Modifying the energy term and considering the entropic contribution by IE method significantly improve the accuracy of predicted binding free energy in MM/PBSA method.

In this study, we examined the folding processes of eight helical proteins (2I9M, TC5B, 1WN8, 1V4Z, 1HO2, 1HLL, 2KFE, and 1YYB) at room temperature using the explicit solvent model under the AMBER14SB force field with the accelerated molecular dynamics (AMD) and traditional molecular dynamics (MD), respectively. We analyzed and compared the simulation results obtained by these two methods based on several aspects, such as root mean square deviation (RMSD), native contacts, cluster analysis, folding snapshots, free energy landscape, and the evolution of the radius of gyration, which showed that these eight proteins were successfully and consistently folded into the corresponding native structures by AMD simulations carried out at room temperature. In addition, the folding occurred in the range of 40~180 ns after starting from the linear structures of the eight proteins at 300 K. By contrast, these stable folding structures were not found when the traditional molecular dynamics (MD) simulation was used. At the same time, the influence of high temperatures (350, 400, and 450 K) is also further investigated. Study found that the simulation efficiency of AMD is higher than that of MD simulations, regardless of the temperature. Of these temperatures, 300 K is the most suitable temperature for protein folding for all systems. To further investigate the efficiency of AMD, another trajectory was simulated for eight proteins with the same linear structure but different random seeds at 300 K. Both AMD trajectories reached the correct folded structures. Our result clearly shows that AMD simulation are a highly efficient and reliable method for the study of protein folding.

At present, the calculated binding free energy obtained using the molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area (MM/PB(GB)SA) method is overestimated due to the lack of knowledge of suitable interior dielectric constants in the simulation on the interaction of Human Immunodeficiency Virus (HIV-1) protease systems with inhibitors. Therefore, the impact of different values of the interior dielectric constant and the entropic contribution when using the MM/PB(GB)SA method to calculate the binding free energy was systemically evaluated. Our results show that the use of higher interior dielectric constants (1.4–2.0) can clearly improve the predictive accuracy of the MM/PBSA and MM/GBSA methods, and computational errors are significantly reduced by including the effects of electronic polarization and using a new highly efficient interaction entropy (IE) method to calculate the entropic contribution. The suitable range for the interior dielectric constant is 1.4–1.6 for the MM/PBSA method; within this range, the correlation coefficient fluctuates around 0.84, and the mean absolute error fluctuates around 2 kcal/mol. Similarly, an interior dielectric constant of 1.8–2.0 produces a correlation coefficient of approximately 0.76 when using the MM/GBSA method. In addition, the entropic contribution of each individual residue was further calculated using the IE method to predict hot-spot residues, and the detailed binding mechanisms underlying the interactions of the HIV-1 protease, its inhibitors, and bridging water molecules were investigated. In this study, the use of a higher interior dielectric constant and the IE method can improve the calculation accuracy of the HIV-1 system.

A new highly efficient interaction entropy (IE) method combined with the polarized protein-specific charge (PPC) force field is employed to investigate the interaction mechanism of CDK2-ligand binding and the effect of the bridging water. Our result shows that the computed binding free energies for five CDK2-ligand complexes using the IE method have a significantly linear correlation with the experimentally measured values with a correlation coefficient of 0.98 in consideration of the bridging water under the PPC force field. And the correlation coefficient is found to be slightly weaker with a value of 0.95 using the traditional normal mode (Nmode) method for calculation of entropy change. Importantly, the rank of the predicted binding free energies is significantly consistent with the experimental rank based on the IE method calculated entropy change using the PPC force field. However, without including the bridging water under PPC simulation, the correlation coefficient is below 0.83. For comparison, the result obtained from the simulation using the nonpolarized AMBER force field gives a much weaker correlation with the correlation coefficients of 0.44 and 0.45 using the Nmode method and IE method, due to the lack of electrostatic polarization. Furthermore, hydrogen bond analysis indicates that the bridging water makes a significant contribution to mediating the hydrogen bond network of protein-ligand binding and stabilizing the complex structure. The current study demonstrates that the new IE method is superior to the standard Nmode method in computing the binding free energy. And our results also emphasize the importance of electronic polarization and bridging water in MD simulations and free energy calculations.

Main chain torsions of alanine dipeptide are parameterized into coupled 2-dimensional Fourier expansions based on quantum mechanical (QM) calculations at M06 2X/aug-cc-pvtz//HF/6-31G** level. Solvation effect is considered by employing polarizable continuum model. Utilization of the M06 2X functional leads to precise potential energy surface that is comparable to or even better than MP2 level, but with much less computational demand. Parameterization of the 2D expansions is against the full main chain torsion space instead of just a few low energy conformations. This procedure is similar to that for the development of AMBER03 force field, except unique weighting factor was assigned to all the grid points. To avoid inconsistency between quantum mechanical calculations and molecular modeling, the model peptide is further optimized at molecular mechanics level with main chain dihedral angles fixed before the calculation of the conformational energy on molecular mechanical level at each grid point, during which generalized Born model is employed. Difference in solvation models at quantum mechanics and molecular mechanics levels makes this parameterization procedure less straightforward. All force field parameters other than main chain torsions are taken from existing AMBER force field. With this new main chain torsion terms, we have studied the main chain dihedral distributions of ALA dipeptide and pentapeptide in aqueous solution. The results demonstrate that 2D main chain torsion is effective in delineating the energy variation associated with rotations along main chain dihedrals. This work is an implication for the necessity of more accurate description of main chain torsions in the future development of ab initio force field and it also raises a challenge to the development of quantum mechanical methods, especially the quantum mechanical solvation models.

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Fluorescence spectroscopy and molecular simulation were explored to study the interaction between caffeic acid and human serum albumin (HSA). The experimental results indicated that the fluorescence quenching mechanism between caffeic acid and HSA is a static quenching, which was proved again by the analysis of fluorescence lifetime by time-correlated single photon counting. The binding process is spontaneous and the hydrophobic force is the main force between caffeic acid and HSA. In addition, the binding of caffeic acid to HSA was modeled by molecular dynamics simulations. The root mean square deviations, root mean square fluctuations, radius of gyration and the number of hydrogen bonds of the molecular dynamic (MD) simulation process were analyzed. Both experimental and modeling results demonstrated strong binding between HSA and caffeic acid. HSA had a slight conformational change when it binds with caffeic acid. The obtained information is useful for HSA drug design. Copyright © 2016 John Wiley & Sons, Ltd.