Communications: Electron polarization critically stabilizes the Mg2+ complex in the catalytic core domain of HIV-1 integrase

Many-body effect determines the selectivity for Ca2+ and Mg2+ in proteins

Calcium ion is a versatile messenger in many cell-signaling processes. To achieve their functions, calcium-binding proteins selectively bind Ca2+ against a background of competing ions such as Mg2+ The high specificity of calcium-binding proteins has been intriguing since Mg2+ has a higher charge density than Ca2+ and is expected to bind more tightly to the carboxylate groups in calcium-binding pockets. Here, we showed that the specificity for Ca2+ is dictated by the many-body polarization effect, which is an energetic cost arising from the dense packing of multiple residues around the metal ion. Since polarization has stronger distance dependence compared with permanent electrostatics, the cost associated with the smaller Mg2+ is much higher than that with Ca2+ and outweighs the electrostatic attraction favorable for Mg2+ With the AMOEBA (atomic multipole optimized energetics for biomolecular simulation) polarizable force field, our simulations captured the relative binding free energy between Ca2+ and Mg2+ for proteins with various types of binding pockets and explained the nonmonotonic size dependence of the binding free energy in EF-hand proteins. Without electronic polarization, the smaller ions are always favored over larger ions and the relative binding free energy is roughly proportional to the net charge of the pocket. The many-body effect depends on both the number and the arrangement of charged residues. Fine-tuning of the ion selectivity could be achieved by combining the many-body effect and geometric constraint.

Toward amino acid typing for proteins in FFLUX

Continuing the development of the FFLUX, a multipolar polarizable force field driven by machine learning, we present a modern approach to atom-typing and building transferable models for predicting atomic properties in proteins. Amino acid atomic charges in a peptide chain respond to the substitution of a neighboring residue and this response can be categorized in a manner similar to atom-typing. Using a machine learning method called kriging, we are able to build predictive models for an atom that is defined, not only by its local environment, but also by its neighboring residues, for a minimal additional computational cost. We found that prediction errors were up to 11 times lower when using a model specific to the correct group of neighboring residues, with a mean prediction of ∼0.0015 au. This finding suggests that atoms in a force field should be defined by more than just their immediate atomic neighbors. When comparing an atom in a single alanine to an analogous atom in a deca-alanine helix, the mean difference in charge is 0.026 au. Meanwhile, the same difference between a trialanine and a deca-alanine helix is only 0.012 au. When compared to deca-alanine models, the transferable models are up to 20 times faster to train, and require significantly less ab initio calculation, providing a practical route to modeling large biological systems. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

FEREBUS: Highly parallelized engine for kriging training

FFLUX is a novel force field based on quantum topological atoms, combining multipolar electrostatics with IQA intraatomic and interatomic energy terms. The program FEREBUS calculates the hyperparameters of models produced by the machine learning method kriging. Calculation of kriging hyperparameters (θ and p) requires the optimization of the concentrated log-likelihood L̂(θ,p). FEREBUS uses Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms to find the maximum of L̂(θ,p). PSO and DE are two heuristic algorithms that each use a set of particles or vectors to explore the space in which L̂(θ,p) is defined, searching for the maximum. The log-likelihood is a computationally expensive function, which needs to be calculated several times during each optimization iteration. The cost scales quickly with the problem dimension and speed becomes critical in model generation. We present the strategy used to parallelize FEREBUS, and the optimization of L̂(θ,p) through PSO and DE. The code is parallelized in two ways. MPI parallelization distributes the particles or vectors among the different processes, whereas the OpenMP implementation takes care of the calculation of L̂(θ,p), which involves the calculation and inversion of a particular matrix, whose size increases quickly with the dimension of the problem. The run time shows a speed-up of 61 times going from single core to 90 cores with a saving, in one case, of ∼98% of the single core time. In fact, the parallelization scheme presented reduces computational time from 2871 s for a single core calculation, to 41 s for 90 cores calculation. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Large-scale molecular dynamics simulation: Effect of polarization on thrombin-ligand binding energy

Molecular dynamics (MD) simulations lasting 500 ns were performed in explicit water to investigate the effect of polarization on the binding of ligands to human α-thrombin based on the standard nonpolarizable AMBER force field and the quantum-derived polarized protein-specific charge (PPC). The PPC includes the electronic polarization effect of the thrombin-ligand complex, which is absent in the standard force field. A detailed analysis and comparison of the results of the MD simulation with experimental data provided strong evidence that intra-protein, protein-ligand hydrogen bonds and the root-mean-square deviation of backbone atoms were significantly stabilized through electronic polarization. Specifically, two critical hydrogen bonds between thrombin and the ligand were broken at approximately 190 ns when AMBER force field was used and the number of intra-protein backbone hydrogen bonds was higher under PPC than under AMBER. The thrombin-ligand binding energy was computed using the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) method, and the results were consistent with the experimental value obtained using PPC. Because hydrogen bonds were unstable, it was failed to predict the binding affinity under the AMBER force field. Furthermore, the results of the present study revealed that differences in the binding free energy between AMBER and PPC almost comes from the electrostatic interaction. Thus, this study provides evidence that protein polarization is critical to accurately describe protein-ligand binding.

Accurate Calculation of Electric Fields Inside Enzymes

The specific electric field generated by a protease at its active site is considered as an important source of the catalytic power. Accurate calculation of electric field at the active site of an enzyme has both fundamental and practical importance. Measuring site-specific changes of electric field at internal sites of proteins due to, eg, mutation, has been realized by using molecular probes with CO or CN groups in the context of vibrational Stark effect. However, theoretical prediction of change in electric field inside a protein based on a conventional force field, such as AMBER or OPLS, is often inadequate. For such calculation, quantum chemical approach or quantum-based polarizable or polarized force field is highly preferable. Compared with the result from conventional force field, significant improvement is found in predicting experimentally measured mutation-induced electric field change using quantum-based methods, indicating that quantum effect such as polarization plays an important role in accurate description of electric field inside proteins. In comparison, the best theoretical prediction comes from fully quantum mechanical calculation in which both polarization and inter-residue charge transfer effects are included for accurate prediction of electrostatics in proteins.

Some practical approaches to treating electrostatic polarization of proteins

Conspectus Electrostatic interaction plays a significant role in determining many properties of biomolecules, which exist and function in aqueous solution, a highly polar environment. For example, proteins are composed of amino acids with charged, polar, and nonpolar side chains and their specific electrostatic properties are fundamental to the structure and function of proteins. An important issue that arises in computational study of biomolecular interaction and dynamics based on classical force field is lack of polarization. Polarization is a phenomenon in which the charge distribution of an isolated molecule will be distorted when interacting with another molecule or presented in an external electric field. The distortion of charge distribution is intended to lower the overall energy of the molecular system, which is counter balanced by the increased internal energy of individual molecules due to the distorted charge distributions. The amount of the charge redistribution, which characterizes the polarizability of a molecule, is determined by the level of the charge distortion. Polarization is inherently quantum mechanical, and therefore classical force fields with fixed atomic charges are incapable of capturing this important effect. As a result, simulation studies based on popular force fields, AMBER, CHARMM, etc., lack the polarization effect, which is a widely known deficiency in most computational studies of biomolecules today. Many efforts have been devoted to remedy this deficiency, such as adding additional movable charge on the atom, allowing atomic charges to fluctuate, or including induced multipoles. Although various successes have been achieved and progress at various levels has been reported over the past decades, the issue of lacking polarization in force field based simulations is far from over. For example, some of these methods do not always give converged results, and other methods require huge computational cost. This Account reviews recent work on developing polarized and polarizable force fields based on fragment quantum mechanical calculations for proteins. The methods described here are based on quantum mechanical calculations of proteins in solution, but with a different level of rigor and different computational efficiency for the molecular dynamics applications. In the general approach, a fragment quantum mechanical calculation for protein with implicit solvation is carried out to derive a polarized protein-specific charge (PPC) for any given protein structure. The PPC correctly reflects the polarization state of the protein in a given conformation, and it can also be dynamically changed as the protein changes conformation in dynamics simulations. Another approach that is computationally more efficient is the effective polarizable bond method in which only polar bonds or groups can be polarized and their polarizabilities are predetermined from quantum mechanical calculations of these groups in external electric fields. Both methods can be employed for applications in various situations by taking advantage of their unique features.

Protein's native structure is dynamically stabilized by electronic polarization

In this paper, molecular dynamics (MD) simulations were performed for a number of benchmark proteins using both the standard assisted model building with energy refinement (AMBER) charge and the dynamically adjusted polarized protein-specific charge (DPPC) from quantum fragment calculations to provide accurate electrostatic interactions. Our result shows that proteins' dynamic structures drifted away from the native structures in simulations under standard (nonpolarizable) AMBER force field. For comparison, proteins' native structures were dynamically stable after a long time simulation under DPPC. The free energy landscape reveals that the native structure is the lowest energy conformation under DPPC, while it is not under standard AMBER charge. To further investigate the polarization effect on the stability of native structures of proteins, we restarted from some decoy structures generated from simulations using standard AMBER charges and then carried out further MD simulation using DPPC to refine those structures. Our study shows that the native structures from these decoy structures can be mostly recovered using DPPC and that the dynamic structures with the highest population in cluster analysis are in close agreement with the corresponding native structures. The current study demonstrates the importance of electronic polarization of protein in stabilizing the native structure.

The F130L mutation in streptavidin reduces its binding affinity to biotin through electronic polarization effect

Recently, Baugh et al. discovered that a distal point mutation (F130L) in streptavidin causes no distinct variation to the structure of the binding pocket but a 1000-fold reduction in biotin binding affinity. In this work, we carry out molecular dynamics simulations and apply an end-state free energy method to calculate the binding free energies of biotin to wild type streptavidin and its F130L mutant. The absolute binding affinities based on AMBER charge are repulsive, and the mutation induced binding loss is underestimated. When using the polarized protein-specific charge, the absolute binding affinities are significantly enhanced. In particular, both the absolute and relative binding affinities are in line with the experimental measurements. Further investigation indicates that polarization effect is indispensable in both the generation of structural ensembles and the calculation of interaction energies. This work verifies Baugh's conjecture that electrostatic polarization effect plays an essential role in modulating the binding affinity of biotin to the streptavidin through F130L mutation.

A New Quantum Calibrated Force Field for Zinc-Protein Complex

A quantum calibrated polarizable-charge transfer force field (QPCT) has been proposed to accurately describe the interaction dynamics of zinc-protein complexes. The parameters of the QPCT force field were calibrated by quantum chemistry calculation and capture the polarization and charge transfer effect. QPCTs are validated by molecular dynamic simulation of the hydration shell of the zinc ion, five proteins containing the most common zinc-binding sites (ZnCys2His2, ZnCys3His1, ZnCys4, Zn2Cys6), as well as protein-ligand binding energy in zinc protein MMP3. The calculated results show excellent agreement with the experimental measurement and with results from QM/MM simulation, demonstrating that QPCT is accurate enough to maintain the correct structural integrity of the zinc binding pocket and provide accurate interaction dynamics of the zinc-residue complex. The current approach can also be extended to the study of interaction dynamics of other metal-containing proteins by recalibrating the corresponding parameters to the specific complexes.

Effect of interprotein polarization on protein-protein binding energy

Molecular dynamics simulation in explicit water for the binding of the benchmark barnase-barstar complex was carried out to investigate the effect polarization of interprotein hydrogen bonds on its binding free energy. Our study is based on the AMBER force field but with polarized atomic charges derived from fragment quantum mechanical calculation for the protein complex. The quantum-derived atomic charges include the effect of polarization of interprotein hydrogen bonds, which was absent in the standard force fields that were used in previous theoretical calculations of barnase-barstar binding energy. This study shows that this polarization effect impacts both the static (electronic) and dynamic interprotein electrostatic interactions and significantly lowers the free energy of the barnase-barstar complex.

Polarization of intraprotein hydrogen bond is critical to thermal stability of short helix

Simulation result for protein folding/unfolding is highly dependent on the accuracy of the force field employed. Even for the simplest structure of protein such as a short helix, simulations using the existing force fields often fail to produce the correct structural/thermodynamic properties of the protein. Recent research indicated that lack of polarization is at least partially responsible for the failure to successfully fold a short helix. In this work, we develop a simple formula-based atomic charge polarization model for intraprotein (backbone) hydrogen bonding based on the existing AMBER force field to study the thermal stability of a short helix (2I9M) by replica exchange molecular dynamics simulation. By comparison of the simulation results with those obtained by employing the standard AMBER03 force field, the formula-based atomic charge polarization model gave the helix melting curve in close agreement with the NMR experiment. However, in simulations using the standard AMBER force field, the helix was thermally unstable at the temperature of the NMR experiment, with a melting temperature almost below the freezing point. The difference in observed thermal stability from these two simulations is the effect of backbone intraprotein polarization, which was included in the formula-based atomic charge polarization model. The polarization of backbone hydrogen bonding thus plays a critical role in the thermal stability of helix or more general protein structures.

Structure and dynamics of a dizinc metalloprotein: effect of charge transfer and polarization

Structures and dynamics of a recently designed dizinc metalloprotein (DFsc) (J. Mol. Biol. 2003, 334, 1101) are studied by molecular dynamics simulation using a dynamically adapted polarized force field derived from fragment quantum calculation for protein in solvent. To properly describe the effect of charge transfer and polarization in the present approach, quantum chemistry calculation of the zinc-binding group is periodically performed (on-the-fly) to update the atomic charges of the zinc-binding group during the MD simulation. Comparison of the present result with those obtained from simulations under standard AMBER force field reveals that charge transfer and polarization are critical to maintaining the correct asymmetric metal coordination in the DFsc. Detailed analysis of the result also shows that dynamic fluctuation of the zinc-binding group facilitates solvent interaction with the zinc ions. In particular, the dynamic fluctuation of the zinc-zinc distance is shown to be an important feature of the catalytic function of the di-ion zinc-binding group. Our study demonstrates that the dynamically adapted polarization approach is computationally practical and can be used to study other metalloprotein systems.