com/ccimg/918600/918505-84-7_b.png)
![1H-Pyrrole-2-carboxamide, 4-[2-[(2-chloro-4-fluorophenyl)amino]-5-methyl-4-pyrimidinyl]](http://img.cochemist.com/ccimg/896800/896720-20-0.png)
![1H-Pyrrole-2-carboxamide, 4-[2-[(2-chloro-4-fluorophenyl)amino]-5-methyl-4-pyrimidinyl]](http://img.cochemist.com/ccimg/896800/896720-20-0_b.png)
![5-(2-phenylpyrazolo[1,5-a]pyridin-3-yl)-1h-pyrazolo[3,4-c]pyridazin-3-amine](http://img.cochemist.com/ccimg/865400/865362-74-9.png)
![5-(2-phenylpyrazolo[1,5-a]pyridin-3-yl)-1h-pyrazolo[3,4-c]pyridazin-3-amine](http://img.cochemist.com/ccimg/865400/865362-74-9_b.png)
![Phenol, 2-[(4S)-4,5-dihydro-4-(1-methylethyl)-2-oxazolyl]-4,6-bis(1,1-dimethylethyl)-](/data/chemimg/3721600/372137-88-7.png)
![Phenol, 2-[(4S)-4,5-dihydro-4-(1-methylethyl)-2-oxazolyl]-4,6-bis(1,1-dimethylethyl)-](/data/chemimg/3721600/372137-88-7_b.png)
![1H,3H-NAPHTHO[1,8-CD]PYRAN-1,3-DIONE, 6-(DIMETHYLAMINO)-](http://img.cochemist.com/ccimg/78000/77976-79-5.png)
![1H,3H-NAPHTHO[1,8-CD]PYRAN-1,3-DIONE, 6-(DIMETHYLAMINO)-](http://img.cochemist.com/ccimg/78000/77976-79-5_b.png)
![D-Iditol,2,5-anhydro-1,6-dideoxy-2-C-[(1E,3E,5E,7E)-8-(4-methoxy-5-methyl-2-oxo-2H-pyran-6-yl)-2-methyl-1,3,5,7-octatetraen-1-yl]-4-C-methyl-](http://img.cochemist.com/ccimg/25500/25425-12-1.png)
![D-Iditol,2,5-anhydro-1,6-dideoxy-2-C-[(1E,3E,5E,7E)-8-(4-methoxy-5-methyl-2-oxo-2H-pyran-6-yl)-2-methyl-1,3,5,7-octatetraen-1-yl]-4-C-methyl-](http://img.cochemist.com/ccimg/25500/25425-12-1_b.png)
![(4aR,5S,8R,8aS,9aS)-4a,5,6,7,8,8a,9,9a-octahydro-8,8a-dihydroxy-9a-methoxy-3,4a,5-trimethylnaphtho[2,3-b]furan-2(4H)-one](http://img.cochemist.com/ccimg/1370600/1370517-50-2.png)
![(4aR,5S,8R,8aS,9aS)-4a,5,6,7,8,8a,9,9a-octahydro-8,8a-dihydroxy-9a-methoxy-3,4a,5-trimethylnaphtho[2,3-b]furan-2(4H)-one](http://img.cochemist.com/ccimg/1370600/1370517-50-2_b.png)
![(3S,8R,10R,14R,17S)-17-((S)-2-hydroxy-6-methyl-5-methyleneheptan-2-yl)-4,4,8,10,14-pentamethyl-hexadecahydro-1H-cyclopenta[a]phenanthren-3-ol](http://img.cochemist.com/ccimg/1105700/1105670-73-2.png)
![(3S,8R,10R,14R,17S)-17-((S)-2-hydroxy-6-methyl-5-methyleneheptan-2-yl)-4,4,8,10,14-pentamethyl-hexadecahydro-1H-cyclopenta[a]phenanthren-3-ol](http://img.cochemist.com/ccimg/1105700/1105670-73-2_b.png)
![[3-methyl-3-(4,8,12-trimethyltridecyl)oxiran-2-yl]methanol](http://img.cochemist.com/ccimg/107500/107438-44-8.png)
![[3-methyl-3-(4,8,12-trimethyltridecyl)oxiran-2-yl]methanol](http://img.cochemist.com/ccimg/107500/107438-44-8_b.png)
![Pyrido[3',4':4,5]cyclohept[1,2-b]indole-12a(1H)-carboxylicacid, 4-ethyl-2,3,4,4a,5,6,7,12-octahydro-2-methyl-6-oxo-, methyl ester,(4S,4aS,12aR)-](http://img.cochemist.com/ccimg/33300/33257-13-5.png)
![Pyrido[3',4':4,5]cyclohept[1,2-b]indole-12a(1H)-carboxylicacid, 4-ethyl-2,3,4,4a,5,6,7,12-octahydro-2-methyl-6-oxo-, methyl ester,(4S,4aS,12aR)-](http://img.cochemist.com/ccimg/33300/33257-13-5_b.png)
![(1S,6bR,9aS,11bR)-1-(methoxymethyl)-9a,11b-dimethyl-1,6b,7,8,9a,10,11,11b-octahydro-3H-furo[4,3,2-de]indeno[4,5-h]isochromene-3,6,9-trione](http://img.cochemist.com/ccimg/31700/31652-69-4.png)
![(1S,6bR,9aS,11bR)-1-(methoxymethyl)-9a,11b-dimethyl-1,6b,7,8,9a,10,11,11b-octahydro-3H-furo[4,3,2-de]indeno[4,5-h]isochromene-3,6,9-trione](http://img.cochemist.com/ccimg/31700/31652-69-4_b.png)
![(2Z,4E)-5-[(1R,5R,8S)-8-hydroxy-1,5-dimethyl-3-oxo-6-oxabicyclo[3.2.1]oct-8-yl]-3-methylpenta-2,4-dienoic acid](http://img.cochemist.com/ccimg/24400/24394-14-7.png)
![(2Z,4E)-5-[(1R,5R,8S)-8-hydroxy-1,5-dimethyl-3-oxo-6-oxabicyclo[3.2.1]oct-8-yl]-3-methylpenta-2,4-dienoic acid](http://img.cochemist.com/ccimg/24400/24394-14-7_b.png)
![1H-Indol-5-ol,3-[2-(dimethylamino)ethyl]-](http://img.cochemist.com/ccimg/500/487-93-4.png)
![1H-Indol-5-ol,3-[2-(dimethylamino)ethyl]-](http://img.cochemist.com/ccimg/500/487-93-4_b.png)
![Phenol,4,4'-[(1S,3aR,4S,6aR)-tetrahydro-1H,3H-furo[3,4-c]furan-1,4-diyl]bis[2-methoxy-](http://img.cochemist.com/ccimg/500/487-36-5.png)
![Phenol,4,4'-[(1S,3aR,4S,6aR)-tetrahydro-1H,3H-furo[3,4-c]furan-1,4-diyl]bis[2-methoxy-](http://img.cochemist.com/ccimg/500/487-36-5_b.png)
