A study of ab initio folding of chignolins using replica-exchange molecular dynamics simulations

More and more studies have confirmed the importance of polarization effects in hydrogen bonding interactions in protein folding simulations. In this paper, a recently developed charge update scheme termed polarized structure-specific backbone charge (PSBC) model was applied to the folding of 10-residue chignolin. A comparison between simulations performed using PSBC and a nonpolarizable (AMBER99SB) force field demonstrably showed the importance of the electrostatic polarization effect in the folding of the short β-hairpin peptide by a series of analyses such as DSSP, free-energy landscape, hydrogen bond occupancy, and melting curve. The PSBC model was further validated by folding two other chignolin variants.

A fixed multi-site interaction charge model for an accurate prediction of the QM/MM interactions

A fixed multi-site interaction charge (FMIC) model was proposed for the accurate prediction of intermolecular electrostatic interactions based on the quantum mechanical linear response of a molecule to an external electric field. In such a model, some additional off-center interaction sites were added for capturing multipole interactions for a given molecule. By multivariate least-square fitting analysis of the calculated QM/MM interactions of a given molecule with the electrostatic environment and the electrostatic potentials of the environment at the pre-defined distributed interaction sites, the FMIC of the molecule was obtained. The model system of CO in myoglobin (Mb) was utilized to demonstrate the derivation of the FMIC. The accuracy of FMIC in predicting the electrostatic interactions between CO and the Mb environment was investigated using 10 000 different Mb-CO configurations generated from the 400 ps QM/MM MD simulation. In comparison to the QM/MM calculations at the B3LYP/aug-cc-pVTZ/ff99SB level, the mean unsigned error (MUE) of the results based on the FMIC model was merely 0.10 kcal mol^-1, and the root mean square error (RMSE) was only 0.13 kcal mol^-1, which are significantly lower than the results predicted by the ESP charge model (MUE = 1.45 kcal mol^-1, and RMSE = 1.7 kcal mol^-1, respectively). The transferability of FMIC was tested by applying the obtained FMIC in the wild type Mb-CO system to the mutants of V68F and H64L Mb-CO systems. The MUEs of the obtained results for 10 000 different configurations are both smaller than 0.2 kcal mol^-1 for the V68F and H64L Mb-CO systems in comparison to the B3LYP/aug-cc-pVTZ/ff99SB calculations, and the RMSEs are also lower than 0.2 kcal mol^-1 for both mutants. The applications of FMIC were extended to model the electrostatic interactions between a hydrogen fluoride molecule and 492 waters in a truncated octahedron box; our study showed that the FMIC could give satisfactory results with a MUE of 0.12 kcal mol^-1 and a RMSE of 0.16 kcal mol^-1 in comparison to the B3LYP/aug-cc-pVDZ/TIP3P calculations for 10 000 different configurations generated using the 10 ns classical MD simulation. Therefore, the FMIC method provides an accurate and efficient tool for predicting intermolecular electrostatic interactions, which can be utilized in the future development of molecular force fields.

An electrostatic energy-based charge model for molecular dynamics simulation

The interactions of the polar chemical bonds such as C=O and N-H with an external electric field were investigated, and a linear relationship between the QM/MM interaction energies and the electric field along the chemical bond is established in the range of weak to intermediate electrical fields. The linear relationship indicates that the electrostatic interactions of a polar group with its surroundings can be described by a simple model of a dipole with constant moment under the action of an electric field. This relationship is employed to develop a general approach to generating an electrostatic energy-based charge (EEC) model for molecules containing single or multiple polar chemical bonds. Benchmark test studies of this model were carried out for (CH₃)₂-CO and N-methyl acetamide in explicit water, and the result shows that the EEC model gives more accurate electrostatic energies than those given by the widely used charge model based on fitting to the electrostatic potential (ESP) in direct comparison to the energies computed by the QM/MM method. The MD simulations of the electric field at the active site of ketosteroid isomerase based on EEC demonstrated that EEC gave a better representation of the electrostatic interaction in the hydrogen-bonding environment than the Amber14SB force field by comparison with experiment. The current study suggests that EEC should be better suited for molecular dynamics study of molecular systems with polar chemical bonds such as biomolecules than the widely used ESP or RESP (restrained ESP) charge models.

Developing an effective polarizable bond method for small molecules with application to optimized molecular docking

Electrostatic interaction plays an essential role in protein-ligand binding. Due to the polarization effect, electrostatic interactions are largely impacted by their local environments. However, traditional force fields use fixed point charge-charge interactions to describe electrostatic interactions but is unable to include the polarization effect. The lack of the polarization effect in the force field representation can result in substantial error in biomolecular studies, such as molecular dynamics and molecular docking. Docking programs usually employ traditional force fields to estimate the binding energy between a ligand and a protein for pose selection or scoring. The intermolecular interaction energy mainly consists of van der Waals and electrostatic interaction in the force field representation. In the current study, we developed an Effective Polarizable Bond (EPB) method for small organic molecules and applied this EPB method to optimize protein-ligand docking in computational tests for a variety of protein-ligand systems. We tested the method on a set of 38 cocrystallized structures taken from the Protein Data Bank (PDB) and found that the maximum error was reduced from 7.98 Å to 2.03 Å when using EPB Dock, providing strong evidence that the use of EPB charges is important. We found that our optimized docking approach with EPB charges could improve the docking performance, sometimes dramatically, and the maximum error was reduced from 12.88 Å to 1.57 Å in Optimized Docking (in the case of 1fqx). The average RMSD decreased from 2.83 Å to 1.85 Å. Further investigations showed that the use of the EBP method could enhance intermolecular hydrogen bonding, which is a major contributing factor to improved docking performance. Developed tools for the calculation of the polarized ligand charge from a protein-ligand complex structure with the EPB method are freely available on GitHub (https://github.com/Xundrug/EPB).

A force consistent method for electrostatic energy calculation in fluctuating charge model

A practical approach to include the polarization effect in a molecular force field is the fluctuating charge method in which atomic charges vary as the configuration of the molecular system changes. However, the use of the Coulomb formula to evaluate energy in a fluctuating charge method is theoretically inconsistent with the forces given by the fluctuating method. In this work, we propose a force-consistent method to correctly calculate electrostatic energies of molecular systems using a fluctuating charge model (Effective Polarizable Bond or EPB). In this protocol, the electrostatic energy is obtained by numerical interaction of the atomic forces along the MD trajectory, rather than using the default Coulomb formula in the EPB model. Test study on the benchmark Barnase-Barstar protein-protein interaction system demonstrates that although the total electrostatic energy of the system shows little deviation due to the averaging effect, specific residue-residue electrostatic interaction energy is affected and the level of the effect depends on the charges of the interacting residues with charged residues showing pronounced differences in calculated energies between using the current protocol and the standard Coulomb formula. It is recommended that the proposed numerical interaction method should be preferred in the calculation of electrostatic energy in fluctuating charge models used in molecular dynamics simulations.

Molecular Dynamics Exploration of Selectivity of Dual Inhibitors 5M7, 65X, and 65Z toward Fatty Acid Binding Proteins 4 and 5

Designing highly selective inhibitors of fatty acid binding proteins 4 and 5 (FABP4 and FABP5) is of importance for treatment of some diseases related with inflammation, metabolism, and tumor growth. In this study, molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were performed to probe binding selectivity of three inhibitors (5M7, 65X, and 65Z) to FABP4/FABP5 with K_i values of 0.022/0.50 μM, 0.011/0.086 μM, and 0.016/0.12 μM, respectively. The results not only suggest that all inhibitors associate more tightly with FABP4 than FABP5, but also prove that the main forces driving the selective bindings of inhibitors to FABP4 and FABP5 stem from the difference in the van der Waals interactions and polar interactions of inhibitors with two proteins. Meanwhile, a residue-based free energy decomposition method was applied to reveal molecular basis that inhibitors selectively interact with individual residues of two different proteins. The calculated results show that the binding difference of inhibitors to the residues (Phe16, Phe19), (Ala33, Gly36), (Phe57, Leu60), (Ala75, Ala78), (Arg126, Arg129), and (Tyr128, Tyr131) in (FABP4, FABP5) drive the selectivity of inhibitors toward FABP4 and FABP5. This study will provide great help for further design of effective drugs to protect against a series of metabolic diseases, arteriosclerosis, and inflammation.

Disordered peptide chains in an α-C-based coarse-grained model

We construct a one-bead-per-residue coarse-grained dynamical model to describe intrinsically disordered proteins at significantly longer timescales than in the all-atom models. In this model, inter-residue contacts form and disappear during the course of the time evolution. The contacts may arise between the sidechains, the backbones or the sidechains and backbones of the interacting residues. The model yields results that are consistent with many all-atom and experimental data on these systems. We demonstrate that the geometrical properties of various homopeptides differ substantially in this model. In particular, the average radius of gyration scales with the sequence length in a residue-dependent manner.

Computational Study of PCSK9-EGFA Complex with Effective Polarizable Bond Force Field

Inhibiting of Proprotein Convertase Subtilisin/Kexin-type 9 (PCSK9) and Low Density Lipoprotein Receptor (LDLR) binding is an effective way for reducing Low Density Lipoprotein cholesterol (LDL-C). Understanding the interaction between PCSK9 and LDLR is useful for PCSK9 inhibitor design. In this work, MD simulations with the standard (non-polarizable) AMBER force field and effective polarizable bond (EPB) force field were performed for wild type and four mutants of PCSK9 and EGFA (Epidermal Growth Factor-like repeat A) domain of LDLR complexes. These four mutants are gain-of-function mutants. The analysis of hydrogen bond dynamics and the relative binding free energy indicates that EPB is more reliable in simulating protein dynamics and predicting relative binding affinity. Structures sampled from MD simulations with the standard AMBER force field deviate too far away from crystal structures. Many important interaction components between of PCSK9 and EGFA no longer exist in the simulation with the Amber force field. For comparison, simulation using EPB force field gives more stable structures as shown by hydrogen bond analysis and produced relative binding free energies that are consistent with experimental results. Our study suggests that inclusion of polarization effects in MD simulation is important for studying the protein-protein interaction.