In this manuscript we expand significantly on our earlier communication by investigating the bilayer self-assembly of eight different types of phospholipids in unbiased molecular dynamics (MD) simulations using three widely used all-atom lipid force fields. Irrespective of the underlying force field, the lipids are shown to spontaneously form stable lamellar bilayer structures within 1 microsecond, the majority of which display properties in satisfactory agreement with the experimental data. The lipids self-assemble via the same general mechanism, though at formation rates that differ both between lipid types, force fields and even repeats on the same lipid/force field combination. In addition to zwitterionic phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipids, anionic phosphatidylserine (PS) and phosphatidylglycerol (PG) lipids are represented. To our knowledge this is the first time bilayer self-assembly of phospholipids with negatively charged head groups is demonstrated in all-atom MD simulations.

The only available crystal structure of the human cardiac troponin molecule (cTn) in the Ca2+ activated state does not include crucial segments, including the N-terminus of the cTn inhibitory subunit (cTnI). We have applied all-atom molecular dynamics (MD) simulations to study the structure and dynamics of cTn, both in the unphosphorylated and bis-phosphorylated states at Ser23/Ser24 of cTnI. We performed multiple microsecond MD simulations of wild type (WT) cTn (6, 5 μs) and bisphosphorylated (SP23/SP24) cTn (9 μs) on a 419 amino acid cTn model containing human sequence cTnC (1–161), cTnI (1–171) and cTnT (212–298), including residues not present in the crystal structure. We have compared our results to previous computational studies, and proven that longer simulations and a water box of at least 25 Å are needed to sample the interesting conformational shifts both in the native and bis-phosphorylated states. As a consequence of the introduction into the model of the C-terminus of cTnT that was missing in previous studies, cTnC–cTnI interactions that are responsible for the cTn dynamics are altered. We have also shown that phosphorylation does not increase cTn fluctuations, and its effects on the protein–protein interaction profiles cannot be assessed in a significant way. Finally, we propose that phosphorylation could provoke a loss of Ca2+ by stabilizing out-of-coordination distances of the cTnC's EF hand II residues, and in particular Ser 69.

This communication reports the first example of spontaneous lipid bilayer formation in unbiased all-atom molecular dynamics (MD) simulations. Using two different lipid force fields we show simulations started from random mixtures of lipids and water in which four different types of phospholipids self-assemble into organized bilayers in under 1 microsecond.

The Amber Lipid14 force field is expanded to include cholesterol parameters for all-atom cholesterol and lipid bilayer molecular dynamics simulations. The General Amber and Lipid14 force fields are used as a basis for assigning atom types and basic parameters. A new RESP charge derivation for cholesterol is presented, and tail parameters are adapted from Lipid14 alkane tails. 1,2-Dimyristoyl-sn-glycero-3-phosphocholine (DMPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers are simulated at a range of cholesterol contents. Experimental bilayer structural properties are compared with bilayer simulations and are found to be in good agreement. With this parameterization, another component of complex membranes is available for molecular dynamics with the Amber Lipid14 force field.

The AMBER lipid force field has been updated to create Lipid14, allowing tensionless simulation of a number of lipid types with the AMBER MD package. The modular nature of this force field allows numerous combinations of head and tail groups to create different lipid types, enabling the easy insertion of new lipid species. The Lennard-Jones and torsion parameters of both the head and tail groups have been revised and updated partial charges calculated. The force field has been validated by simulating bilayers of six different lipid types for a total of 0.5 μs each without applying a surface tension; with favorable comparison to experiment for properties such as area per lipid, volume per lipid, bilayer thickness, NMR order parameters, scattering data, and lipid lateral diffusion. As the derivation of this force field is consistent with the AMBER development philosophy, Lipid14 is compatible with the AMBER protein, nucleic acid, carbohydrate, and small molecule force fields.

We have successfully developed and validated with experiment a new computational method for quantitatively predicting the effects of mutations at a protein–protein interface. From over 500 ns of explicitly solvated molecular dynamics, Mutational Locally Enhanced Sampling (MULES) shows significantly improved accuracy over post-processing methods for a prototypical set of mutations, with a maximum mean unsigned error to experiment of 0.5 kcal mol−1 and comparable or better precision. The technique in principle allows the effect of any mutation to be calculated, whether natural or non-natural. The versatility, quantitative accuracy, high precision and speed of MULES compared to existing computational prediction techniques enhance its potential for modelling changes to the interface in a systematic way, thereby aiding peptide and protein interaction design.

Protein kinase B (PKB) is a serine/threonine kinase that plays a key role in the phosphoinositide 3-kinase (PI3K) pathway—one of the most frequently activated proliferation pathways in cancer. In this pathway, PKB is recruited to the plasma membrane by direct interaction of its pleckstrin homology (PH) domain with the inositol phosphate head-group of phosphatidylinositol 3,4,5-trisphosphate [PtdIns(3,4,5)P3] or phosphatidylinositol 3,4-bisphosphate [PtdIns(3,4)P2]. This recruitment is a critical stage in the activation of PKB, whose downstream effectors play important roles in cell survival, proliferation and growth. It is therefore of great interest to understand PKB's mode of binding, as well as its specificity and affinity for different phosphoinositides. We have used a total of 3 μs of molecular dynamics (MD) simulations to better understand the interactions of the PKB PH domain with the inositol phosphate head-groups of phosphoinositides involved in the PI3K pathway. Our computational models successfully mirror PKB's in vivo selectivity for 3-phosphorylated phosphoinositides. Furthermore, the models also help to rationalize unexpected in vitro data in which inositol 1,4,5-trisphosphate [Ins(1,4,5)P3] binds with a relatively high affinity to the PKB PH domain, despite its parent lipid phosphatidylinositol 4,5-bisphosphate [PtdIns(4,5)P2] being known not to bind in vivo. With the support of computational simulations, we propose that when not bonded to a phosphatidate tail Ins(1,4,5)P3 binds in an orientation in which its inositol ring is flipped with respect to the 3-phosphorylated inositol phosphate ligands and its parent lipid.

Previous attempts to simulate phospholipid bilayers using the General Amber Force Field (GAFF) yielded many bilayer characteristics in agreement with experiment, however when using a tensionless NPT ensemble the bilayer is seen to compress to an undesirable extent resulting in low areas per lipid and high order parameters in comparison to experiment. In this work, the GAFF Lennard-Jones parameters for the simulation of acyl chains are corrected to allow the accurate and stable simulation of pure lipid bilayers. Lipid bilayers comprised of six phospholipid types were simulated for timescales approaching a quarter of a microsecond under tensionless constant pressure conditions using Graphics Processing Units. Structural properties including area per lipid, volume per lipid, bilayer thickness, order parameter and headgroup hydration show favourable agreement with available experimental values. Expanding the system size from 72 to 288 lipids and a more experimentally realistic 2 × 288 lipid bilayer stack induces little change in the observed properties. This preliminary work is intended for combination with the new AMBER Lipid11 modular force field as part of on-going attempts to create a modular phospholipid AMBER force field allowing tensionless NPT simulations of complex lipid bilayers.

The non-specific binding of candidate positron emission tomography (PET) radiotracers causes resulting PET images to have poor contrast and is a key determinant for the success or failure of imaging drugs. Non-specific binding is thought to arise when radiotracers bind to cell membranes and moieties other than their intended target. Our previous preliminary work has proposed the use of the drug-lipid interaction energy descriptor to predict the level of non-specific binding in vivo using a limited set of ten well known PET radiotracers with kinetic modelling data taken from the literature. This work validates and extends the use of the drug-lipid interaction energy descriptor using a new set of twenty-two candidate PET radiotracers with non-specific binding data recently collected at the same imaging centre with consistent methodology. As with the previous set of radiotracers, a significant correlation is found between the quantum chemical drug-lipid interaction energy and in vivo non-specific binding experimental values. In an effort to speed up the calculation process, several semi-empirical quantum chemical methods were assessed for their ability to reproduce the ab initio results. However no single semi-empirical method was found to consistently reproduce the level of correlation achieved with ab initio quantum chemical methods.

This paper describes the parameterization of inositol 1,3,4,5-tetrakisphosphate [Ins(1,3,4,5)P4] for use in molecular dynamics (MD) simulations. For this theoretical investigation, eleven isomers of Ins(1,3,4,5)P4, with different levels and arrangements of protonation, have been considered. Herein we report accurate quantum mechanics (QM) calculations offering a detailed description of the energetic and structural properties of the Ins(1,3,4,5)P4 isomers and subsequent development of parameters for these isomers for application in the AMBER force field. QM calculations were employed to geometry optimize the Ins(1,3,4,5)P4 isomers, using the DFT-B3LYP level of theory in gas phase. In subsequent steps, charge parameters were generated for each isomer. These charge parameters, plus assigned atom-types from the AMBER ff99SB force field, were then applied to the optimized isomers for energy minimization in AMBER. The quality of the parameters was evaluated by comparing the structural, energetic and spectroscopic properties of the Ins(1,3,4,5)P4 isomers between the QM geometry optimization stage, from which the parameters were generated, and the energy minimization stage, in which the parameters were applied. The results were shown to be in strong qualitative agreement between these stages, suggesting good quality parameters have been obtained. Additionally, adaptations to the gas phase protocol, investigating the use of the MP2 method for the geometry optimization stage and GAFF atom-types for the energy minimization stage, were tested. These results confirmed the initial protocol applied was the most appropriate. Calculations for the Ins(1,3,4,5)P4 isomers were also carried out in the presence of implicit solvent, allowing comparison and validation of the theoretical calculations with experimental data. The computed energetic properties of the Ins(1,3,4,5)P4 isomers were assessed against their experimental probabilities based on 31P-NMR titration data. The computational and experimental results were shown to be in strong agreement, with the lower energy isomers corresponding to those more probable. This paper reports a clearly-defined algorithmic approach to generate parameters for the highly charged Ins(1,3,4,5)P4 ligand, permitting their use in future MD studies.

This paper describes the parameterization of inositol 1,3,4,5-tetrakisphosphate [Ins(1,3,4,5)P4] for use in molecular dynamics (MD) simulations. For this theoretical investigation, eleven isomers of Ins(1,3,4,5)P4, with different levels and arrangements of protonation, have been considered. Herein we report accurate quantum mechanics (QM) calculations offering a detailed description of the energetic and structural properties of the Ins(1,3,4,5)P4 isomers and subsequent development of parameters for these isomers for application in the AMBER force field. QM calculations were employed to geometry optimize the Ins(1,3,4,5)P4 isomers, using the DFT-B3LYP level of theory in gas phase. In subsequent steps, charge parameters were generated for each isomer. These charge parameters, plus assigned atom-types from the AMBER ff99SB force field, were then applied to the optimized isomers for energy minimization in AMBER. The quality of the parameters was evaluated by comparing the structural, energetic and spectroscopic properties of the Ins(1,3,4,5)P4 isomers between the QM geometry optimization stage, from which the parameters were generated, and the energy minimization stage, in which the parameters were applied. The results were shown to be in strong qualitative agreement between these stages, suggesting good quality parameters have been obtained. Additionally, adaptations to the gas phase protocol, investigating the use of the MP2 method for the geometry optimization stage and GAFF atom-types for the energy minimization stage, were tested. These results confirmed the initial protocol applied was the most appropriate. Calculations for the Ins(1,3,4,5)P4 isomers were also carried out in the presence of implicit solvent, allowing comparison and validation of the theoretical calculations with experimental data. The computed energetic properties of the Ins(1,3,4,5)P4 isomers were assessed against their experimental probabilities based on 31P-NMR titration data. The computational and experimental results were shown to be in strong agreement, with the lower energy isomers corresponding to those more probable. This paper reports a clearly-defined algorithmic approach to generate parameters for the highly charged Ins(1,3,4,5)P4 ligand, permitting their use in future MD studies.

The non-specific binding of candidate positron emission tomography (PET) radiotracers causes resulting PET images to have poor contrast and is a key determinant for the success or failure of imaging drugs. Non-specific binding is thought to arise when radiotracers bind to cell membranes and moieties other than their intended target. Our previous preliminary work has proposed the use of the drug-lipid interaction energy descriptor to predict the level of non-specific binding in vivo using a limited set of ten well known PET radiotracers with kinetic modelling data taken from the literature. This work validates and extends the use of the drug-lipid interaction energy descriptor using a new set of twenty-two candidate PET radiotracers with non-specific binding data recently collected at the same imaging centre with consistent methodology. As with the previous set of radiotracers, a significant correlation is found between the quantum chemical drug-lipid interaction energy and in vivo non-specific binding experimental values. In an effort to speed up the calculation process, several semi-empirical quantum chemical methods were assessed for their ability to reproduce the ab initio results. However no single semi-empirical method was found to consistently reproduce the level of correlation achieved with ab initio quantum chemical methods.

The only available crystal structure of the human cardiac troponin molecule (cTn) in the Ca2+ activated state does not include crucial segments, including the N-terminus of the cTn inhibitory subunit (cTnI). We have applied all-atom molecular dynamics (MD) simulations to study the structure and dynamics of cTn, both in the unphosphorylated and bis-phosphorylated states at Ser23/Ser24 of cTnI. We performed multiple microsecond MD simulations of wild type (WT) cTn (6, 5 μs) and bisphosphorylated (SP23/SP24) cTn (9 μs) on a 419 amino acid cTn model containing human sequence cTnC (1–161), cTnI (1–171) and cTnT (212–298), including residues not present in the crystal structure. We have compared our results to previous computational studies, and proven that longer simulations and a water box of at least 25 Å are needed to sample the interesting conformational shifts both in the native and bis-phosphorylated states. As a consequence of the introduction into the model of the C-terminus of cTnT that was missing in previous studies, cTnC–cTnI interactions that are responsible for the cTn dynamics are altered. We have also shown that phosphorylation does not increase cTn fluctuations, and its effects on the protein–protein interaction profiles cannot be assessed in a significant way. Finally, we propose that phosphorylation could provoke a loss of Ca2+ by stabilizing out-of-coordination distances of the cTnC's EF hand II residues, and in particular Ser 69.

This communication reports the first example of spontaneous lipid bilayer formation in unbiased all-atom molecular dynamics (MD) simulations. Using two different lipid force fields we show simulations started from random mixtures of lipids and water in which four different types of phospholipids self-assemble into organized bilayers in under 1 microsecond.

Protein kinase B (PKB) is a serine/threonine kinase that plays a key role in the phosphoinositide 3-kinase (PI3K) pathway—one of the most frequently activated proliferation pathways in cancer. In this pathway, PKB is recruited to the plasma membrane by direct interaction of its pleckstrin homology (PH) domain with the inositol phosphate head-group of phosphatidylinositol 3,4,5-trisphosphate [PtdIns(3,4,5)P3] or phosphatidylinositol 3,4-bisphosphate [PtdIns(3,4)P2]. This recruitment is a critical stage in the activation of PKB, whose downstream effectors play important roles in cell survival, proliferation and growth. It is therefore of great interest to understand PKB's mode of binding, as well as its specificity and affinity for different phosphoinositides. We have used a total of 3 μs of molecular dynamics (MD) simulations to better understand the interactions of the PKB PH domain with the inositol phosphate head-groups of phosphoinositides involved in the PI3K pathway. Our computational models successfully mirror PKB's in vivo selectivity for 3-phosphorylated phosphoinositides. Furthermore, the models also help to rationalize unexpected in vitro data in which inositol 1,4,5-trisphosphate [Ins(1,4,5)P3] binds with a relatively high affinity to the PKB PH domain, despite its parent lipid phosphatidylinositol 4,5-bisphosphate [PtdIns(4,5)P2] being known not to bind in vivo. With the support of computational simulations, we propose that when not bonded to a phosphatidate tail Ins(1,4,5)P3 binds in an orientation in which its inositol ring is flipped with respect to the 3-phosphorylated inositol phosphate ligands and its parent lipid.

In this manuscript we expand significantly on our earlier communication by investigating the bilayer self-assembly of eight different types of phospholipids in unbiased molecular dynamics (MD) simulations using three widely used all-atom lipid force fields. Irrespective of the underlying force field, the lipids are shown to spontaneously form stable lamellar bilayer structures within 1 microsecond, the majority of which display properties in satisfactory agreement with the experimental data. The lipids self-assemble via the same general mechanism, though at formation rates that differ both between lipid types, force fields and even repeats on the same lipid/force field combination. In addition to zwitterionic phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipids, anionic phosphatidylserine (PS) and phosphatidylglycerol (PG) lipids are represented. To our knowledge this is the first time bilayer self-assembly of phospholipids with negatively charged head groups is demonstrated in all-atom MD simulations.

We have successfully developed and validated with experiment a new computational method for quantitatively predicting the effects of mutations at a protein–protein interface. From over 500 ns of explicitly solvated molecular dynamics, Mutational Locally Enhanced Sampling (MULES) shows significantly improved accuracy over post-processing methods for a prototypical set of mutations, with a maximum mean unsigned error to experiment of 0.5 kcal mol−1 and comparable or better precision. The technique in principle allows the effect of any mutation to be calculated, whether natural or non-natural. The versatility, quantitative accuracy, high precision and speed of MULES compared to existing computational prediction techniques enhance its potential for modelling changes to the interface in a systematic way, thereby aiding peptide and protein interaction design.