Sire: An interoperability engine for prototyping algorithms and exchanging information between molecular simulation programs.

Sire is a Python/C++ library that is used both to prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of many other programs and libraries. This empowers researchers to use sire to write a single script that can, for example, load a molecule from a PDBx/mmCIF file via Gemmi, perform SMARTS searches via RDKit, parameterize molecules using BioSimSpace, run GPU-accelerated molecular dynamics via OpenMM, and then display the resulting dynamics trajectory in a NGLView Jupyter notebook 3D molecular viewer. This functionality is built on by BioSimSpace, which uses sire's molecular information engine to interconvert with programs such as GROMACS, NAMD, Amber, and AmberTools for automated molecular parameterization and the running of molecular dynamics, metadynamics, and alchemical free energy workflows. Sire comes complete with a powerful molecular information search engine, plus trajectory loading and editing, analysis, and energy evaluation engines. This, when combined with an in-built computer algebra system, gives substantial flexibility to researchers to load, search for, edit, and combine molecular information from multiple sources and use that to drive novel algorithms by combining functionality from other programs. Sire is open source (GPL3) and is available via conda and at a free Jupyter notebook server at https://try.openbiosim.org. Sire is supported by the not-for-profit OpenBioSim community interest company.

Exploration of the structural requirements of Aurora Kinase B inhibitors by a combined QSAR, modelling and molecular simulation approach.

Aurora kinase B plays an important role in the cell cycle to orchestrate the mitotic process. The amplification and overexpression of this kinase have been implicated in several human malignancies. Therefore, Aurora kinase B is a potential drug target for anticancer therapies. Here, we combine atom-based 3D-QSAR analysis and pharmacophore model generation to identify the principal structural features of acylureidoindolin derivatives that could potentially be responsible for the inhibition of Aurora kinase B. The selected CoMFA and CoMSIA model showed significant results with cross-validation values (q2) of 0.68, 0.641 and linear regression values (r2) of 0.971, 0.933 respectively. These values support the statistical reliability of our model. A pharmacophore model was also generated, incorporating features of reported crystal complex structures of Aurora kinase B. The pharmacophore model was used to screen commercial databases to retrieve potential lead candidates. The resulting hits were analyzed at each stage for diversity based on the pharmacophore model, followed by molecular docking and filtering based on their interaction with active site residues and 3D-QSAR predictions. Subsequently, MD simulations and binding free energy calculations were performed to test the predictions and to characterize interactions at the molecular level. The results suggested that the identified compounds retained the interactions with binding residues. Binding energy decomposition identified residues Glu155, Trp156 and Ala157 of site B and Leu83 and Leu207 of site C as major contributors to binding affinity, complementary to 3D-QSAR results. To best of our knowledge, this is the first comparison of WaterSwap field and 3D-QSAR maps. Overall, this integrated strategy provides a basis for the development of new and potential AK-B inhibitors and is applicable to other protein targets.

A General Mechanism for Signal Propagation in the Nicotinic Acetylcholine Receptor Family.

Nicotinic acetylcholine receptors (nAChRs) modulate synaptic activity in the central nervous system. The α7 subtype, in particular, has attracted considerable interest in drug discovery as a target for several conditions, including Alzheimer's disease and schizophrenia. Identifying agonist-induced structural changes underlying nAChR activation is fundamentally important for understanding biological function and rational drug design. Here, extensive equilibrium and nonequilibrium molecular dynamics simulations, enabled by cloud-based high-performance computing, reveal the molecular mechanism by which structural changes induced by agonist unbinding are transmitted within the human α7 nAChR. The simulations reveal the sequence of coupled structural changes involved in driving conformational change responsible for biological function. Comparison with simulations of the α4ß2 nAChR subtype identifies features of the dynamical architecture common to both receptors, suggesting a general structural mechanism for signal propagation in this important family of receptors.

Synthetic self-assembling ADDomer platform for highly efficient vaccination by genetically encoded multiepitope display.

Self-assembling virus-like particles represent highly attractive tools for developing next-generation vaccines and protein therapeutics. We created ADDomer, an adenovirus-derived multimeric protein-based self-assembling nanoparticle scaffold engineered to facilitate plug-and-play display of multiple immunogenic epitopes from pathogens. We used cryo-electron microscopy at near-atomic resolution and implemented novel, cost-effective, high-performance cloud computing to reveal architectural features in unprecedented detail. We analyzed ADDomer interaction with components of the immune system and developed a promising first-in-kind ADDomer-based vaccine candidate to combat emerging Chikungunya infectious disease, exemplifying the potential of our approach.

Visualizing protein-ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site.

Kallikrein-8, a serine protease, is a target for structure-based drug design due to its therapeutic potential in treating Alzheimer's disease and is also useful as a biomarker in ovarian cancer. We present a binding assessment of ligands to kallikrein-8 using a residue-wise decomposition of the binding energy. Binding of four putative inhibitors of kallikrein-8 is investigated through molecular dynamics simulation and ligand binding energy evaluation with two methods (MM/PBSA and WaterSwap). For visualization of the residue-wise decomposition of binding energies, chemical energy-wise decomposition or CHEWD is introduced as a plugin to UCSF Chimera and Pymol. CHEWD allows easy comparison between ligands using individual residue contributions to the binding energy. Molecular dynamics simulations indicate one ligand binds stably to the kallikrein-8 S1 binding site. Comparison with other members of the kallikrein family shows that residues responsible for binding are specific to kallikrein-8. Thus, ZINC02927490 is a promising lead for development of novel kallikrein-8 inhibitors.

Elucidation of Nonadditive Effects in Protein-Ligand Binding Energies: Thrombin as a Case Study.

Accurate predictions of free energies of binding of ligands to proteins are challenging partly because of the nonadditivity of protein-ligand interactions; i.e., the free energy of binding is the sum of numerous enthalpic and entropic contributions that cannot be separated into functional group contributions. In principle, molecular simulations methodologies that compute free energies of binding do capture nonadditivity of protein-ligand interactions, but efficient protocols are necessary to compute well-converged free energies of binding that clearly resolve nonadditive effects. To this end, an efficient GPU-accelerated implementation of alchemical free energy calculations has been developed and applied to two congeneric series of ligands of the enzyme thrombin. The results show that accurate binding affinities are computed across the two congeneric series and positive coupling between nonpolar R(1) substituents and a X = NH3(+) substituent is reproduced, albeit with a weaker trend than experimentally observed. By contrast, a docking methodology completely fails to capture nonadditive effects. Further analysis shows that the nonadditive effects are partly due to variations in the strength of a hydrogen-bond between the X = NH3(+) ligands family and thrombin residue Gly216. However, other partially compensating interactions occur across the entire binding site, and no single interaction dictates the magnitude of the nonadditive effects for all the analyzed protein-ligand complexes.

Registering methodology for imaging and analysis of residual-limb shape after transtibial amputation.

Successful prosthetic rehabilitation following lower-limb amputation depends upon a safe and comfortable socket-residual limb interface. Current practice predominantly uses a subjective, iterative process to establish socket shape, often requiring several visits to a prosthetist. This study proposes an objective methodology for residual-limb shape scanning and analysis by high-resolution, automated measurements. A three-dimensional printed "analog" residuum was scanned with three surface digitizers on 10 occasions. Accuracy was measured by the scan height error between repeat analog scans and the computer-aided design (CAD) geometry and the scan versus CAD volume. Subsequently, 20 male residuum casts from ambulatory individuals with transtibial amputation were scanned by two observers, and 10 were repeat-scanned by one observer. The shape files were aligned spatially and geometric measurements extracted. Repeatability was evaluated by intraclass correlation, Bland-Altman analysis of scan volumes, and pairwise root-mean-square error ranges of scan area and width profiles. Submillimeter accuracy was achieved when scanning the analog shape, and using male residuum casts the process was highly repeatable within and between observers. The technique provides clinical researchers and prosthetists the capability to establish their own quantitative, objective, multipatient data sets, providing an evidence base for training, long-term follow-up, and interpatient outcome comparison, for decision support in socket design.

Combined quantum mechanics/molecular mechanics (QM/MM) simulations for protein-ligand complexes: free energies of binding of water molecules in influenza neuraminidase.

The applicability of combined quantum mechanics/molecular mechanics (QM/MM) methods for the calculation of absolute binding free energies of conserved water molecules in protein/ligand complexes is demonstrated. Here, we apply QM/MM Monte Carlo simulations to investigate binding of water molecules to influenza neuraminidase. We investigate five different complexes, including those with the drugs oseltamivir and peramivir. We investigate water molecules in two different environments, one more hydrophobic and one hydrophilic. We calculate the free-energy change for perturbation of a QM to MM representation of the bound water molecule. The calculations are performed at the BLYP/aVDZ (QM) and TIP4P (MM) levels of theory, which we have previously demonstrated to be consistent with one another for QM/MM modeling. The results show that the QM to MM perturbation is significant in both environments (greater than 1 kcal mol(-1)) and larger in the more hydrophilic site. Comparison with the same perturbation in bulk water shows that this makes a contribution to binding. The results quantify how electronic polarization differences in different environments affect binding affinity and also demonstrate that extensive, converged QM/MM free-energy simulations, with good levels of QM theory, are now practical for protein/ligand complexes.

Rapid decomposition and visualisation of protein-ligand binding free energies by residue and by water.

Recent advances in computational hardware, software and algorithms enable simulations of protein-ligand complexes to achieve timescales during which complete ligand binding and unbinding pathways can be observed. While observation of such events can promote understanding of binding and unbinding pathways, it does not alone provide information about the molecular drivers for protein-ligand association, nor guidance on how a ligand could be optimised to better bind to the protein. We have developed the waterswap (C. J. Woods et al., J. Chem. Phys., 2011, 134, 054114) absolute binding free energy method that calculates binding affinities by exchanging the ligand with an equivalent volume of water. A significant advantage of this method is that the binding free energy is calculated using a single reaction coordinate from a single simulation. This has enabled the development of new visualisations of binding affinities based on free energy decompositions to per-residue and per-water molecule components. These provide a clear picture of which protein-ligand interactions are strong, and which active site water molecules are stabilised or destabilised upon binding. Optimisation of the algorithms underlying the decomposition enables near-real-time visualisation, allowing these calculations to be used either to provide interactive feedback to a ligand designer, or to provide run-time analysis of protein-ligand molecular dynamics simulations.

Computational assay of H7N9 influenza neuraminidase reveals R292K mutation reduces drug binding affinity.

The emergence of a novel H7N9 avian influenza that infects humans is a serious cause for concern. Of the genome sequences of H7N9 neuraminidase available, one contains a substitution of arginine to lysine at position 292, suggesting a potential for reduced drug binding efficacy. We have performed molecular dynamics simulations of oseltamivir, zanamivir and peramivir bound to H7N9, H7N9-R292K, and a structurally related H11N9 neuraminidase. They show that H7N9 neuraminidase is structurally homologous to H11N9, binding the drugs in identical modes. The simulations reveal that the R292K mutation disrupts drug binding in H7N9 in a comparable manner to that observed experimentally for H11N9-R292K. Absolute binding free energy calculations with the WaterSwap method confirm a reduction in binding affinity. This indicates that the efficacy of antiviral drugs against H7N9-R292K will be reduced. Simulations can assist in predicting disruption of binding caused by mutations in neuraminidase, thereby providing a computational 'assay.'

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.

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.

A massively multicore parallelization of the Kohn-Sham energy gradients.

In a previous article [Brown et al., J Chem Theory Comput 2009, 4, 1620], we described a quadrature-based formulation of the Kohn-Sham Coulomb problem that allows for efficient parallelization over thousands of small processor cores. Here, we present the analytic gradients of this modified Kohn-Sham scheme, and describe the parallel implementation of the gradients on a numerical accelerator architecture. We demonstrate an order-of-magnitude acceleration for the combined energy and gradient calculation over a conventional single-core implementation.

Multicore Parallelization of Kohn-Sham Theory.

A multicore parallelization of Kohn-Sham theory is described, using standard commodity multisocket and multisocket/multicore shared-memory processors. Near-linear scaling of the parallel parts of the code was observed up to the maximum of sixteen cores that were available for benchmarking, and an order of magnitude reduction in run time was achieved running using sixteen threads on a quad-socket quad-core Xeon system. The speed-ups achieved using multisocket/multicore processors were competitive with those achieved using numerical accelerator cards.

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.

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.

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.

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.

Fluoride-selective binding in a new deep cavity calix[4]pyrrole: experiment and theory.

A new "super-extended cavity" tetraacetylcalix[4]pyrrole derivative was synthesized and characterized, and X-ray crystal structures of complexes bound to fluoride and acetonitrile were obtained. The binding behavior of this receptor was investigated by NMR titration, and the complex was found to exclusively bind fluoride ions in DMSO-d(6). This unusual binding behavior was investigated by Monte Carlo free energy perturbation simulations and Poisson calculations, and the ion specificity was seen to result from the favorable electrostatic interactions that the fluoride gains by sitting lower in the phenolic cavity of the receptor. The effect of water present in the DMSO on the calculated free energies of binding was also investigated. Owing to the use of a saturated ion solution, the effect of contaminating water is small in this case; however, it has the potential to be very significant at lower ion concentrations. Finally, the adaptive umbrella WHAM protocol was investigated and optimized for use in binding free energy calculations, and its efficiency was compared to that of the free energy perturbation calculations; adaptive umbrella WHAM was found to be approximately two times more efficient. In addition, structural evidence demonstrates that the protocol explores a wider conformational range than free energy perturbation and should therefore be the method of choice. This paper represents the first complete application of this methodology to "alchemical" changes.