Yadong Chen

Name:

Organization: China Pharmaceutical University

Department: Laboratory of Molecular Design and Drug Discovery

Title:

Chemicals
References

QSAR modeling and in silico design of small-molecule inhibitors targeting the interaction between E3 ligase VHL and HIF-1 \(\alpha \)

Co-reporter:Jing Pan;Yanmin Zhang;Ting Ran;Anyang Xu;Xin Qiao;Lingfeng Yin

Molecular Diversity 2017 Volume 21( Issue 3) pp:719-739

Publication Date(Web):08 July 2017

DOI:10.1007/s11030-017-9750-y

Protein–protein interactions (PPIs) have attracted much attention recently because of their preponderant role in most biological processes. The prevention of the interaction between E3 ligase VHL and HIF-1\(\alpha \) may improve tolerance to hypoxia and ameliorate the prognosis of many diseases. To obtain novel potent inhibitors of VHL/HIF-1\(\alpha \) interaction, a series of hydroxyproline-based inhibitors were investigated for structural optimization using a combination of QSAR modeling and molecular docking. Here, 2D- and 3D-QSAR models were developed by genetic function approximation (GFA) and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods, respectively. The top-ranked models with strict validation revealed satisfactory statistical parameters (CoMFA with \(q^{2}\), 0.637; \(r^{2}\), 0.955; \(r_{\mathrm{pred}}^2\), 0.944; CoMSIA with \(q^{2}\), 0.649; \(r^{2}\), 0.954; \(r_{\mathrm{pred}}^2\), 0.911; GFA with \(q^{2}\), 0.721; \(r^{2}\), 0.801; \(r_{\mathrm{pred}}^2\), 0.861). The selected five 2D-QSAR descriptors were in good accordance with the 3D-QSAR results, and contour maps gave the visualization of feature requirements for inhibitory activity. A new diverse molecular database was created by molecular fragment replacement and BREED techniques for subsequent virtual screening. Eventually, 31 novel hydroxyproline derivatives stood out as potential VHL/HIF-1\(\alpha \) inhibitors with favorable predictions by the CoMFA, CoMSIA and GFA models. The reliability of this protocol suggests that it could also be applied to the exploration of lead optimization of other PPI targets.

Structure-based design, synthesis, and evaluation of 4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c]pyridine derivatives as novel c-Met inhibitors

Co-reporter:Li Zhang, Beichen Zhang, Jingyun Zhao, Yanle Zhi, Lu Wang, Tao Lu, Yadong Chen

European Journal of Medicinal Chemistry 2017 Volume 138(Volume 138) pp:

Publication Date(Web):29 September 2017

DOI:10.1016/j.ejmech.2017.06.057

•A series of 4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c]pyridine derivatives were designed, synthesized.•The target compounds showed potent antitumor activity.•Compound 8c showed an Ic50 value of 68 nM against c-Met and was capable of inhibiting the phosphorylation of c-Met kinase in MKN45 cell line in a dose-dependent manner.•Compound 8c demonstrated more than 50-fold selectivity against other tyrosine kinases tested.c-Met was emerging as an attractive target for cancer-targeted therapy because deregulation of c-Met has been observed in multiple tumor types. A series of 4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c]pyridine derivatives were designed, synthesized and evaluated for their enzymatic inhibitory activity against c-Met kinase and cellular potency against MKN45, EBC-1 and PC-3 cell lines. Nine of them showed better activity than lead compound 1 which was found via computer-aided drug design. Among them, compound 8c showed inhibitory activity of 68 nM against c-Met and low micromole cellular potency against MKN45 and EBC-1 cell lines. Moreover, 8c demonstrated more than 50-fold selectivity against other tyrosine kinases tested. The result of western blot indicated that compound 8c was capable of inhibiting the phosphorylation of c-Met kinase in MKN45 cell line in a dose-dependent manner.Download high-res image (259KB)Download full-size image

Identification of Covalent Binding Sites Targeting Cysteines Based on Computational Approaches

Co-reporter:Yanmin Zhang, Danfeng Zhang, Haozhong Tian, Yu Jiao, Zhihao Shi, Ting Ran, Haichun Liu, Shuai Lu, Anyang Xu, Xin Qiao, Jing Pan, Lingfeng Yin, Weineng Zhou, Tao Lu, and Yadong Chen

Molecular Pharmaceutics 2016 Volume 13(Issue 9) pp:3106-3118

Publication Date(Web):August 2, 2016

DOI:10.1021/acs.molpharmaceut.6b00302

Covalent drugs have attracted increasing attention in recent years due to good inhibitory activity and selectivity. Targeting noncatalytic cysteines with irreversible inhibitors is a powerful approach for enhancing pharmacological potency and selectivity because cysteines can form covalent bonds with inhibitors through their nucleophilic thiol groups. However, most human kinases have multiple noncatalytic cysteines within the active site; to accurately predict which cysteine is most likely to form covalent bonds is of great importance but remains a challenge when designing irreversible inhibitors. In this work, FTMap was first applied to check its ability in predicting covalent binding site defined as the region where covalent bonds are formed between cysteines and irreversible inhibitors. Results show that it has excellent performance in detecting the hot spots within the binding pocket, and its hydrogen bond interaction frequency analysis could give us some interesting instructions for identification of covalent binding cysteines. Furthermore, we proposed a simple but useful covalent fragment probing approach and showed that it successfully predicted the covalent binding site of seven targets. By adopting a distance-based method, we observed that the closer the nucleophiles of covalent warheads are to the thiol group of a cysteine, the higher the possibility that a cysteine is prone to form a covalent bond. We believe that the combination of FTMap and our distance-based covalent fragment probing method can become a useful tool in detecting the covalent binding site of these targets.Keywords: covalent binding sites; cysteines; fragment probing; irreversible inhibitors;

Targeting epigenetic reader and eraser: Rational design, synthesis and in vitro evaluation of dimethylisoxazoles derivatives as BRD4/HDAC dual inhibitors

Co-reporter:Zhimin Zhang, Shaohua Hou, Hongli Chen, Ting Ran, Fei Jiang, Yuanyuan Bian, Dewei Zhang, Yanle Zhi, Lu Wang, Li Zhang, Hongmei Li, Yanmin Zhang, Weifang Tang, Tao Lu, Yadong Chen

Bioorganic & Medicinal Chemistry Letters 2016 Volume 26(Issue 12) pp:2931-2935

Publication Date(Web):15 June 2016

DOI:10.1016/j.bmcl.2016.04.034

The bromodomain protein module and histone deacetylase (HDAC), which recognize and remove acetylated lysine, respectively, have emerged as important epigenetic therapeutic targets in cancer treatments. Herein we presented a novel design approach for cancer drug development by combination of bromodomain and HDAC inhibitory activity in one molecule. The designed compounds were synthesized which showed inhibitory activity against bromodomain 4 and HDAC1. The representative dual bromodomain/HDAC inhibitors, compound 11 and 12, showed potent antiproliferative activities against human leukaemia cell line K562 and MV4-11 in cellular assays. This work may lay the foundation for developing dual bromodomain/HDAC inhibitors as potential anticancer therapeutics.

Insight into the key interactions of bromodomain inhibitors based on molecular docking, interaction fingerprinting, molecular dynamics and binding free energy calculation

Co-reporter:Ting Ran, Zhimin Zhang, Kejun Liu, Yi Lu, Huifang Li, Jinxing Xu, Xiao Xiong, Yanmin Zhang, Anyang Xu, Shuai Lu, Haichun Liu, Tao Lu and Yadong Chen

Molecular BioSystems 2015 vol. 11(Issue 5) pp:1295-1304

Publication Date(Web):03 Mar 2015

DOI:10.1039/C4MB00723A

The bromodomain is a key protein–protein interaction module that specifically reads the acetylation marks of histones in epigenetic regulation. Currently, lots of inhibitors targeting the bromodomain have been reported as therapeutic agents. To better understand the interaction mechanism of bromodomain inhibitors, 20 diverse bromodomain inhibitors were studied using a combination of computational methods, including molecular docking, interaction fingerprinting, molecular dynamics simulation and binding free energy calculation. As a result, interactions important for the activity were critically analyzed, and the energy contribution in terms of individual residues was explored. These integrated results provided insights into two hot spots in the active site of the bromodomain, where the hydrophobic hot spot formed by Trp81, Val87, Leu92 and Ile146 played a central role in the interaction, and the hydrogen-bond hot spot mediated by Asn140 exhibited a moderate contribution to the binding affinity of the bromodomain inhibitors. This interaction mechanism study may facilitate the rational design of novel small-molecule bromodomain inhibitors.

A selectivity study of sodium-dependent glucose cotransporter 2/sodium-dependent glucose cotransporter 1 inhibitors by molecular modeling

Co-reporter:Jinxing Xu;Haoliang Yuan;Ting Ran;Yanmin Zhang;Haichun Liu;Shuai Lu;Xiao Xiong;Anyang Xu;Yulei Jiang;Tao Lu

Journal of Molecular Recognition 2015 Volume 28( Issue 8) pp:467-479

Publication Date(Web):

DOI:10.1002/jmr.2464

Sodium-dependent glucose cotransporters (SGLTs) play an important role in glucose reabsorption in the kidney and have been identified as promising targets to treat diabetes. Because of the side effects like glucose and galactose malabsorption by targeting SGLT1, highly selective SGLT2 inhibitors are more promising in the treatment of diabetes. To understand the mechanism of selectivity, we conducted selectivity-based three-dimensional quantitative structure–activity relationship studies to highlight the structure requirements for highly selective SGLT2 inhibitors. The best comparative molecular field analysis and comparative molecular similarity indices analysis models showed the noncross-validated coefficient (r²) of 0.967 and 0.943, respectively. The predicted correlation coefficients (r²_pred) of 0.974 and 0.938 validated the reliability and predictability of these models. Besides, homology models of SGLT2 and SGLT1 were also constructed to investigate the selective mechanism from structure-based perspective. Molecular dynamics simulation and binding free energy calculation were performed on the systems of a potent and selective compound interacting with SGLT2 and SGLT1 to compare the different binding modes. The simulation results showed that the stretch of the methylthio group on Met241 had an essential effect on the different binding modes between SGLT1 and SGLT2, which was consistent with the three-dimensional quantitative structure–activity relationship analysis. Hydrogen bond analysis and binding free energy calculation revealed that SGLT2 binding complex was more stable and favorable than SGLT1 complex, which was highly correlated with the experimental results. Our obtained results give useful information for the investigation of the inhibitors' selectivity between SGLT2 and SGLT1 and will help for further development of highly selective SGLT2 inhibitors. Copyright © 2015 John Wiley & Sons, Ltd.

Fragment virtual screening based on Bayesian categorization for discovering novel VEGFR-2 scaffolds

Co-reporter:Yanmin Zhang;Yu Jiao;Xiao Xiong;Haichun Liu;Ting Ran;Jinxing Xu

Molecular Diversity 2015 Volume 19( Issue 4) pp:895-913

Publication Date(Web):2015 November

DOI:10.1007/s11030-015-9592-4

The discovery of novel scaffolds against a specific target has long been one of the most significant but challengeable goals in discovering lead compounds. A scaffold that binds in important regions of the active pocket is more favorable as a starting point because scaffolds generally possess greater optimization possibilities. However, due to the lack of sufficient chemical space diversity of the databases and the ineffectiveness of the screening methods, it still remains a great challenge to discover novel active scaffolds. Since the strengths and weaknesses of both fragment-based drug design and traditional virtual screening (VS), we proposed a fragment VS concept based on Bayesian categorization for the discovery of novel scaffolds. This work investigated the proposal through an application on VEGFR-2 target. Firstly, scaffold and structural diversity of chemical space for 10 compound databases were explicitly evaluated. Simultaneously, a robust Bayesian classification model was constructed for screening not only compound databases but also their corresponding fragment databases. Although analysis of the scaffold diversity demonstrated a very unevenly distribution of scaffolds over molecules, results showed that our Bayesian model behaved better in screening fragments than molecules. Through a literature retrospective research, several generated fragments with relatively high Bayesian scores indeed exhibit VEGFR-2 biological activity, which strongly proved the effectiveness of fragment VS based on Bayesian categorization models. This investigation of Bayesian-based fragment VS can further emphasize the necessity for enrichment of compound databases employed in lead discovery by amplifying the diversity of databases with novel structures.

Molecular Modeling of Exquisitely Selective c-Met Inhibitors through 3D-QSAR and Molecular Dynamics Simulations

Co-reporter:Haoliang Yuan, Jin Zhuang, Shihe Hu, Huifang Li, Jinxing Xu, Yaning Hu, Xiao Xiong, Yadong Chen, and Tao Lu

Journal of Chemical Information and Modeling 2014 Volume 54(Issue 9) pp:2544-2554

Publication Date(Web):September 2, 2014

DOI:10.1021/ci500268s

c-Met has been considered as an attractive target for developing antitumor agents. The highly selective c-Met inhibitors provide invaluable opportunities for the combination with other therapies safely to achieve the optimal efficacy. In this work, a series of triazolopyrazine c-Met inhibitors with exquisitely selectivity were investigated using a combination of molecular docking, three-dimensional quantitative structure–activity relationship (3D-QSAR), and molecular dynamics simulation. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models were developed to reveal the structural determinants for c-Met inhibition. Both models were validated to have high reliability and predictability, and contour map analysis suggested feature requirements for different substituents on the scaffold. It is worth noting that an important hydrogen bond rich region was identified in the unique narrow channel, which is distinct from other kinases. Molecular dynamics simulations and binding free energy calculations provided further support that suitable groups in this hydrogen bond rich region made great contributions to the binding of ligands. Moreover, hydrogen bonds with residues of the narrow channel were also indicated to be essential to improve the activity and selectivity. This study will facilitate the discovery and optimization of novel c-Met inhibitors with higher activity and selectivity.

An efficient multistep ligand-based virtual screening approach for GPR40 agonists

Co-reporter:Sihui Yao;Tao Lu;Zifan Zhou;Haichun Liu;Haoliang Yuan;Ting Ran

Molecular Diversity 2014 Volume 18( Issue 1) pp:183-193

Publication Date(Web):2014 February

DOI:10.1007/s11030-013-9493-3

G protein-coupled receptor 40/free fatty acid receptor 1 (GPR40/FFAR1) is a member of the GPCR superfamily, and GPR40 agonists have therapeutic potential for type 2 diabetes. With the crystal structure of GPR40 currently unavailable, various ligand-based virtual screening approaches can be applied to identify novel agonists of GPR40. It is known that each ligand-based method has its own advantages and limitations. To improve the efficiency of individual ligand-based methods, an efficient multistep ligand-based virtual screening approach is presented in this study, including the pharmacophore-based screening, physicochemical property filtering, protein–ligand interaction fingerprint similarity analysis, and 2D-fingerprint structural similarity search. A focused decoy library was generated and used to evaluate the efficiency of this virtual screening protocol. This multistep workflow not only significantly improved the hit rate compared with each individual ligand-based method, but also identified diverse known actives from decoys. This protocol may serve as an efficient virtual screening tool for the targets without crystal structures available to discover novel active compounds.

3D-QSAR and molecular fragment replacement study on diaminopyrimidine and pyrrolotriazine ALK inhibitors

Co-reporter:Zhipeng Ke, Tao Lu, Haichun Liu, Haoliang Yuan, Ting Ran, Yanmin Zhang, Sihui Yao, Xiao Xiong, Jinxing Xu, Anyang Xu, Yadong Chen

Journal of Molecular Structure 2014 1067() pp: 127-137

Publication Date(Web):5 June 2014

DOI:10.1016/j.molstruc.2014.03.036

•We developed CoMFA, CoMSIA and Topomer CoMFA models for a series of ALK inhibitors.•Topomer Search was utilized for virtual screening to obtain suitable fragments.•Novel compounds were generated by molecular fragment replacement.•Novel compounds were evaluated by 3D-QSAR models prediction and docking analysis.•A set of novel derivatives with predicted activities were designed.Over expression of anaplastic lymphoma kinase (ALK) has been found in many types of cancer, and ALK is a promising therapeutic target for the treatment of cancer. To obtain new potent inhibitors of ALK, we conducted lead optimization using 3D-QSAR modeling and molecular docking investigation of 2,4-diaminopyrimidines and 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine-based compounds. Three favorable 3D-QSAR models (CoMFA with q2, 0.555; r2, 0.939; CoMSIA with q2, 0.625; r2, 0.974; Topomer CoMFA with q2, 0.557; r2 0.756) have been developed to predict the biological activity of novel compounds. Topomer Search was utilized for virtual screening to obtain suitable fragments. The novel compounds generated by molecular fragment replacement (MFR) were evaluated by Topomer CoMFA prediction, Glide (docking) and further evaluated with CoMFA and CoMSIA prediction. 25 novel 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine derivatives as potential ALK inhibitors were finally obtained. In this paper, a combination of CoMFA, CoMSIA and Topomer CoMFA could obtain favorable 3D-QSAR models and suitable fragments for ALK inhibitors optimization. The work flow which comprised 3D-QSAR modeling, Topomer Search, MFR, molecular docking and evaluating criteria could be applied to de novo drug design and the resulted compounds initiate us to further optimize and design new potential ALK inhibitors.Graphical abstract

An Integrated Virtual Screening Approach for VEGFR-2 Inhibitors

Co-reporter:Yanmin Zhang, Shangyan Yang, Yu Jiao, Haichun Liu, Haoliang Yuan, Shuai Lu, Ting Ran, Sihui Yao, Zhipeng Ke, Jinxing Xu, Xiao Xiong, Yadong Chen, and Tao Lu

Journal of Chemical Information and Modeling 2013 Volume 53(Issue 12) pp:3163-3177

Publication Date(Web):November 22, 2013

DOI:10.1021/ci400429g

In recent years, various virtual screening (VS) tools have been developed, and many successful screening campaigns have been showcased. However, whether by conventional molecular docking or pharmacophore screening, the selection of virtual hits is based on the ranking of compounds by scoring functions or fit values, which remains the bottleneck of VS due to insufficient accuracy. As the limitations of individual methods persist, a comprehensive comparison and integration of different methods may provide insights into selecting suitable methods for VS. Here, we evaluated the performance of molecular docking, fingerprint-based 2D similarity and multicomplex pharmacophore in an individual and a combined manner, through a retrospective VS study on VEGFR-2 inhibitors. An integrated two-layer workflow was developed and validated through VS of VEGFR-2 inhibitors against the DUD-E database, which demonstrated improved VS performance through a ligand-based method ECFP_4, followed by molecular docking, and then a strict multicomplex pharmacophore. Through a retrospective comparison with six published papers, this integrated approach outperformed 43 out of 45 methods, indicating a great effectiveness. This kind of integrated VS approach can be extended to other targets for the screening and discovery of inhibitors.

Fragment-based strategy for structural optimization in combination with 3D-QSAR

Co-reporter:Haoliang Yuan;Wenting Tai;Shihe Hu

Journal of Computer-Aided Molecular Design 2013 Volume 27( Issue 10) pp:897-915

Publication Date(Web):2013 October

DOI:10.1007/s10822-013-9687-x

Fragment-based drug design has emerged as an important methodology for lead discovery and drug design. Different with other studies focused on fragment library design and active fragment identification, a fragment-based strategy was developed in combination with three-dimensional quantitative structure–activity relationship (3D-QSAR) for structural optimization in this study. Based on a validated scaffold or fragment hit, a series of structural optimization was conducted to convert it to lead compounds, including 3D-QSAR modelling, active site analysis, fragment-based structural optimization and evaluation of new molecules. 3D-QSAR models and active site analysis provided sufficient information for confirming the SAR and pharmacophoric features for fragments. This strategy was evaluated through the structural optimization on a c-Met inhibitor scaffold 5H-benzo[4,5]cyclohepta[1,2-b]pyridin-5-one, which resulted in an c-Met inhibitor with high inhibitory activity. Our study suggested the effectiveness of this fragment-based strategy and the druggability of our newly explored active region. The reliability of this strategy indicated it could also be applied to facilitate lead optimization of other targets.

Identification of Novel Polo-like Kinase 1 Inhibitors by a Hybrid Virtual Screening

Co-reporter:Shuai Lu;Shan-Liang Sun;Hai-Chun Liu;Ya-Dong Chen;Hao-Liang Yuan;Yi-Ping Gao;Pei Yang;Tao Lu

Chemical Biology & Drug Design 2012 Volume 80( Issue 2) pp:328-339

Publication Date(Web):

DOI:10.1111/j.1747-0285.2012.01412.x

Polo-like kinase 1 is an important and attractive oncological target that plays a key role in mitosis and cytokinesis. A combined pharmacophore- and docking-based virtual screening was performed to identify novel polo-like kinase 1 inhibitors. A total of 34 hit compounds were selected and tested in vitro, and some compounds showed inhibition of polo-like kinase 1 and human tumor cell growth. The most potent compound (66) inhibited polo-like kinase 1 with an IC₅₀ value of 6.99 μm. The docked binding models of two hit compounds were discussed in detail. These compounds contained novel chemical scaffolds and may be used as foundations for the development of novel classes of polo-like kinase 1 inhibitors.

Design, synthesis and biological evaluation of β-carboline derivatives as novel inhibitors targeting B-Raf kinase

Co-reporter:Botao Xin, Weifang Tang, Yue Wang, Guowu Lin, Haichun Liu, Yu Jiao, Yong Zhu, Haoliang Yuan, Yadong Chen, Tao Lu

Bioorganic & Medicinal Chemistry Letters 2012 Volume 22(Issue 14) pp:4783-4786

Publication Date(Web):15 July 2012

DOI:10.1016/j.bmcl.2012.05.053

β-Carboline family of compounds is a large group of alkaloids widely distributed in nature and exhibits broad-spectrum anti-tumor activities. We designed and synthesized two series of novel 1-carboxamide- and 6-sulfonamide-substituted β-carboline derivatives 7a–p and 12a–b, and their wild type B-Raf kinase inhibitory activities were described. Most compounds showed moderate to excellent inhibitory activities. Among them, 1-carboxamide-6-(N-(3-(dimethylamino)propyl)-sulfamoyl)-β-carboline, 7e exhibited potent activity (IC50 = 1.62 μM), showing the potential for further investigation as a lead compound.Two series of novel 1-carboxamide and 6-sulfonamide substituted β-carboline derivatives 7a–o, 12a–b were designed and synthesized and their wild type B-Raf kinase inhibitory activities were described. Compound 1-carboxamide-6-(N-(3-(dimethylamino)propyl)sulfamoyl)-β-carboline, 7e exhibited potent activity (IC50 = 1.62 μM), showing the potential for further investigation as a lead compound.

De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction

Co-reporter:Yanmin Zhang;Haichun Liu;Yu Jiao;Haoliang Yuan;Fengxiao Wang

Molecular Diversity 2012 Volume 16( Issue 4) pp:787-802

Publication Date(Web):2012 November

DOI:10.1007/s11030-012-9405-y

Vascular endothelial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR) have been identified as promising targets for novel anticancer agents. To achieve new potent inhibitors of KDR, we conducted molecular fragment replacement (MFR) studies for the understanding of 3D-QSAR modeling and the docking investigation of arylphthalazines and 2-((1H-Azol-1-yl)methyl)-N-arylbenzamides-based KDR inhibitors. Two favorable 3D-QSAR models (CoMFA with q2, 0.671; r2, 0.969; CoMSIA with q2, 0.608; r2, 0.936) have been developed to predict the biological activity of new compounds. The new molecular database generated by MFR was virtually screened using Glide (docking) and further evaluated with CoMFA prediction, protein–ligand interaction fingerprint (PLIF) and ADMET analysis. 44 N-(pyridin-4-ylmethyl)aniline derivatives as novel potential KDR inhibitors were finally obtained. In this paper, the work flow developed could be applied to de novo drug design and virtual screening potential KDR inhibitors, and use hit compounds to further optimize and design new potential KDR inhibitors.

Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors

Co-reporter:Wenting Tai;Tao Lu;Haoliang Yuan;Fengxiao Wang

Journal of Molecular Modeling 2012 Volume 18( Issue 7) pp:3087-3100

Publication Date(Web):2012 July

DOI:10.1007/s00894-011-1328-5

Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC50 values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer’s randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.

A selectivity study on mTOR/PI3Kα inhibitors by homology modeling and 3D-QSAR

Co-reporter:Ting Ran;Tao Lu;Haoliang Yuan;Haichun Liu;Jian Wang

Journal of Molecular Modeling 2012 Volume 18( Issue 1) pp:171-186

Publication Date(Web):2012 January

DOI:10.1007/s00894-011-1034-3

The phosphatidylinositol-3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway plays a critical role in the regulation of cellular growth, survival and proliferation. mTOR and PI3K have attracted particular attention as cancer targets. These kinases belong to the phosphatidylinositol-3-kinase-related kinase (PIKK) family and therefore have considerable homology in their active sites. To accelerate the discovery of inhibitors with selective activity against mTOR and PI3K as cancer targets, in this work, a homology model of mTOR was developed to identify the structural divergence in the active sites between mTOR and PI3Kα. Furthermore, two highly predictive comparative molecular similarity index analyses (CoMSIA) models were built based on 304 selective inhibitors docked into mTOR and PI3Kα, respectively (mTOR: q2 = 0.658, rpre2 = 0.839; PI3Kα: q2 = 0.540, rpre2 = 0.719). The results showed that steric and electrostatic fields have an important influence on selectivity towards mTOR and PI3Kα—a finding consistent with the structural divergence between the active sites. The findings may be helpful in investigating selective mTOR/PI3Kα inhibitors.

Novel Strategy for Three-Dimensional Fragment-Based Lead Discovery

Co-reporter:Haoliang Yuan, Tao Lu, Ting Ran, Haichun Liu, Shuai Lu, Wenting Tai, Ying Leng, Weiwei Zhang, Jian Wang, and Yadong Chen

Journal of Chemical Information and Modeling 2011 Volume 51(Issue 4) pp:959-974

Publication Date(Web):March 25, 2011

DOI:10.1021/ci200003c

Fragment-based drug design (FBDD) is considered a promising approach in lead discovery. However, for a practical application of this approach, problems remain to be solved. Hence, a novel practical strategy for three-dimensional lead discovery is presented in this work. Diverse fragments with spatial positions and orientations retained in separately adjacent regions were generated by deconstructing well-aligned known inhibitors in the same target active site. These three-dimensional fragments retained their original binding modes in the process of new molecule construction by fragment linking and merging. Root-mean-square deviation (rmsd) values were used to evaluate the conformational changes of the component fragments in the final compounds and to identify the potential leads as the main criteria. Furthermore, the successful validation of our strategy is presented on the basis of two relevant tumor targets (CDK2 and c-Met), demonstrating the potential of our strategy to facilitate lead discovery against some drug targets.

Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors

Co-reporter:Xiu-Mei Chen;Tao Lu;Shuai Lu;Hui-Fang Li

Journal of Molecular Modeling 2010 Volume 16( Issue 7) pp:1195-1204

Publication Date(Web):2010 July

DOI:10.1007/s00894-009-0630-y

Checkpoint kinase 1 (Chk1), a member of the serine/threonine kinase family, is an attractive therapeutic target for anticancer combination therapy. A structure-based modeling approach complemented with shape components was pursued to develop a reliable pharmacophore model for ATP-competitive Chk1 inhibitors. Common chemical features of the pharmacophore model were derived by clustering multiple structure-based pharmacophore features from different Chk1-ligand complexes in comparable binding modes. The final model consisted of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD), two hydrophobic (HY) features, several excluded volumes and shape constraints. In the validation study, this feature-shape query yielded an enrichment factor of 9.196 and performed fairly well at distinguishing active from inactive compounds, suggesting that the pharmacophore model can serve as a reliable tool for virtual screening to facilitate the discovery of novel Chk1 inhibitors. Besides, these pharmacophore features were assumed to be essential for Chk1 inhibitors, which might be useful for the identification of potential Chk1 inhibitors.