xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures

GOLEM: Automated and Robust Cryo-EM-Guided Ligand Docking with Explicit Water Molecules

A detailed understanding of ligand-protein interaction is essential for developing rational drug-design strategies. In recent years, technological advances in cryo-electron microscopy (cryo-EM) brought a new era to the structural determination of biological macromolecules and assemblies at high resolution, marking cryo-EM as a promising tool for studying ligand-protein interactions. However, even in high-resolution cryo-EM results, the densities for the bound small-molecule ligands are often of lower quality due to their relatively dynamic and flexible nature, frustrating their accurate coordinate assignment. To address the challenge of ligand modeling in cryo-EM maps, here we report the development of GOLEM (Genetic Optimization of Ligands in Experimental Maps), an automated and robust ligand docking method that predicts a ligand's pose and conformation in cryo-EM maps. GOLEM employs a Lamarckian genetic algorithm to perform a hybrid global/local search for exploring the ligand's conformational, orientational, and positional space. As an important feature, GOLEM explicitly considers water molecules and places them at optimal positions and orientations. GOLEM takes into account both molecular energetics and the correlation with the cryo-EM maps in its scoring function to optimally place the ligand. We have validated GOLEM against multiple cryo-EM structures with a wide range of map resolutions and ligand types, returning ligand poses in excellent agreement with the densities. As a VMD plugin, GOLEM is free of charge and accessible to the community. With these features, GOLEM will provide a valuable tool for ligand modeling in cryo-EM efforts toward drug discovery.

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge-driven or artificial intelligence-driven and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary-structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models that contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly while refining them against the density maps. We introduce such an adaptive decision-making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two prototypical protein systems, adenylate kinase and carbon monoxide dehydrogenase. For these test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2-3 Å map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that are inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from the chimpanzee adenovirus. The overhead for decision making remains low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install R-MDFF on different computing environments, from local Linux-based workstations to high-performance computing environments.

Automated simulation-based membrane protein refinement into cryo-EM data

The resolution revolution has increasingly enabled single-particle cryogenic electron microscopy (cryo-EM) reconstructions of previously inaccessible systems, including membrane proteins-a category that constitutes a disproportionate share of drug targets. We present a protocol for using density-guided molecular dynamics simulations to automatically refine atomistic models into membrane protein cryo-EM maps. Using adaptive force density-guided simulations as implemented in the GROMACS molecular dynamics package, we show how automated model refinement of a membrane protein is achieved without the need to manually tune the fitting force ad hoc. We also present selection criteria to choose the best-fit model that balances stereochemistry and goodness of fit. The proposed protocol was used to refine models into a new cryo-EM density of the membrane protein maltoporin, either in a lipid bilayer or detergent micelle, and we found that results do not substantially differ from fitting in solution. Fitted structures satisfied classical model-quality metrics and improved the quality and the model-to-map correlation of the x-ray starting structure. Additionally, the density-guided fitting in combination with generalized orientation-dependent all-atom potential was used to correct the pixel-size estimation of the experimental cryo-EM density map. This work demonstrates the applicability of a straightforward automated approach to fitting membrane protein cryo-EM densities. Such computational approaches promise to facilitate rapid refinement of proteins under different conditions or with various ligands present, including targets in the highly relevant superfamily of membrane proteins.

Molecular architecture and dynamics of SARS-CoV-2 envelope by integrative modeling

Despite tremendous efforts, the exact structure of SARS-CoV-2 and related betacoronaviruses remains elusive. SARS-CoV-2 envelope is a key structural component of the virion that encapsulates viral RNA. It is composed of three structural proteins, spike, membrane (M), and envelope, which interact with each other and with the lipids acquired from the host membranes. Here, we developed and applied an integrative multi-scale computational approach to model the envelope structure of SARS-CoV-2 with near atomistic detail, focusing on studying the dynamic nature and molecular interactions of its most abundant, but largely understudied, M protein. The molecular dynamics simulations allowed us to test the envelope stability under different configurations and revealed that the M dimers agglomerated into large, filament-like, macromolecular assemblies with distinct molecular patterns. These results are in good agreement with current experimental data, demonstrating a generic and versatile approach to model the structure of a virus de novo.

Visualizing RNA conformational and architectural heterogeneity in solution

RNA flexibility is reflected in its heterogeneous conformation. Through direct visualization using atomic force microscopy (AFM) and the adenosylcobalamin riboswitch aptamer domain as an example, we show that a single RNA sequence folds into conformationally and architecturally heterogeneous structures under near-physiological solution conditions. Recapitulated 3D topological structures from AFM molecular surfaces reveal that all conformers share the same secondary structural elements. Only a population-weighted cohort, not any single conformer, including the crystal structure, can account for the ensemble behaviors observed by small-angle X-ray scattering (SAXS). All conformers except one are functionally active in terms of ligand binding. Our findings provide direct visual evidence that the sequence-structure relationship of RNA under physiologically relevant solution conditions is more complex than the one-to-one relationship for well-structured proteins. The direct visualization of conformational and architectural ensembles at the single-molecule level in solution may suggest new approaches to RNA structural analyses.

State-specific morphological deformations of the lipid bilayer explain mechanosensitive gating of MscS ion channels

The force-from-lipids hypothesis of cellular mechanosensation posits that membrane channels open and close in response to changes in the physical state of the lipid bilayer, induced for example by lateral tension. Here, we investigate the molecular basis for this transduction mechanism by studying the mechanosensitive ion channel MscS from Escherichia coli and its eukaryotic homolog MSL1 from Arabidopsis thaliana. First, we use single-particle cryo-electron microscopy to determine the structure of a novel open conformation of wild-type MscS, stabilized in a thinned lipid nanodisc. Compared with the closed state, the structure shows a reconfiguration of helices TM1, TM2, and TM3a, and widening of the central pore. Based on these structures, we examined how the morphology of the membrane is altered upon gating, using molecular dynamics simulations. The simulations reveal that closed-state MscS causes drastic protrusions in the inner leaflet of the lipid bilayer, both in the absence and presence of lateral tension, and for different lipid compositions. These deformations arise to provide adequate solvation to hydrophobic crevices under the TM1-TM2 hairpin, and clearly reflect a high-energy conformation for the membrane, particularly under tension. Strikingly, these protrusions are largely eradicated upon channel opening. An analogous computational study of open and closed MSL1 recapitulates these findings. The gating equilibrium of MscS channels thus appears to be dictated by opposing conformational preferences, namely those of the lipid membrane and of the protein structure. We propose a membrane deformation model of mechanosensation, which posits that tension shifts the gating equilibrium towards the conductive state not because it alters the mode in which channel and lipids interact, but because it increases the energetic cost of the morphological perturbations in the membrane required by the closed state.

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

Energetics and J-coupling constants for Ala, Gly, and Val peptides demonstrated using ABEEM polarizable force field in vacuo and an aqueous solution

The development of an atom-bond electronegativity equalisation method at the σπ-level (ABEEM) polarisable force field (PFF) for peptides is presented. ABEEM PFF utilises a fluctuating charge model to explicitly describe...

Cryo-Electron Microscopy and Mass Analysis of Oligolysine-Coated DNA Nanostructures

Cationic coatings can enhance the stability of synthetic DNA objects in low ionic strength environments such as physiological fluids. Here, we used single-particle cryo-electron microscopy (cryo-EM), pseudoatomic model fitting, and single-molecule mass photometry to study oligolysine and polyethylene glycol (PEG)-oligolysine-coated multilayer DNA origami objects. The coatings preserve coarse structural features well on a resolution of multiple nanometers but can also induce deformations such as twisting and bending. Higher-density coatings also led to internal structural deformations in the DNA origami test objects, in which a designed honeycomb-type helical lattice was deformed into a more square-lattice-like pattern. Under physiological ionic strength, where the uncoated objects disassembled, the coated objects remained intact but they shrunk in the helical direction and expanded in the direction perpendicular to the helical axis. Helical details like major/minor grooves and crossover locations were not discernible in cryo-EM maps that we determined of DNA origami coated with oligolysine and PEG-oligolysine, whereas these features were visible in cryo-EM maps determined from the uncoated reference objects. Blunt-ended double-helical interfaces remained accessible underneath the coating and may be used for the formation of multimeric DNA origami assemblies that rely on stacking interactions between blunt-ended helices. The ionic strength requirements for forming multimers from coated DNA origami differed from those needed for uncoated objects. Using single-molecule mass photometry, we found that the mass of coated DNA origami objects prior to and after incubation in low ionic strength physiological conditions remained unchanged. This finding indicated that the coating effectively prevented strand dissociation but also that the coating itself remained stable in place. Our results validate oligolysine coatings as a powerful stabilization method for DNA origami but also reveal several potential points of failure that experimenters should watch to avoid working with false premises.

Fighting viruses with computers, right now

The synergistic conjunction of various technological revolutions with the accumulated knowledge and workflows is rapidly transforming several scientific fields. Particularly, Virology can now feed from accurate physical models, polished computational tools, and massive computational power to readily integrate high-resolution structures into biological representations of unprecedented detail. That preparedness allows for the first time to get crucial information for vaccine and drug design from in-silico experiments against emerging pathogens of worldwide concern at relevant action windows. The present work reviews some of the main milestones leading to these breakthroughs in Computational Virology, providing an outlook for future developments in capacity building and accessibility to computational resources.

Revealing the structures of megadalton-scale DNA complexes with nucleotide resolution

The methods of DNA nanotechnology enable the rational design of custom shapes that self-assemble in solution from sets of DNA molecules. DNA origami, in which a long template DNA single strand is folded by many short DNA oligonucleotides, can be employed to make objects comprising hundreds of unique DNA strands and thousands of base pairs, thus in principle providing many degrees of freedom for modelling complex objects of defined 3D shapes and sizes. Here, we address the problem of accurate structural validation of DNA objects in solution with cryo-EM based methodologies. By taking into account structural fluctuations, we can determine structures with improved detail compared to previous work. To interpret the experimental cryo-EM maps, we present molecular-dynamics-based methods for building pseudo-atomic models in a semi-automated fashion. Among other features, our data allows discerning details such as helical grooves, single-strand versus double-strand crossovers, backbone phosphate positions, and single-strand breaks. Obtaining this higher level of detail is a step forward that now allows designers to inspect and refine their designs with base-pair level interventions.

Precision design of DNA origami needs precision validation. Here, the authors developed cryo-EM methods for obtaining high resolution structural data and for constructing pseudo-atomic models in a semi-automated fashion, allowing for iterative nanodevice inspection and refinement.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Molecular basis of force-from-lipids gating in the mechanosensitive channel MscS

Prokaryotic mechanosensitive (MS) channels open by sensing the physical state of the membrane. As such, lipid-protein interactions represent the defining molecular process underlying mechanotransduction. Here, we describe cryo-electron microscopy (cryo-EM) structures of the E. coli small-conductance mechanosensitive channel (MscS) in nanodiscs (ND). They reveal a novel membrane-anchoring fold that plays a significant role in channel activation and establish a new location for the lipid bilayer, shifted ~14 Å from previous consensus placements. Two types of lipid densities are explicitly observed. A phospholipid that ‘hooks’ the top of each TM2-TM3 hairpin and likely plays a role in force sensing, and a bundle of acyl chains occluding the permeation path above the L105 cuff. These observations reshape our understanding of force-from-lipids gating in MscS and highlight the key role of allosteric interactions between TM segments and phospholipids bound to key dynamic components of the channel.

The Crystal Structure of Dph2 in Complex with Elongation Factor 2 Reveals the Structural Basis for the First Step of Diphthamide Biosynthesis

Elongation factor 2 (EF-2), a five-domain, GTP-dependent ribosomal translocase of archaebacteria and eukaryotes, undergoes post-translational modification to form diphthamide on a specific histidine residue in domain IV prior to binding the ribosome. The first step of diphthamide biosynthesis in archaebacteria is catalyzed by Dph2, a homodimeric radical S-adenosylmethionine (SAM) enzyme having a noncanonical architecture. Here, we describe a 3.5 Å resolution crystal structure of the Methanobrevibacter smithii (Ms) Dph2 homodimer bound to two molecules of MsEF-2, one of which is ordered and the other largely disordered. MsEF-2 is bound to both protomers of MsDph2, with domain IV bound to the active site of one protomer and domain III bound to a surface α-helix of an adjacent protomer. The histidine substrate of domain IV is inserted into the active site, which reveals for the first time the architecture of the Dph2 active site in complex with its target substrate. We also determined a high-resolution crystal structure of isolated MsDph2 bound to 5'-methylthioadenosine that shows a conserved arginine residue preoriented by conserved phenylalanine and aspartate residues for binding the carboxylate group of SAM. Mutagenesis experiments suggest that the arginine plays an important role in the first step of diphthamide biosynthesis.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.

Constructing atomic structural models into cryo-EM densities using molecular dynamics - Pros and cons

Accurate structure determination from electron density maps at 3-5 Å resolution necessitates a balance between extensive global and local sampling of atomistic models, yet with the stereochemical correctness of backbone and sidechain geometries. Molecular Dynamics Flexible Fitting (MDFF), particularly through a resolution-exchange scheme, ReMDFF, provides a robust way of achieving this balance for hybrid structure determination. Employing two high-resolution density maps, namely that of β-galactosidase at 3.2 Å and TRPV1 at 3.4 Å, we showcase the quality of ReMDFF-generated models, comparing them against ones submitted by independent research groups for the 2015-2016 Cryo-EM Model Challenge. This comparison offers a clear evaluation of ReMDFF's strengths and shortcomings, and those of data-guided real-space refinements in general. ReMDFF results scored highly on the various metric for judging the quality-of-fit and quality-of-model. However, some systematic discrepancies are also noted employing a Molprobity analysis, that are reproducible across multiple competition entries. A space of key refinement parameters is explored within ReMDFF to observe their impact within the final model. Choice of force field parameters and initial model seem to have the most significant impact on ReMDFF model-quality. To this end, very recently developed CHARMM36m force field parameters provide now more refined ReMDFF models than the ones originally submitted to the Cryo-EM challenge. Finally, a set of good-practices is prescribed for the community to benefit from the MDFF developments.

Structure of the EmrE multidrug transporter and its use for inhibitor peptide design

Small multidrug resistance (SMR) pumps represent a minimal paradigm of proton-coupled membrane transport in bacteria, yet no high-resolution structure of an SMR protein is available. Here, atomic-resolution structures of the Escherichia coli efflux-multidrug resistance E (EmrE) multidrug transporter in ligand-bound form are refined using microsecond molecular dynamics simulations biased using low-resolution data from X-ray crystallography. The structures are compatible with existing mutagenesis data as well as NMR and biochemical experiments, including pKas of the catalytic glutamate residues and the dissociation constant ([Formula: see text]) of the tetraphenylphosphonium⁺ cation. The refined structures show the arrangement of residue side chains in the EmrE active site occupied by two different ligands and in the absence of a ligand, illustrating how EmrE can adopt structurally diverse active site configurations. The structures also show a stable, well-packed binding interface between the helices H4 of the two monomers, which is believed to be crucial for EmrE dimerization. Guided by the atomic details of this interface, we design proteolysis-resistant stapled peptides that bind to helix H4 of an EmrE monomer. The peptides are expected to interfere with the dimerization and thereby inhibit drug transport. Optimal positions of the peptide staple were determined using free-energy simulations of peptide binding to monomeric EmrE Three of the four top-scoring peptides selected for experimental testing resulted in significant inhibition of proton-driven ethidium efflux in live cells without nonspecific toxicity. The approach described here is expected to be of general use for the design of peptide therapeutics.

De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge

Protein tertiary structure modeling is a critical step for the interpretation of three dimensional (3D) election microscopy density. Our group participated the 2015/2016 EM Model Challenge using the MAINMAST software for a de novo main chain modeling. The software generates local dense points using the mean shifting algorithm, and connects them into Cα models by calculating the minimum spanning tree and the longest path. Subsequently, full atom structure models are generated, which are subject to structural refinement. Here, we summarize the qualities of our submitted models and examine successful and unsuccessful models, including 3D models we did not submit to the Challenge. Our protocol using the MAINMAST software was sometimes able to build correct conformations with 3.4–5.1 Å RMSD. Unsuccessful models had failure of chain traces, however, their Cα positions and some local structures were quite correctly built. For evaluate the quality of the models, the MAINMAST software provides a confidence score for each Cα position from the consensus of top 100 scoring models.

Assigning crystallographic electron densities with free energy calculations-The case of the fluoride channel Fluc

Approximately 90% of the structures in the Protein Data Bank (PDB) were obtained by X-ray crystallography or electron microscopy. Whereas the overall quality of structure is considered high, thanks to a wide range of tools for structure validation, uncertainties may arise from density maps of small molecules, such as organic ligands, ions or water, which are non-covalently bound to the biomolecules. Even with some experience and chemical intuition, the assignment of such disconnected electron densities is often far from obvious. In this study, we suggest the use of molecular dynamics (MD) simulations and free energy calculations, which are well-established computational methods, to aid in the assignment of ambiguous disconnected electron densities. Specifically, estimates of (i) relative binding affinities, for instance between an ion and water, (ii) absolute binding free energies, i.e., free energies for transferring a solute from bulk solvent to a binding site, and (iii) stability assessments during equilibrium simulations may reveal the most plausible assignments. We illustrate this strategy using the crystal structure of the fluoride specific channel (Fluc), which contains five disconnected electron densities previously interpreted as four fluoride and one sodium ion. The simulations support the assignment of the sodium ion. In contrast, calculations of relative and absolute binding free energies as well as stability assessments during free MD simulations suggest that four of the densities represent water molecules instead of fluoride. The assignment of water is compatible with the loss of these densities in the non-conductive F82I/F85I mutant of Fluc. We critically discuss the role of the ion force fields for the calculations presented here. Overall, these findings indicate that MD simulations and free energy calculations are helpful tools for modeling water and ions into crystallographic density maps.

Cryo-EM Studies of Pre-mRNA Splicing: From Sample Preparation to Model Visualization

The removal of noncoding introns from pre-messenger RNA (pre-mRNA) is an essential step in eukaryotic gene expression and is catalyzed by a dynamic multi-megadalton ribonucleoprotein complex called the spliceosome. The spliceosome assembles on pre-mRNA substrates by the stepwise addition of small nuclear ribonucleoprotein particles and numerous protein factors. Extensive remodeling is required to form the RNA-based active site and to mediate the pre-mRNA branching and ligation reactions. In the past two years, cryo-electron microscopy (cryo-EM) structures of spliceosomes captured in different assembly and catalytic states have greatly advanced our understanding of its mechanism. This was made possible by long-standing efforts in the purification of spliceosome intermediates as well as recent developments in cryo-EM imaging and computational methodology. The resulting high-resolution densities allow for de novo model building in core regions of the complexes. In peripheral and less ordered regions, the combination of cross-linking, bioinformatics, biochemical, and genetic data is essential for accurate modeling. Here, we summarize these achievements and highlight the critical steps in obtaining near-atomic resolution structures of the spliceosome.

CHARMM-GUI 10 years for biomolecular modeling and simulation

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

Variability of Protein Structure Models from Electron Microscopy

An increasing number of biomolecular structures are solved by electron microscopy (EM). However, the quality of structure models determined from EM maps vary substantially. To understand to what extent structure models are supported by information embedded in EM maps, we used two computational structure refinement methods to examine how much structures can be refined using a dataset of 49 maps with accompanying structure models. The extent of structure modification as well as the disagreement between refinement models produced by the two computational methods scaled inversely with the global and the local map resolutions. A general quantitative estimation of deviations of structures for particular map resolutions are provided. Our results indicate that the observed discrepancy between the deposited map and the refined models is due to the lack of structural information present in EM maps and thus these annotations must be used with caution for further applications.

CHARMM-GUI MDFF/xMDFF Utilizer for Molecular Dynamics Flexible Fitting Simulations in Various Environments

X-ray crystallography and cryo-electron microscopy are two popular methods for the structure determination of biological molecules. Atomic structures are derived through the fitting and refinement of an initial model into electron density maps constructed by both experiments. Two computational approaches, MDFF and xMDFF, have been developed to facilitate this process by integrating the experimental data with molecular dynamics simulation. However, the setup of an MDFF/xMDFF simulation requires knowledge of both experimental and computational methods, which is not straightforward for nonexpert users. In addition, sometimes it is desirable to include realistic environments, such as explicit solvent and lipid bilayers during the simulation, which poses another challenge even for expert users. To alleviate these difficulties, we have developed MDFF/xMDFF Utilizer in CHARMM-GUI that helps users to set up an MDFF/xMDFF simulation. The capability of MDFF/xMDFF Utilizer is greatly enhanced by integration with other CHARMM-GUI modules, including protein structure manipulation, a diverse set of lipid types, and all-atom CHARMM and coarse-grained PACE force fields. With this integration, various simulation environments are available for MDFF Utilizer (vacuum, implicit/explicit solvent, and bilayers) and xMDFF Utilizer (vacuum and solution). In this work, three examples are shown to demonstrate the usage of MDFF/xMDFF Utilizer.

Crystal Structure and Conformational Change Mechanism of a Bacterial Nramp-Family Divalent Metal Transporter

The widely conserved natural resistance-associated macrophage protein (Nramp) family of divalent metal transporters enables manganese import in bacteria and dietary iron uptake in mammals. We determined the crystal structure of the Deinococcus radiodurans Nramp homolog (DraNramp) in an inward-facing apo state, including the complete transmembrane (TM) segment 1a (absent from a previous Nramp structure). Mapping our cysteine accessibility scanning results onto this structure, we identified the metal-permeation pathway in the alternate outward-open conformation. We investigated the functional impact of two natural anemia-causing glycine-to-arginine mutations that impaired transition metal transport in both human Nramp2 and DraNramp. The TM4 G153R mutation perturbs the closing of the outward metal-permeation pathway and alters the selectivity of the conserved metal-binding site. In contrast, the TM1a G45R mutation prevents conformational change by sterically blocking the essential movement of that helix, thus locking the transporter in an inward-facing state.

Re-evaluation of low-resolution crystal structures via interactive molecular-dynamics flexible fitting (iMDFF): a case study in complement C4

While the rapid proliferation of high-resolution structures in the Protein Data Bank provides a rich set of templates for starting models, it remains the case that a great many structures both past and present are built at least in part by hand-threading through low-resolution and/or weak electron density. With current model-building tools this task can be challenging, and the de facto standard for acceptable error rates (in the form of atomic clashes and unfavourable backbone and side-chain conformations) in structures based on data with dmax not exceeding 3.5 Å reflects this. When combined with other factors such as model bias, these residual errors can conspire to make more serious errors in the protein fold difficult or impossible to detect. The three recently published 3.6-4.2 Å resolution structures of complement C4 (PDB entries 4fxg, 4fxk and 4xam) rank in the top quartile of structures of comparable resolution both in terms of Rfree and MolProbity score, yet, as shown here, contain register errors in six β-strands. By applying a molecular-dynamics force field that explicitly models interatomic forces and hence excludes most physically impossible conformations, the recently developed interactive molecular-dynamics flexible fitting (iMDFF) approach significantly reduces the complexity of the conformational space to be searched during manual rebuilding. This substantially improves the rate of detection and correction of register errors, and allows user-guided model building in maps with a resolution lower than 3.5 Å to converge to solutions with a stereochemical quality comparable to atomic resolution structures. Here, iMDFF has been used to individually correct and re-refine these three structures to MolProbity scores of <1.7, and strategies for working with such challenging data sets are suggested. Notably, the improved model allowed the resolution for complement C4b to be extended from 4.2 to 3.5 Å as demonstrated by paired refinement.

Microscopic Characterization of Membrane Transporter Function by In Silico Modeling and Simulation

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

DOI:http://dx.doi.org/10.7554/eLife.16105.001

To understand the roles that proteins and other large molecules play inside cells, it is important to determine their structures. One of the techniques that researchers can use to do this is called cryo-electron microscopy (cryo-EM), which rapidly freezes molecules to fix them in position before imaging them in fine detail.

The cryo-EM images are like maps that show the approximate position of atoms. These images must then be processed in order to build a three-dimensional model of the protein that shows how its atoms are arranged relative to each other. One computational approach called Molecular Dynamics Flexible Fitting (MDFF) works by flexibly fitting possible atomic structures into cryo-EM maps. Although this approach works well with relatively undetailed (or ‘low resolution’) cryo-EM images, it struggles to handle the high-resolution cryo-EM maps now being generated.

Singharoy, Teo, McGreevy et al. have now developed two MDFF methods – called cascade MDFF and resolution exchange MDFF – that help to resolve atomic models of biological molecules from cryo-EM images. Each method can refine poorly guessed models into ones that are consistent with the high-resolution experimental images. The refinement is achieved by interpreting a range of images that starts with a ‘fuzzy’ image. The contrast of the image is then progressively improved until an image is produced that has a resolution that is good enough to almost distinguish individual atoms.

The method works because each cryo-EM image shows not just one, but a collection of atomic structures that the molecule can take on, with the fuzzier parts of the image representing the more flexible parts of the molecule. By taking into account this flexibility, the large-scale features of the protein structure can be determined first from the fuzzier images, and increasing the contrast of the images allows smaller-scale refinements to be made to the structure.

The MDFF tools have been designed to be easy to use and are available to researchers at low cost through cloud computing platforms. They can now be used to unravel the structure of many different proteins and protein complexes including those involved in photosynthesis, respiration and protein synthesis.

DOI:http://dx.doi.org/10.7554/eLife.16105.002

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.

Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes

The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.

Advances in the molecular dynamics flexible fitting method for cryo-EM modeling

Molecular Dynamics Flexible Fitting (MDFF) is an established technique for fitting all-atom structures of molecules into corresponding cryo-electron microscopy (cryo-EM) densities. The practical application of MDFF is simple but requires a user to be aware of and take measures against a variety of possible challenges presented by each individual case. Some of these challenges arise from the complexity of a molecular structure or the limited quality of available structural models and densities to be interpreted, while others stem from the intricacies of MDFF itself. The current article serves as an overview of the strategies that have been developed since MDFF's inception to overcome common challenges and successfully perform MDFF simulations.

Higher-Resolution Structure of the Human Insulin Receptor Ectodomain: Multi-Modal Inclusion of the Insert Domain

Insulin receptor (IR) signaling is critical to controlling nutrient uptake and metabolism. However, only a low-resolution (3.8 Å) structure currently exists for the IR ectodomain, with some segments ill-defined or unmodeled due to disorder. Here, we revise this structure using new diffraction data to 3.3 Å resolution that allow improved modeling of the N-linked glycans, the first and third fibronectin type III domains, and the insert domain. A novel haptic interactive molecular dynamics strategy was used to aid fitting to low-resolution electron density maps. The resulting model provides a foundation for investigation of structural transitions in IR upon ligand binding.

LPA1extracellular loop residues 115 and 191 are not required for receptor activation but prevent Ki16425 super-antagonism

Extracellular loop residues (R115 and D191) are not required for receptor activation but repress Ki16425-type super-antagonism but not LPA-analogue antagonists using a combination of site-directed mutagenesis and intracellular calcium assay procedures.

Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic Resolution

While conventional high-resolution techniques in structural biology are challenged by the size and flexibility of many biological assemblies, recent advances in low-resolution techniques such as cryo-electron microscopy (cryo-EM) and small angle X-ray scattering (SAXS) have opened up new avenues to define the structures of such assemblies. By systematically combining various sources of structural, biochemical and biophysical information, integrative modeling approaches aim to provide a unified structural description of such assemblies, starting from high-resolution structures of the individual components and integrating all available information from low-resolution experimental methods. In this review, we describe integrative modeling approaches, which use complementary data from either cryo-EM or SAXS. Specifically, we focus on the popular molecular dynamics flexible fitting (MDFF) method, which has been widely used for flexible fitting into cryo-EM maps. Second, we describe hybrid molecular dynamics, Rosetta Monte-Carlo and minimum ensemble search (MES) methods that can be used to incorporate SAXS into pseudoatomic structural models. We present concise descriptions of the two methods and their most popular alternatives, along with select illustrative applications to protein/nucleic acid assemblies involved in DNA replication and repair.

Macromolecular Crystallography for Synthetic Abiological Molecules: Combining xMDFF and PHENIX for Structure Determination of Cyanostar Macrocycles

Crystal structure determination has long provided insight into structure and bonding of small molecules. When those same small molecules are designed to come together in multimolecular assemblies, such as in coordination cages, supramolecular architectures and organic-based frameworks, their crystallographic characteristics closely resemble biological macromolecules. This resemblance suggests that biomacromolecular refinement approaches be used for structure determination of abiological molecular complexes that arise in an aggregate state. Following this suggestion we investigated the crystal structure of a pentagonal macrocycle, cyanostar, by means of biological structure analysis methods and compared results to traditional small molecule methods. Cyanostar presents difficulties seen in supramolecular crystallography including whole molecule disorder and highly flexible solvent molecules sitting in macrocyclic and intermolecule void spaces. We used the force-field assisted refinement method, molecular dynamics flexible fitting algorithm for X-ray crystallography (xMDFF), along with tools from the macromolecular structure determination suite PHENIX. We found that a standard implementation of PHENIX, namely one without xMDFF, either fails to produce a solution by molecular replacement alone or produces an inaccurate structure when using generic geometry restraints, even at a very high diffraction data resolution of 0.84 Å. The problems disappear when taking advantage of xMDFF, which applies an optimized force field to realign molecular models during phasing by providing accurate restraints. The structure determination for this model system shows excellent agreement with the small-molecule methods. Therefore, the joint xMDFF-PHENIX refinement protocol provides a new strategy that uses macromolecule methods for structure determination of small molecules and their assemblies.