Hybrid programming-model strategies for GPU offloading of electronic structure calculation kernels.

To address the challenge of performance portability and facilitate the implementation of electronic structure solvers, we developed the basic matrix library (BML) and Parallel, Rapid O(N), and Graph-based Recursive Electronic Structure Solver (PROGRESS) library. The BML implements linear algebra operations necessary for electronic structure kernels using a unified user interface for various matrix formats (dense and sparse) and architectures (CPUs and GPUs). Focusing on density functional theory and tight-binding models, PROGRESS implements several solvers for computing the single-particle density matrix and relies on BML. In this paper, we describe the general strategies used for these implementations on various computer architectures, using OpenMP target functionalities on GPUs, in conjunction with third-party libraries to handle performance critical numerical kernels. We demonstrate the portability of this approach and its performance in benchmark problems.

Water Networks in Photosystem II Using Crystalline Molecular Dynamics Simulations and Room-Temperature XFEL Serial Crystallography.

Structural dynamics of water and its hydrogen-bonding networks play an important role in enzyme function via the transport of protons, ions, and substrates. To gain insights into these mechanisms in the water oxidation reaction in Photosystem II (PS II), we have performed crystalline molecular dynamics (MD) simulations of the dark-stable S1 state. Our MD model consists of a full unit cell with 8 PS II monomers in explicit solvent (861 894 atoms), enabling us to compute the simulated crystalline electron density and to compare it directly with the experimental density from serial femtosecond X-ray crystallography under physiological temperature collected at X-ray free electron lasers (XFELs). The MD density reproduced the experimental density and water positions with high fidelity. The detailed dynamics in the simulations provided insights into the mobility of water molecules in the channels beyond what can be interpreted from experimental B-factors and electron densities alone. In particular, the simulations revealed fast, coordinated exchange of waters at sites where the density is strong, and water transport across the bottleneck region of the channels where the density is weak. By computing MD hydrogen and oxygen maps separately, we developed a novel Map-based Acceptor-Donor Identification (MADI) technique that yields information which helps to infer hydrogen-bond directionality and strength. The MADI analysis revealed a series of hydrogen-bond wires emanating from the Mn cluster through the Cl1 and O4 channels; such wires might provide pathways for proton transfer during the reaction cycle of PS II. Our simulations provide an atomistic picture of the dynamics of water and hydrogen-bonding networks in PS II, with implications for the specific role of each channel in the water oxidation reaction.

Graph-based quantum response theory and shadow Born-Oppenheimer molecular dynamics.

Graph-based linear scaling electronic structure theory for quantum-mechanical molecular dynamics simulations [A. M. N. Niklasson et al., J. Chem. Phys. 144, 234101 (2016)] is adapted to the most recent shadow potential formulations of extended Lagrangian Born-Oppenheimer molecular dynamics, including fractional molecular-orbital occupation numbers [A. M. N. Niklasson, J. Chem. Phys. 152, 104103 (2020) and A. M. N. Niklasson, Eur. Phys. J. B 94, 164 (2021)], which enables stable simulations of sensitive complex chemical systems with unsteady charge solutions. The proposed formulation includes a preconditioned Krylov subspace approximation for the integration of the extended electronic degrees of freedom, which requires quantum response calculations for electronic states with fractional occupation numbers. For the response calculations, we introduce a graph-based canonical quantum perturbation theory that can be performed with the same natural parallelism and linear scaling complexity as the graph-based electronic structure calculations for the unperturbed ground state. The proposed techniques are particularly well-suited for semi-empirical electronic structure theory, and the methods are demonstrated using self-consistent charge density-functional tight-binding theory both for the acceleration of self-consistent field calculations and for quantum-mechanical molecular dynamics simulations. Graph-based techniques combined with the semi-empirical theory enable stable simulations of large, complex chemical systems, including tens-of-thousands of atoms.

Mix-and-inject XFEL crystallography reveals gated conformational dynamics during enzyme catalysis.

How changes in enzyme structure and dynamics facilitate passage along the reaction coordinate is a fundamental unanswered question. Here, we use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL), ambient-temperature X-ray crystallography, computer simulations, and enzyme kinetics to characterize how covalent catalysis modulates isocyanide hydratase (ICH) conformational dynamics throughout its catalytic cycle. We visualize this previously hypothetical reaction mechanism, directly observing formation of a thioimidate covalent intermediate in ICH microcrystals during catalysis. ICH exhibits a concerted helical displacement upon active-site cysteine modification that is gated by changes in hydrogen bond strength between the cysteine thiolate and the backbone amide of the highly strained Ile152 residue. These catalysis-activated motions permit water entry into the ICH active site for intermediate hydrolysis. Mutations at a Gly residue (Gly150) that modulate helical mobility reduce ICH catalytic turnover and alter its pre-steady-state kinetic behavior, establishing that helical mobility is important for ICH catalytic efficiency. These results demonstrate that MISC can capture otherwise elusive aspects of enzyme mechanism and dynamics in microcrystalline samples, resolving long-standing questions about the connection between nonequilibrium protein motions and enzyme catalysis.

Biomolecular Solvation Structure Revealed by Molecular Dynamics Simulations.

To compare ordered water positions from experiment with those from molecular dynamics (MD) simulations, a number of MD models of water structure in crystalline endoglucanase were calculated. The starting MD model was derived from a joint X-ray and neutron diffraction crystal structure, enabling the use of experimentally assigned protonation states. Simulations were performed in the crystalline state, using a periodic 2 × 2 × 2 supercell with explicit solvent. Water X-ray and neutron scattering density maps were computed from MD trajectories using standard macromolecular crystallography methods. In one set of simulations, harmonic restraints were applied to bias the protein structure toward the crystal structure. For these simulations, the recall of crystallographic waters using strong peaks in the MD water electron density was very good, and there also was substantial visual agreement between the boomerang-like wings of the neutron scattering density and the crystalline water hydrogen positions. An unrestrained simulation also was performed. For this simulation, the recall of crystallographic waters was much lower. For both restrained and unrestrained simulations, the strongest water density peaks were associated with crystallographic waters. The results demonstrate that it is now possible to recover crystallographic water structure using restrained MD simulations but that it is not yet reasonable to expect unrestrained MD simulations to do the same. Further development and generalization of MD water models for force-field development, macromolecular crystallography, and medicinal chemistry applications is now warranted. In particular, the combination of room-temperature crystallography, neutron diffraction, and crystalline MD simulations promises to substantially advance modeling of biomolecular solvation.

Measuring and modeling diffuse scattering in protein X-ray crystallography.

X-ray diffraction has the potential to provide rich information about the structural dynamics of macromolecules. To realize this potential, both Bragg scattering, which is currently used to derive macromolecular structures, and diffuse scattering, which reports on correlations in charge density variations, must be measured. Until now, measurement of diffuse scattering from protein crystals has been scarce because of the extra effort of collecting diffuse data. Here, we present 3D measurements of diffuse intensity collected from crystals of the enzymes cyclophilin A and trypsin. The measurements were obtained from the same X-ray diffraction images as the Bragg data, using best practices for standard data collection. To model the underlying dynamics in a practical way that could be used during structure refinement, we tested translation-libration-screw (TLS), liquid-like motions (LLM), and coarse-grained normal-modes (NM) models of protein motions. The LLM model provides a global picture of motions and was refined against the diffuse data, whereas the TLS and NM models provide more detailed and distinct descriptions of atom displacements, and only used information from the Bragg data. Whereas different TLS groupings yielded similar Bragg intensities, they yielded different diffuse intensities, none of which agreed well with the data. In contrast, both the LLM and NM models agreed substantially with the diffuse data. These results demonstrate a realistic path to increase the number of diffuse datasets available to the wider biosciences community and indicate that dynamics-inspired NM structural models can simultaneously agree with both Bragg and diffuse scattering.

Conformational dynamics of a crystalline protein from microsecond-scale molecular dynamics simulations and diffuse X-ray scattering.

X-ray diffraction from protein crystals includes both sharply peaked Bragg reflections and diffuse intensity between the peaks. The information in Bragg scattering is limited to what is available in the mean electron density. The diffuse scattering arises from correlations in the electron density variations and therefore contains information about collective motions in proteins. Previous studies using molecular-dynamics (MD) simulations to model diffuse scattering have been hindered by insufficient sampling of the conformational ensemble. To overcome this issue, we have performed a 1.1-µs MD simulation of crystalline staphylococcal nuclease, providing 100-fold more sampling than previous studies. This simulation enables reproducible calculations of the diffuse intensity and predicts functionally important motions, including transitions among at least eight metastable states with different active-site geometries. The total diffuse intensity calculated using the MD model is highly correlated with the experimental data. In particular, there is excellent agreement for the isotropic component of the diffuse intensity, and substantial but weaker agreement for the anisotropic component. Decomposition of the MD model into protein and solvent components indicates that protein-solvent interactions contribute substantially to the overall diffuse intensity. We conclude that diffuse scattering can be used to validate predictions from MD simulations and can provide information to improve MD models of protein motions.

Graph-based linear scaling electronic structure theory.

We show how graph theory can be combined with quantum theory to calculate the electronic structure of large complex systems. The graph formalism is general and applicable to a broad range of electronic structure methods and materials, including challenging systems such as biomolecules. The methodology combines well-controlled accuracy, low computational cost, and natural low-communication parallelism. This combination addresses substantial shortcomings of linear scaling electronic structure theory, in particular with respect to quantum-based molecular dynamics simulations.

Predicting X-ray diffuse scattering from translation-libration-screw structural ensembles.

Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier's equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation-libration-screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.

Changes in an enzyme ensemble during catalysis observed by high-resolution XFEL crystallography.

Enzymes populate ensembles of structures necessary for catalysis that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography at an x-ray free electron laser to observe catalysis in a designed mutant isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations, and formation of the thioimidate intermediate selects for catalytically competent substates. The influence of cysteine ionization on the ICH ensemble is validated by determining structures of the enzyme at multiple pH values. Large molecular dynamics simulations in crystallo and time-resolved electron density maps show that Asp17 ionizes during catalysis and causes conformational changes that propagate across the dimer, permitting water to enter the active site for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Molecular-dynamics simulations of macromolecular diffraction, part II: Analysis of protein crystal simulations.

Molecular-dynamics (MD) simulations have contributed substantially to our understanding of protein structure and dynamics, yielding insights into many biological processes including protein folding, drug binding, and mechanisms of protein-protein interactions. Much of what is known about protein structure comes from macromolecular crystallography (MX) experiments. MD simulations of protein crystals are useful in the study of MX because the simulations can be analyzed to calculate almost any crystallographic observable of interest, from atomic coordinates to structure factors and densities, B-factors, multiple conformations and their populations/occupancies, and diffuse scattering intensities. Computing resources and software to support crystalline MD simulations are now readily available to many researchers studying protein structure and dynamics and who may be interested in advanced interpretation of MX data, including diffuse scattering. In this work, we outline methods of analyzing MD simulations of protein crystals and provide accompanying Jupyter notebooks as practical resources for researchers wishing to perform similar analyses on their own systems of interest.

Molecular-dynamics simulations of macromolecular diffraction, part I: Preparation of protein crystal simulations.

Molecular-dynamics (MD) simulations of protein crystals enable the prediction of structural and dynamical features of both the protein and the solvent components of macromolecular crystals, which can be validated against diffraction data from X-ray crystallographic experiments. The simulations have been useful for studying and predicting both Bragg and diffuse scattering in protein crystallography; however, the preparation is not yet automated and includes choices and tradeoffs that can impact the results. Here we examine some of the intricacies and consequences of the choices involved in setting up MD simulations of protein crystals for the study of diffraction data, and provide a recipe for preparing the simulations, packaged in an accompanying Jupyter notebook. This article and the accompanying notebook are intended to serve as practical resources for researchers wishing to put these models to work.

Molecular-dynamics simulation methods for macromolecular crystallography.

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein-solvent interface. To address this limitation, a set of MD-MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

Interpreting macromolecular diffraction through simulation.

This chapter discusses the use of diffraction simulators to improve experimental outcomes in macromolecular crystallography, in particular for future experiments aimed at diffuse scattering. Consequential decisions for upcoming data collection include the selection of either a synchrotron or free electron laser X-ray source, rotation geometry or serial crystallography, and fiber-coupled area detector technology vs. pixel-array detectors. The hope is that simulators will provide insights to make these choices with greater confidence. Simulation software, especially those packages focused on physics-based calculation of the diffraction, can help to predict the location, size, shape, and profile of Bragg spots and diffuse patterns in terms of an underlying physical model, including assumptions about the crystal's mosaic structure, and therefore can point to potential issues with data analysis in the early planning stages. Also, once the data are collected, simulation may offer a pathway to improve the measurement of diffraction, especially with weak data, and might help to treat problematic cases such as overlapping patterns.

Changes in an Enzyme Ensemble During Catalysis Observed by High Resolution XFEL Crystallography.

Enzymes populate ensembles of structures with intrinsically different catalytic proficiencies that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL) to observe catalysis in a designed mutant (G150T) isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations and formation of the thioimidate catalytic intermediate selects for catalytically competent substates. A prior proposal for active site cysteine charge-coupled conformational changes in ICH is validated by determining structures of the enzyme over a range of pH values. A combination of large molecular dynamics simulations of the enzyme in crystallo and time-resolved electron density maps shows that ionization of the general acid Asp17 during catalysis causes additional conformational changes that propagate across the dimer interface, connecting the two active sites. These ionization-linked changes in the ICH conformational ensemble permit water to enter the active site in a location that is poised for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Genome majority vote improves gene predictions.

Recent studies have noted extensive inconsistencies in gene start sites among orthologous genes in related microbial genomes. Here we provide the first documented evidence that imposing gene start consistency improves the accuracy of gene start-site prediction. We applied an algorithm using a genome majority vote (GMV) scheme to increase the consistency of gene starts among orthologs. We used a set of validated Escherichia coli genes as a standard to quantify accuracy. Results showed that the GMV algorithm can correct hundreds of gene prediction errors in sets of five or ten genomes while introducing few errors. Using a conservative calculation, we project that GMV would resolve many inconsistencies and errors in publicly available microbial gene maps. Our simple and logical solution provides a notable advance toward accurate gene maps.

Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques.

Water often plays a key role in protein structure, molecular recognition, and mediating protein-ligand interactions. Thus, free energy calculations must adequately sample water motions, which often proves challenging in typical MD simulation time scales. Thus, the accuracy of methods relying on MD simulations ends up limited by slow water sampling. Particularly, as a ligand is removed or modified, bulk water may not have time to fill or rearrange in the binding site. In this work, we focus on several molecular dynamics (MD) simulation-based methods attempting to help rehydrate buried water sites: BLUES, using nonequilibrium candidate Monte Carlo (NCMC); grand, using grand canonical Monte Carlo (GCMC); and normal MD. We assess the accuracy and efficiency of these methods in rehydrating target water sites. We selected a range of systems with varying numbers of waters in the binding site, as well as those where water occupancy is coupled to the identity or binding mode of the ligand. We analyzed the rehydration of buried water sites in binding pockets using both clustering of trajectories and direct analysis of electron density maps. Our results suggest both BLUES and grand enhance water sampling relative to normal MD and grand is more robust than BLUES, but also that water sampling remains a major challenge for all of the methods tested. The lessons we learned for these methods and systems are discussed.

Consistency of gene starts among Burkholderia genomes.

BACKGROUND: Evolutionary divergence in the position of the translational start site among orthologous genes can have significant functional impacts. Divergence can alter the translation rate, degradation rate, subcellular location, and function of the encoded proteins. RESULTS: Existing Genbank gene maps for Burkholderia genomes suggest that extensive divergence has occurred--53% of ortholog sets based on Genbank gene maps had inconsistent gene start sites. However, most of these inconsistencies appear to be gene-calling errors. Evolutionary divergence was the most plausible explanation for only 17% of the ortholog sets. Correcting probable errors in the Genbank gene maps decreased the percentage of ortholog sets with inconsistent starts by 68%, increased the percentage of ortholog sets with extractable upstream intergenic regions by 32%, increased the sequence similarity of intergenic regions and predicted proteins, and increased the number of proteins with identifiable signal peptides. CONCLUSIONS: Our findings highlight an emerging problem in comparative genomics: single-digit percent errors in gene predictions can lead to double-digit percentages of inconsistent ortholog sets. The work demonstrates a simple approach to evaluate and improve the quality of gene maps.

Selected papers from the Fourth Annual q-bio Conference on Cellular Information Processing.

This special issue consists of 11 original papers that elaborate on work presented at the Fourth Annual q-bio Conference on Cellular Information Processing, which was held on the campus of St John's College in Santa Fe, New Mexico, USA, 11-14 August 2010. Now in its fourth year, the q-bio conference has changed considerably over time. It is now well established and a major event in systems biology. The 2010 conference saw attendees from all continents (except Antarctica!) sharing novel results and participating in lively discussions at both the oral and poster sessions. The conference was oversubscribed and grew to 27 contributed talks, 16 poster spotlights and 137 contributed posters. We deliberately decreased the number of invited speakers to 21 to leave more space for contributed presentations, and the attendee feedback confirmed that the choice was a success. Although the q-bio conference has grown and matured, it has remained true to the original goal of being an intimate and dynamic event that brings together modeling, theory and quantitative experimentation for the study of cell regulation and information processing. Funded in part by a grant from NIGMS and by DOE funds through the Los Alamos National Laboratory Directed Research and Development program, the conference has continued to exhibit youth and vigor by attracting (and partially supporting) over 100 undergraduate, graduate and postdoctoral researchers. The associated q-bio summer school, which precedes the conference each year, further emphasizes the development of junior scientists and makes q-bio a singular event in its impact on the future of quantitative biology. In addition to an increased international presence, the conference has notably diversified its demographic representation within the USA, including increased participation from the southeastern corner of the country. One big change in the conference this year is our new publication partner, Physical Biology. Although we are very grateful to our previous partner, IET Systems Biology, for their help over the years in publicizing the work presented at the conference, we felt that the changing needs of our participants required that we find a new partner. We are thrilled that Physical Biology is publishing the q-bio proceedings this year. It has been a great collaboration, as evidenced by the high quality of this special issue. What's next for q-bio? We are happy to report that NIGMS has recently extended the q-bio conference grant for the next three years, ensuring strong support for junior researchers who need financial assistance to participate in the event. The conference will retain its emphasis on cellular information processing, but will also build connections to other areas of modern biology and biotechnology, focusing specifically on ecology and evolutionary biology next year. Indeed, to fully understand biological information processing systems, they must be studied in their ecological contexts. We will continue to honor distinguished contributors to the field in our opening banquets; the tradition started with Howard Berg, Bruce Alberts and Michael Savageau in previous years, and continues with Dennis Bray at the upcoming 2011 event. Starting in 2011, the conference will also venture into exploration of the social aspects of science. The future is bright for q-bio! We will see you at the Fifth Annual q-bio Conference on 10-13 August 2011, in Santa Fe, New Mexico, USA and at the Sixth Annual q-bio Conference in early August 2012.

Reproducibility of protein x-ray diffuse scattering and potential utility for modeling atomic displacement parameters.

Protein structure and dynamics can be probed using x-ray crystallography. Whereas the Bragg peaks are only sensitive to the average unit-cell electron density, the signal between the Bragg peaks-diffuse scattering-is sensitive to spatial correlations in electron-density variations. Although diffuse scattering contains valuable information about protein dynamics, the diffuse signal is more difficult to isolate from the background compared to the Bragg signal, and the reproducibility of diffuse signal is not yet well understood. We present a systematic study of the reproducibility of diffuse scattering from isocyanide hydratase in three different protein forms. Both replicate diffuse datasets and datasets obtained from different mutants were similar in pairwise comparisons (Pearson correlation coefficient ≥0.8). The data were processed in a manner inspired by previously published methods using custom software with modular design, enabling us to perform an analysis of various data processing choices to determine how to obtain the highest quality data as assessed using unbiased measures of symmetry and reproducibility. The diffuse data were then used to characterize atomic mobility using a liquid-like motions (LLM) model. This characterization was able to discriminate between distinct anisotropic atomic displacement parameter (ADP) models arising from different anisotropic scaling choices that agreed comparably with the Bragg data. Our results emphasize the importance of data reproducibility as a model-free measure of diffuse data quality, illustrate the ability of LLM analysis of diffuse scattering to select among alternative ADP models, and offer insights into the design of successful diffuse scattering experiments.