Christopher J. Woods

An efficient method for the calculation of quantum mechanics/molecular mechanics free energies

The combination of quantum mechanics (QM) with molecular mechanics (MM) offers a route to improved accuracy in the study of biological systems, and there is now significant research effort being spent to develop QM/MM methods that can be applied to the calculation of relative free energies. Currently, the computational expense of the QM part of the calculation means that there is no single method that achieves both efficiency and rigor; either the QM/MM free energy method is rigorous and computationally expensive, or the method introduces efficiency-led assumptions that can lead to errors in the result, or a lack of generality of application. In this paper we demonstrate a combined approach to form a single, efficient, and, in principle, exact QM/MM free energy method. We demonstrate the application of this method by using it to explore the difference in hydration of water and methane. We demonstrate that it is possible to calculate highly converged QM/MM relative free energies at the MP2/aug-cc-pVDZ/OPLS level within just two days of computation, using commodity processors, and show how the method allows consistent, high-quality sampling of complex solvent configurational change, both when perturbing hydrophilic water into hydrophobic methane, and also when moving from a MM Hamiltonian to a QM/MM Hamiltonian. The results demonstrate the validity and power of this methodology, and raise important questions regarding the compatibility of MM and QM/MM forcefields, and offer a potential route to improved compatibility.

Biomolecular simulation and modelling: status, progress and prospects

Molecular simulation is increasingly demonstrating its practical value in the investigation of biological systems. Computational modelling of biomolecular systems is an exciting and rapidly developing area, which is expanding significantly in scope. A range of simulation methods has been developed that can be applied to study a wide variety of problems in structural biology and at the interfaces between physics, chemistry and biology. Here, we give an overview of methods and some recent developments in atomistic biomolecular simulation. Some recent applications and theoretical developments are highlighted.

Long Time Scale GPU Dynamics Reveal the Mechanism of Drug Resistance of the Dual Mutant I223R/H275Y Neuraminidase from H1N1-2009 Influenza Virus

Multidrug resistance of the pandemic H1N1-2009 strain of influenza has been reported due to widespread treatment using the neuraminidase (NA) inhibitors, oseltamivir (Tamiflu), and zanamivir (Relenza). From clinical data, the single I223R (IR(1)) mutant of H1N1-2009 NA reduced efficacy of oseltamivir and zanamivir by 45 and 10 times, (1) respectively. More seriously, the efficacy of these two inhibitors against the double mutant I223R/H275Y (IRHY(2)) was significantly reduced by a factor of 12 374 and 21 times, respectively, compared to the wild-type.(2) This has led to the question of why the efficacy of the NA inhibitors is reduced by the occurrence of these mutations and, specifically, why the efficacy of oseltamivir against the double mutant IRHY was significantly reduced, to the point where oseltamivir has become an ineffective treatment. In this study, 1 μs of molecular dynamics (MD) simulations was performed to answer these questions. The simulations, run using graphical processors (GPUs), were used to investigate the effect of conformational change upon binding of the NA inhibitors oseltamivir and zanamivir in the wild-type and the IR and IRHY mutant strains. These long time scale dynamics simulations demonstrated that the mechanism of resistance of IRHY to oseltamivir was due to the loss of key hydrogen bonds between the inhibitor and residues in the 150-loop. This allowed NA to transition from a closed to an open conformation. Oseltamivir binds weakly with the open conformation of NA due to poor electrostatic interactions between the inhibitor and the active site. The results suggest that the efficacy of oseltamivir is reduced significantly because of conformational changes that lead to the open form of the 150-loop. This suggests that drug resistance could be overcome by increasing hydrogen bond interactions between NA inhibitors and residues in the 150-loop, with the aim of maintaining the closed conformation, or by designing inhibitors that can form a hydrogen bond to the mutant R223 residue, thereby preventing competition between R223 and R152.

A water-swap reaction coordinate for the calculation of absolute protein–ligand binding free energies

The accurate prediction of absolute protein-ligand binding free energies is one of the grand challenge problems of computational science. Binding free energy measures the strength of binding between a ligand and a protein, and an algorithm that would allow its accurate prediction would be a powerful tool for rational drug design. Here we present the development of a new method that allows for the absolute binding free energy of a protein-ligand complex to be calculated from first principles, using a single simulation. Our method involves the use of a novel reaction coordinate that swaps a ligand bound to a protein with an equivalent volume of bulk water. This water-swap reaction coordinate is built using an identity constraint, which identifies a cluster of water molecules from bulk water that occupies the same volume as the ligand in the protein active site. A dual topology algorithm is then used to swap the ligand from the active site with the identified water cluster from bulk water. The free energy is then calculated using replica exchange thermodynamic integration. This returns the free energy change of simultaneously transferring the ligand to bulk water, as an equivalent volume of bulk water is transferred back to the protein active site. This, directly, is the absolute binding free energy. It should be noted that while this reaction coordinate models the binding process directly, an accurate force field and sufficient sampling are still required to allow for the binding free energy to be predicted correctly. In this paper we present the details and development of this method, and demonstrate how the potential of mean force along the water-swap coordinate can be improved by calibrating the soft-core Coulomb and Lennard-Jones parameters used for the dual topology calculation. The optimal parameters were applied to calculations of protein-ligand binding free energies of a neuraminidase inhibitor (oseltamivir), with these results compared to experiment. These results demonstrate that the water-swap coordinate provides a viable and potentially powerful new route for the prediction of protein-ligand binding free energies.

FESetup: Automating Setup for Alchemical Free Energy Simulations.

FESetup is a new pipeline tool which can be used flexibly within larger workflows. The tool aims to support fast and easy setup of alchemical free energy simulations for molecular simulation packages such as AMBER, GROMACS, Sire, or NAMD. Post-processing methods like MM-PBSA and LIE can be set up as well. Ligands are automatically parametrized with AM1-BCC, and atom mappings for a single topology description are computed with a maximum common substructure search (MCSS) algorithm. An abstract molecular dynamics (MD) engine can be used for equilibration prior to free energy setup or standalone. Currently, all modern AMBER force fields are supported. Ease of use, robustness of the code, and automation where it is feasible are the main development goals. The project follows an open development model, and we welcome contributions.

Grid computing and biomolecular simulation

Biomolecular computer simulations are now widely used not only in an academic setting to understand the fundamental role of molecular dynamics on biological function, but also in the industrial context to assist in drug design. In this paper, two applications of Grid computing to this area will be outlined. The first, involving the coupling of distributed computing resources to dedicated Beowulf clusters, is targeted at simulating protein conformational change using the Replica Exchange methodology. In the second, the rationale and design of a database of biomolecular simulation trajectories is described. Both applications illustrate the increasingly important role modern computational methods are playing in the life sciences.

Massively Multicore Parallelization of Kohn-Sham Theory

A multicore parallelization of Kohn-Sham density functional theory is described, using an accelerator technology made by ClearSpeed Technology. Efficiently scaling parallelization over 2304 cores is achieved. To deliver this degree of parallelism, the Coulomb problem is reformulated to use Poisson density fitting with numerical quadrature of the required three-index integrals; extensive testing reveals negligible errors from the additional approximations.

A "Stepping Stone" Approach for Obtaining Quantum Free Energies of Hydration

We present a method which uses DFT (quantum, QM) calculations to improve free energies of binding computed with classical force fields (classical, MM). To overcome the incomplete overlap of configurational spaces between MM and QM, we use a hybrid Monte Carlo approach to generate quickly correct ensembles of structures of intermediate states between a MM and a QM/MM description, hence taking into account a great fraction of the electronic polarization of the quantum system, while being able to use thermodynamic integration to compute the free energy of transition between the MM and QM/MM. Then, we perform a final transition from QM/MM to full QM using a one-step free energy perturbation approach. By using QM/MM as a stepping stone toward the full QM description, we find very small convergence errors (<1 kJ/mol) in the transition to full QM. We apply this method to compute hydration free energies, and we obtain consistent improvements over the MM values for all molecules we used in this study. This approach requires large-scale DFT calculations as the full QM systems involved the ligands and all waters in their simulation cells, so the linear-scaling DFT code ONETEP was used for these calculations.

Analysis and assay of oseltamivir-resistant mutants of influenza neuraminidase via direct observation of drug unbinding and rebinding in simulation

The emergence of influenza drug resistance is a major public health concern. The molecular basis of resistance to oseltamivir (Tamiflu) is investigated using a computational assay involving multiple 500 ns unrestrained molecular dynamics (MD) simulations of oseltamivir complexed with mutants of H1N1-2009 influenza neuraminidase. The simulations, accelerated using graphics processors (GPUs), and using a fully explicit model of water, are of sufficient length to observe multiple drug unbinding and rebinding events. Drug unbinding occurs during simulations of known oseltamivir-resistant mutants of neuraminidase. Molecular-level rationalizations of drug resistance are revealed by analysis of these unbinding trajectories, with particular emphasis on the dynamics of the mutant residues. The results indicate that MD simulations can predict weakening of binding associated with drug resistance. In addition, visualization and analysis of binding site water molecules reveal their importance in stabilizing the binding mode of the drug. Drug unbinding is accompanied by conformational changes, driven by the mutant residues, which results in flooding of a key pocket containing tightly bound water molecules. This displaces oseltamivir, allowing the tightly bound water molecules to be released into bulk. In addition to the role of water, analysis of the trajectories reveals novel behavior of the structurally important 150-loop. Motion of the loop, which can move between an open and closed conformation, is intimately associated with drug unbinding and rebinding. Opening of the loop occurs coincidentally with drug unbinding, and interactions between oseltamivir and the loop seem to aid in the repositioning of the drug back into an approximation of its original binding mode on rebinding. The similarity of oseltamivir to a transition state analogue for neuraminidase suggests that the dynamics of the loop could play an important functional role in the enzyme, with loop closing aiding in binding of the substrate and loop opening aiding the release of the product.

Lennard−Jones Parameters for B3LYP/CHARMM27 QM/MM Modeling of Nucleic Acid Bases

Combined quantum mechanics/molecular mechanics (QM/MM) methods allow computations on chemical events in large molecular systems. Here, we have tested the suitability of the standard CHARMM27 forcefield Lennard-Jones van der Waals (vdW) parameters for the treatment of nucleic acid bases in QM/MM calculations at the B3LYP/6-311+G(d,p)-CHARMM27 level. Alternative parameters were also tested by comparing the QM/MM hydrogen bond lengths and interaction energies with full QM [B3LYP/6-311+G(d,p)] results. The optimization of vdW parameters for nucleic acid bases is challenging because of the likelihood of multiple hydrogen bonds between the nucleic acid base and a water molecule. Two sets of optimized atomic vdW parameters for polar hydrogen, carbonyl carbon, and aromatic nitrogen atoms for nucleic acid bases are reported: base-dependent and base-independent. The results indicate that, for QM/MM investigations of nucleic acids, the standard forcefield vdW parameters may not be appropriate for atoms treated by QM. QM/MM interaction energies calculated with standard CHARMM27 parameters are found to be too large, by around 3 kcal/mol. This is because of overestimation of electrostatic interactions. Interaction energies closer to the full QM results are found using the optimized vdW parameters developed here. The optimized vdW parameters [developed by reference to B3LYP/6-311+G(d,p) results] were also tested at the B3LYP/6-31G(d) QM/MM level and were found to be transferable to the lower level. The optimized parameters also model the interaction energies of charged nucleic acid bases and deprotonation energies reasonably well.