Constant pH molecular dynamics in generalized Born implicit solvent

A new method is proposed for constant pH molecular dynamics (MD), employing generalized Born (GB) electrostatics. Protonation states are modeled with different charge sets, and titrating residues sample a Boltzmann distribution of protonation states as the simulation progresses, using Monte Carlo sampling based on GB-derived energies. The method is applied to four different crystal structures of hen egg-white lysozyme (HEWL). pK(a) predictions derived from the simulations have root-mean-square (RMS) error of 0.82 relative to experimental values. Similarity of results between the four crystal structures shows the method to be independent of starting crystal structure; this is in contrast to most electrostatics-only models. A strong correlation between conformation and protonation state is noted and quantitatively analyzed, emphasizing the importance of sampling protonation states in conjunction with dynamics.     

Prediction of pKa shifts in proteins using a combination of molecular mechanical and continuum solvent calculations

The prediction of pKa shifts of ionizable groups in proteins is of great relevance for a number of important biological phenomena. We present an implementation of the MM-GBSA approach, which combines molecular mechanical (MM) and generalized Born (GB) continuum solvent energy terms, to the calculation of pKa values of a panel of nine proteins, including 69 individual comparisons with experiment. While applied so far mainly to the calculation of biomolecular binding free energies, we show that this method can also be used for the estimation of protein pKa shifts, with an accuracy around 1 pKa unit, even for strongly shifted residues. Our analysis reveals that the nonelectrostatic terms that are part of the MM-GBSA free energy expression are important contributors to improved prediction accuracy. This suggests that most of the previous approaches that focus only on electrostatic interactions could be improved by adding other nonpolar energy terms to their free energy expression. Interestingly, our method yields best accuracy at protein dielectric constants of epsilonint = 2-4, which is in contrast to previous approaches that peak at higher epsilonint > or = 8. An important component of our procedure is an intermediate minimization step of each protonation state involving different rotamers and tautomers as a way to explicitly model protein relaxation upon (de)protonation.     

Effects of system net charge and electrostatic truncation on all‐atom constant pH molecular dynamics

Constant pH molecular dynamics offers a means to rigorously study the effects of solution pH on dynamical processes. Here, we address two critical questions arising from the most recent developments of the all‐atom continuous constant pH molecular dynamics (CpHMD) method: (1) What is the effect of spatial electrostatic truncation on the sampling of protonation states? (2) Is the enforcement of electrical neutrality necessary for constant pH simulations? We first examined how the generalized reaction field and force‐shifting schemes modify the electrostatic forces on the titration coordinates. Free energy simulations of model compounds were then carried out to delineate the errors in the deprotonation free energy and salt‐bridge stability due to electrostatic truncation and system net charge. Finally, CpHMD titration of a mini‐protein HP36 was used to understand the manifestation of the two types of errors in the calculated pK_a values. The major finding is that enforcing charge neutrality under all pH conditions and at all time via cotitrating ions significantly improves the accuracy of protonation‐state sampling. We suggest that such finding is also relevant for simulations with particle mesh Ewald, considering the known artifacts due to charge‐compensating background plasma. © 2014 Wiley Periodicals, Inc.     

Monte carlo simulations of proteins at constant pH with generalized born solvent,flexible sidechains,and an effective dielectric boundary

Titratable residues determine the acid/base behavior of proteins, strongly influencing their function; in addition, proton binding is a valuable reporter on electrostatic interactions. We describe a method for pK_a calculations, using constant‐pH Monte Carlo (MC) simulations to explore the space of sidechain conformations and protonation states, with an efficient and accurate generalized Born model (GB) for the solvent effects. To overcome the many‐body dependency of the GB model, we use a “Native Environment” approximation, whose accuracy is shown to be good. It allows the precalculation and storage of interactions between all sidechain pairs, a strategy borrowed from computational protein design, which makes the MC simulations themselves very fast. The method is tested for 12 proteins and 167 titratable sidechains. It gives an rms error of 1.1 pH units, similar to the trivial “Null” model. The only adjustable parameter is the protein dielectric constant. The best accuracy is achieved for values between 4 and 8, a range that is physically plausible for a protein interior. For sidechains with large pK_a shifts, ≥2, the rms error is 1.6, compared to 2.5 with the Null model and 1.5 with the empirical PROPKA method. © 2013 Wiley Periodicals, Inc.     

Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking

In molecular docking, it is challenging to develop a scoring function that is accurate to conduct high-throughput screenings. Most scoring functions implemented in popular docking software packages were developed with many approximations for computational efficiency, which sacrifices the accuracy of prediction. With advanced technology and powerful computational hardware nowadays, it is feasible to use rigorous scoring functions, such as molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) in molecular docking studies. Here, we systematically investigated the performance of MM/PBSA and MM/GBSA to identify the correct binding conformations and predict the binding free energies for 98 protein-ligand complexes. Comparison studies showed that MM/GBSA (69.4%) outperformed MM/PBSA (45.5%) and many popular scoring functions to identify the correct binding conformations. Moreover, we found that molecular dynamics simulations are necessary for some systems to identify the correct binding conformations. Based on our results, we proposed the guideline for MM/GBSA to predict the binding conformations. We then tested the performance of MM/GBSA and MM/PBSA to reproduce the binding free energies of the 98 protein-ligand complexes. The best prediction of MM/GBSA model with internal dielectric constant 2.0, produced a Spearman's correlation coefficient of 0.66, which is better than MM/PBSA (0.49) and almost all scoring functions used in molecular docking. In summary, MM/GBSA performs well for both binding pose predictions and binding free-energy estimations and is efficient to re-score the top-hit poses produced by other less-accurate scoring functions.     

Beta‐hairpin restraint potentials for calculations of potentials of mean force as a function of beta‐hairpin tilt,rotation, and distance

We have developed a set of restraint potentials for β‐hairpin tilt relative to the membrane normal, β‐hairpin rotation around the β‐hairpin axis, and hairpin–hairpin distance. Such restraint potentials enable us to characterize the molecular basis of specific β‐hairpin tilt and rotation in membranes and hairpin–hairpin interactions at the atomic level by sampling their conformational space along these degrees of freedom, i.e., reaction coordinates, during molecular dynamics simulations. We illustrate the efficacy of the β‐hairpin restraint potentials by calculating the potentials of mean force (PMFs) as a function of tilt and rotation angles of protegrin‐1 (PG‐1), a β‐hairpin antimicrobial peptide, in an implicit membrane model. The peptide association in the membrane is also examined by calculating the PMFs as a function of distance between two PG‐1 peptides in various dimer interfaces. These novel restraint potentials are found to perform well in each of these cases and are expected to be a useful means to study the microscopic driving forces of insertion, tilting, and rotation of β‐hairpin peptides in membranes as well as their association in aqueous solvent or membrane environments particularly when combined with explicit solvent models. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009     

Combining the polarizable Drude force field with a continuum electrostatic Poisson–Boltzmann implicit solvation model

In this work, we have combined the polarizable force field based on the classical Drude oscillator with a continuum Poisson–Boltzmann/solvent‐accessible surface area (PB/SASA) model. In practice, the positions of the Drude particles experiencing the solvent reaction field arising from the fixed charges and induced polarization of the solute must be optimized in a self‐consistent manner. Here, we parameterized the model to reproduce experimental solvation free energies of a set of small molecules. The model reproduces well‐experimental solvation free energies of 70 molecules, yielding a root mean square difference of 0.8 kcal/mol versus 2.5 kcal/mol for the CHARMM36 additive force field. The polarization work associated with the solute transfer from the gas‐phase to the polar solvent, a term neglected in the framework of additive force fields, was found to make a large contribution to the total solvation free energy, comparable to the polar solute–solvent solvation contribution. The Drude PB/SASA also reproduces well the electronic polarization from the explicit solvent simulations of a small protein, BPTI. Model validation was based on comparisons with the experimental relative binding free energies of 371 single alanine mutations. With the Drude PB/SASA model the root mean square deviation between the predicted and experimental relative binding free energies is 3.35 kcal/mol, lower than 5.11 kcal/mol computed with the CHARMM36 additive force field. Overall, the results indicate that the main limitation of the Drude PB/SASA model is the inability of the SASA term to accurately capture non‐polar solvation effects. © 2018 Wiley Periodicals, Inc.     

Solvent models for protein–ligand binding: Comparison of implicit solvent poisson and surface generalized born models with explicit solvent simulations

Solvent effects play a crucial role in mediating the interactions between proteins and their ligands. Implicit solvent models offer some advantages for modeling these interactions, but they have not been parameterized on such complex problems, and therefore, it is not clear how reliable they are. We have studied the binding of an octapeptide ligand to the murine MHC class I protein using both explicit solvent and implicit solvent models. The solvation free energy calculations are more than 10³ faster using the Surface Generalized Born implicit solvent model compared to FEP simulations with explicit solvent. For some of the electrostatic calculations needed to estimate the binding free energy, there is near quantitative agreement between the explicit and implicit solvent model results; overall, the qualitative trends in the binding predicted by the explicit solvent FEP simulations are reproduced by the implicit solvent model. With an appropriate choice of reference system based on the binding of the discharged ligand, electrostatic interactions are found to enhance the binding affinity because the favorable Coulomb interaction energy between the ligand and protein more than compensates for the unfavorable free energy cost of partially desolvating the ligand upon binding. Some of the effects of protein flexibility and thermal motions on charging the peptide in the solvated complex are also considered. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 591–607, 2001     

Ranking protein–protein docking results using steered molecular dynamics and potential of mean force calculations

Crystallization of protein–protein complexes can often be problematic and therefore computational structural models are often relied on. Such models are often generated using protein–protein docking algorithms, where one of the main challenges is selecting which of several thousand potential predictions represents the most near‐native complex. We have developed a novel technique that involves the use of steered molecular dynamics (sMD) and umbrella sampling to identify near‐native complexes among protein–protein docking predictions. Using this technique, we have found a strong correlation between our predictions and the interface RMSD (iRMSD) in ten diverse test systems. On two of the systems, we investigated if the prediction results could be further improved using potential of mean force calculations. We demonstrated that a near‐native (<2.0 Å iRMSD) structure could be identified in the top‐1 ranked position for both systems. © 2016 Wiley Periodicals, Inc.     

Toward quantitative estimates of binding affinities for protein–ligand systems involving large inhibitor compounds: A steered molecular dynamics simulation route

Understanding binding mechanisms between enzymes and potential inhibitors and quantifying protein – ligand affinities in terms of binding free energy is of primary importance in drug design studies. In this respect, several approaches based on molecular dynamics simulations, often combined with docking techniques, have been exploited to investigate the physicochemical properties of complexes of pharmaceutical interest. Even if the geometric properties of a modeled protein – ligand complex can be well predicted by computational methods, it is still challenging to rank with chemical accuracy a series of ligand analogues in a consistent way. In this article, we face this issue calculating relative binding free energies of a focal adhesion kinase, an important target for the development of anticancer drugs, with pyrrolopyrimidine‐based ligands having different inhibitory power. To this aim, we employ steered molecular dynamics simulations combined with nonequilibrium work theorems for free energy calculations. This technique proves very powerful when a series of ligand analogues is considered, allowing one to tackle estimation of protein – ligand relative binding free energies in a reasonable time. In our cases, the calculated binding affinities are comparable with those recovered from experiments by exploiting the Michaelis – Menten mechanism with a competitive inhibitor.     

A QM/MM simulation study of transamination reaction at the active site of aspartate aminotransferase: Free energy landscape and proton transfer pathways

Transaminase is a key enzyme for amino acid metabolism, which reversibly catalyzes the transamination reaction with the help of PLP (pyridoxal 5^' -phosphate) as its cofactor. Here we have investigated the mechanism and free energy landscape of the transamination reaction involving the aspartate transaminase (AspTase) enzyme and aspartate-PLP (Asp-PLP) complex using QM/MM simulation and metadynamics methods. The reaction is found to follow a stepwise mechanism where the active site residue Lys258 acts as a base to shuttle a proton from α -carbon (CA) to imine carbon (C4A) of the PLP-Asp Schiff base. In the first step, the Lys258 abstracts the CA proton of the substrate leading to the formation of a carbanionic intermediate which is followed by the reprotonation of the Asp-PLP Schiff base at C4A atom by Lys258. It is found that the free energy barrier for the proton abstraction by Lys258 and that for the reprotonation are 17.85 and 3.57 kcal/mol, respectively. The carbanionic intermediate is 7.14 kcal/mol higher in energy than the reactant. Hence, the first step acts as the rate limiting step. The present calculations also show that the Lys258 residue undergoes a conformational change after the first step of transamination reaction and becomes proximal to C4A atom of the Asp-PLP Schiff base to favor the second step. The active site residues Tyr70* and Gly38 anchor the Lys258 in proper position and orientation during the first step of the reaction and stabilize the positive charge over Lys258 generated at the intermediate step.     

Theoretical thermodynamic study of the adenine–thymine tautomeric equilibrium: Electronic structure calculations and steered molecular dynamic simulations

Free energy of the tautomeric equilibrium A‐T ? A*‐T* between the canonical and noncanonical DNA base equilibrium in aqueous solution was theoretically determined by applying electronic structure methods (at the M06‐2X‐PCM/6‐311++G(d,p) level) and steered molecular dynamic simulations. Concerted and stepwise mechanisms were considered for the double proton transfer in an effort to explain the anomalous behavior of this system where an unfavorable process without a transition state can be observed depending on the level of calculation used. Of the different mechanisms used in the simulations, the stepwise mechanism, in which the first step implies the transference of a proton from thymine to adenine, and a second step with the transference of a different proton from adenine to thymine, was the only one that showed two transition states and a reaction intermediate. However, a concerted and stepwise mechanism has similar kinetic and thermodynamic behavior, with similar reaction and activation energies. Simple proton transfer was more favorable for the transference of the hydrogen from the adenine to the thymine. The inclusion of an aqueous medium in this study only slightly modified these energies, but the barrier energy was higher when the solvent was described as a discrete medium. Transition states and intermediate structures were analyzed at molecular dynamic level.     

Evaluating nonpolarizable nucleic acid force fields: A systematic comparison of the nucleobases hydration free energies and chloroform‐to‐water partition coefficients

Nucleic acid force fields have been shown to reproduce structural properties of DNA and RNA very well, but comparative studies with respect to thermodynamic properties are rare. As a test for thermodynamic properties, we have computed hydration free energies and chloroform‐to‐water partition coefficients of nucleobases using the AMBER‐99, AMBER‐gaff, CHARMM‐27, GROMOS‐45a4/53a6 and OPLS‐AA force fields. A mutual force field comparison showed a very large spread in the calculated thermodynamic properties, demonstrating that some of the parameter sets require further optimization. The choice of solvent model used in the simulation does not have a significant effect on the results. Comparing the hydration free energies obtained by the various force fields to the adenine and thymine experimental values showed a very large deviation for the GROMOS and AMBER parameter sets. Validation against experimental partition coefficients showed good agreement for the CHARMM‐27 parameter set. In view of mutation studies, differences in partition coefficient between two bases were also compared, and good agreement between experiments and calculations was found for the AMBER‐99 parameter set. Overall, the CHARMM‐27 parameter set performs best with respect to the thermodynamic properties tested here. © 2012 Wiley Periodicals, Inc.     

Pharmacophore model-aided virtual screening combined with comparative molecular docking and molecular dynamics for identification of marine natural products as SARS-CoV-2 papain-like protease inhibitors

Targeting SARS-CoV-2 papain-like protease using inhibitors is a suitable approach for inhibition of virus replication and dysregulation of host anti-viral immunity. Engaging all five binding sites far from the catalytic site of PLpro is essential for developing a potent inhibitor. We developed and validated a structure-based pharmacophore model with 9 features of a potent PLpro inhibitor. The pharmacophore model-aided virtual screening of the comprehensive marine natural product database predicted 66 initial hits. This hit library was downsized by filtration through a molecular weight filter of ≤ 500 g/mol. The 50 resultant hits were screened by comparative molecular docking using AutoDock and AutoDock Vina. Comparative molecular docking enables benchmarking docking and relieves the disparities in the search and scoring functions of docking engines. Both docking engines retrieved 3 same compounds at different positions in the top 1 % rank, hence consensus scoring was applied, through which CMNPD28766, aspergillipeptide F emerged as the best PLpro inhibitor. Aspergillipeptide F topped the 50-hit library with a pharmacophore-fit score of 75.916. Favorable binding interactions were predicted between aspergillipeptide F and PLpro similar to the native ligand XR8-24. Aspergillipeptide F was able to engage all the 5 binding sites including the newly discovered BL2 groove, site V. Molecular dynamics for quantification of Cα-atom movements of PLpro after ligand binding indicated that it exhibits highly correlated domain movements contributing to the low free energy of binding and a stable conformation. Thus, aspergillipeptide F is a promising candidate for pharmaceutical and clinical development as a potent SARS-CoV-2 PLpro inhibitor.