Kainate receptor channel opening and gating mechanism.

Kainate receptors, a subclass of ionotropic glutamate receptors, are tetrameric ligand-gated ion channels that mediate excitatory neurotransmission1-4. Kainate receptors modulate neuronal circuits and synaptic plasticity during the development and function of the central nervous system and are implicated in various neurological and psychiatric diseases, including epilepsy, depression, schizophrenia, anxiety and autism5-11. Although structures of kainate receptor domains and subunit assemblies are available12-18, the mechanism of kainate receptor gating remains poorly understood. Here we present cryo-electron microscopy structures of the kainate receptor GluK2 in the presence of the agonist glutamate and the positive allosteric modulators lectin concanavalin A and BPAM344. Concanavalin A and BPAM344 inhibit kainate receptor desensitization and prolong activation by acting as a spacer between the amino-terminal and ligand-binding domains and a stabilizer of the ligand-binding domain dimer interface, respectively. Channel opening involves the kinking of all four pore-forming M3 helices. Our structures reveal the molecular basis of kainate receptor gating, which could guide the development of drugs for treatment of neurological disorders.

Opening of glutamate receptor channel to subconductance levels.

Ionotropic glutamate receptors (iGluRs) are tetrameric ligand-gated ion channels that open their pores in response to binding of the agonist glutamate1-3. An ionic current through a single iGluR channel shows up to four discrete conductance levels (O1-O4)4-6. Higher conductance levels have been associated with an increased number of agonist molecules bound to four individual ligand-binding domains (LBDs)6-10. Here we determine structures of a synaptic complex of AMPA-subtype iGluR and the auxiliary subunit γ2 in non-desensitizing conditions with various occupancy of the LBDs by glutamate. We show that glutamate binds to LBDs of subunits B and D only after it is already bound to at least the same number of LBDs that belong to subunits A and C. Our structures combined with single-channel recordings, molecular dynamics simulations and machine-learning analysis suggest that channel opening requires agonist binding to at least two LBDs. Conversely, agonist binding to all four LBDs does not guarantee maximal channel conductance and favours subconductance states O1 and O2, with O3 and O4 being rare and not captured structurally. The lack of subunit independence and low efficiency coupling of glutamate binding to channel opening underlie the gating of synaptic complexes to submaximal conductance levels, which provide a potential for upregulation of synaptic activity.

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions.

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling.

In silico identification of potent protein inhibitors commonly requires prediction of a ligand binding free energy (BFE). Thermodynamics integration (TI) based on molecular dynamics (MD) simulations is a BFE calculation method capable of acquiring accurate BFE, but it is computationally expensive and time-consuming. In this work, we have developed an efficient automated workflow for identifying compounds with the lowest BFE among thousands of congeneric ligands, which requires only hundreds of TI calculations. Automated machine learning (AutoML) orchestrated by active learning (AL) in an AL-AutoML workflow allows unbiased and efficient search for a small set of best-performing molecules. We have applied this workflow to select inhibitors of the SARS-CoV-2 papain-like protease and were able to find 133 compounds with improved binding affinity, including 16 compounds with better than 100-fold binding affinity improvement. We obtained a hit rate that outperforms that expected of traditional expert medicinal chemist-guided campaigns. Thus, we demonstrate that the combination of AL and AutoML with free energy simulations provides at least 20× speedup relative to the naïve brute force approaches.

Structural mechanism of TRPM7 channel regulation by intracellular magnesium.

Zn2+, Mg2+ and Ca2+ are essential divalent cations implicated in many metabolic processes and signalling pathways. An emerging new paradigm is that the organismal balance of these cations predominantly depends on a common gatekeeper, the channel-kinase TRPM7. Despite extensive electrophysiological studies and recent cryo-EM analysis, an open question is how the channel activity of TRPM7 is activated. Here, we performed site-directed mutagenesis of mouse TRPM7 in conjunction with patch-clamp assessment of whole-cell and single-channel activity and molecular dynamics (MD) simulations to show that the side chains of conserved N1097 form an inter-subunit Mg2+ regulatory site located in the lower channel gate of TRPM7. Our results suggest that intracellular Mg2+ binds to this site and stabilizes the TRPM7 channel in the closed state, whereas the removal of Mg2+ favours the opening of TRPM7. Hence, our study identifies the structural underpinnings through which the TRPM7 channel is controlled by cytosolic Mg2+, representing a new structure-function relationship not yet explored among TRPM channels.

Structure and function of the calcium-selective TRP channel TRPV6.

Epithelial calcium channel TRPV6 is a member of the vanilloid subfamily of TRP channels that is permeable to cations and highly selective to Ca2+ ; it shows constitutive activity regulated negatively by Ca2+ and positively by phosphoinositol and cholesterol lipids. In this review, we describe the molecular structure of TRPV6 and discuss how its structural elements define its unique functional properties. High Ca2+ selectivity of TRPV6 originates from the narrow selectivity filter, where Ca2+ ions are directly coordinated by a ring of anionic aspartate side chains. Divalent cations Ca2+ and Ba2+ permeate TRPV6 pore according to the knock-off mechanism, while tight binding of Gd3+ to the aspartate ring blocks the channel and prevents Na+ from permeating the pore. The iris-like channel opening is accompanied by an α-to-π helical transition in the pore-lining transmembrane helix S6. As a result of this transition, the intracellular halves of the S6 helices bend and rotate by about 100 deg, exposing different residues to the channel pore in the open and closed states. Channel opening is also associated with changes in occupancy of the transmembrane domain lipid binding sites. The inhibitor 2-aminoethoxydiphenyl borate (2-APB) binds to TRPV6 in a pocket formed by the cytoplasmic half of the S1-S4 transmembrane helical bundle and shifts open-closed channel equilibrium towards the closed state by outcompeting lipids critical for activation. Ca2+ inhibits TRPV6 via binding to calmodulin (CaM), which mediates Ca2+ -dependent inactivation. The TRPV6-CaM complex exhibits 1:1 stoichiometry; one TRPV6 tetramer binds both CaM lobes, which adopt a distinct head-to-tail arrangement. The CaM C-terminal lobe plugs the channel through a unique cation-π interaction by inserting the side chain of lysine K115 into a tetra-tryptophan cage at the ion channel pore intracellular entrance. Recent studies of TRPV6 structure and function described in this review advance our understanding of the role of this channel in physiology and pathophysiology and inform new therapeutic design.

Epoxidation Catalyzed by the Nonheme Iron(II)- and 2-Oxoglutarate-Dependent Oxygenase, AsqJ: Mechanistic Elucidation of Oxygen Atom Transfer by a Ferryl Intermediate.

Mechanisms of enzymatic epoxidation via oxygen atom transfer (OAT) to an olefin moiety is mainly derived from the studies on thiolate-heme containing epoxidases, such as cytochrome P450 epoxidases. The molecular basis of epoxidation catalyzed by nonheme-iron enzymes is much less explored. Herein, we present a detailed study on epoxidation catalyzed by the nonheme iron(II)- and 2-oxoglutarate-dependent (Fe/2OG) oxygenase, AsqJ. The native substrate and analogues with different para substituents ranging from electron-donating groups (e.g., methoxy) to electron-withdrawing groups (e.g., trifluoromethyl) were used to probe the mechanism. The results derived from transient-state enzyme kinetics, Mössbauer spectroscopy, reaction product analysis, X-ray crystallography, density functional theory calculations, and molecular dynamic simulations collectively revealed the following mechanistic insights: (1) The rapid O2 addition to the AsqJ Fe(II) center occurs with the iron-bound 2OG adopting an online-binding mode in which the C1 carboxylate group of 2OG is trans to the proximal histidine (His134) of the 2-His-1-carboxylate facial triad, instead of assuming the offline-binding mode with the C1 carboxylate group trans to the distal histidine (His211); (2) The decay rate constant of the ferryl intermediate is not strongly affected by the nature of the para substituents of the substrate during the OAT step, a reactivity behavior that is drastically different from nonheme Fe(IV)-oxo synthetic model complexes; (3) The OAT step most likely proceeds through a stepwise process with the initial formation of a C(benzylic)-O bond to generate an Fe-alkoxide species, which is observed in the AsqJ crystal structure. The subsequent C3-O bond formation completes the epoxide installation.

Membrane Position Dependency of the pKa and Conductivity of the Protein Ion Channel.

The dependency of current-voltage characteristics of the α-hemolysin channel on the channel position within the membrane was studied using Poisson-Nernst-Planck theory of ion conductivity with soft repulsion between mobile ions and protein atoms (SP-PNP). The presence of the membrane environment also influences the protonation state of the residues at the boundary of the water-lipid interface. In this work, we predict that Asp and Lys residues at the protein rim change their protonation state upon penetration to the lipid environment. Free energies of protein insertion in the membrane for different penetration depths were estimated using the Poisson-Boltzmann/solvent-accessible surface area (PB/SASA) model. The results show that rectification and reversal potentials are very sensitive to the relative position of channel in the membrane, which in turn contributes to alternative protonation states of lipid-penetrating ionizable groups. The prediction of channel position based on the matching of calculated rectification with experimentally determined rectification is in good agreement with recent neutron reflection experiments. Based on the results, we conclude that α-hemolysin membrane position is determined by a combination of factors and not only by the pattern of the surface hydrophobicity as is typically assumed.

Configurational Preference of the Glutamate Receptor Ligand Binding Domain Dimers.

Ionotropic glutamate receptors are a family of tetrameric ion channels with functional states consisting of nonconducting, conducting, and desensitized states that are starting to become well characterized by electrophysiological and biophysical studies. However, the structure and relative energetics of these states beyond the general structure of the receptor are still not well understood. It is known that the interface between monomeric subunits of the tetramer plays a major role in distinguishing these functional states. We have used umbrella sampling and multimicrosecond molecular dynamics simulations of the GluA2 AMPA subtype glutamate receptor ligand-binding domain (LBD) dimers to characterize a natural propensity of the LBD dimers for various configurational states. Our results show a proposed desensitized conformation of the LBD dimer is a highly preferable conformation of the LBD dimer without the influence of other receptor domains or crystallographic conditions. This has been demonstrated by both free protein simulations of 5 µs duration, as well as by computed free energy difference between the active and desensitized states. At the same time, the simulations performed using the same protocols revealed that for the LBD mutant L483Y, known to lack desensitization, the postulated active state of the LBD dimer is indeed the preferred configurational state, which remained stable in the simulations. Our findings pave the path for developing more detailed hypotheses of the full receptor activation mechanism. Combined with the energetics of glutamate binding to the LBD and the energy required to open the transmembrane pore helices, our results strongly support a hypothesis that the low absolute free-energy state is the desensitized state of the intact AMPA receptor.

Stability and rigidity/flexibility-two sides of the same coin?

Protein molecules require both flexibility and rigidity for functioning. The fast and accurate prediction of protein rigidity/flexibility is one of the important problems in protein science. We have determined flexible regions for four homologous pairs from thermophilic and mesophilic organisms by two methods: the fast FoldUnfold which uses amino acid sequence and the time consuming MDFirst which uses three-dimensional structures. We demonstrate that both methods allow determining flexible regions in protein structure. For three of the four thermophile-mesophile pairs of proteins, FoldUnfold predicts practically the same flexible regions which have been found by the MD/First method. As expected, molecular dynamics simulations show that thermophilic proteins are more rigid in comparison to their mesophilic homologues. Analysis of rigid clusters and their decomposition provides new insights into protein stability. It has been found that the local networks of salt bridges and hydrogen bonds in thermophiles render their structure more stable with respect to fluctuations of individual contacts. Such network includes salt bridge triads Agr-Glu-Lys and Arg-Glu-Arg, or salt bridges (such as Arg-Glu) connected with hydrogen bonds. This ionic network connects alpha helices and rigidifies the structure. Mesophiles can be characterized by stand alone salt bridges and hydrogen bonds or small ionic clusters. Such difference in the network of salt bridges results in different flexibility of homologous proteins. Combining both approaches allows characterizing structural features in atomic detail that determine the rigidity/flexibility of a protein structure. This article is a part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.

Structural basis of selective TRPM7 inhibition by the anticancer agent CCT128930.

TRP channels are implicated in various diseases, but high structural similarity between them makes selective pharmacological modulation challenging. Here, we study the molecular mechanism underlying specific inhibition of the TRPM7 channel, which is essential for cancer cell proliferation, by the anticancer agent CCT128930 (CCT). Using cryo-EM, functional analysis, and MD simulations, we show that CCT binds to a vanilloid-like (VL) site, stabilizing TRPM7 in the closed non-conducting state. Similar to other allosteric inhibitors of TRPM7, NS8593 and VER155008, binding of CCT is accompanied by displacement of a lipid that resides in the VL site in the apo condition. Moreover, we demonstrate the principal role of several residues in the VL site enabling CCT to inhibit TRPM7 without impacting the homologous TRPM6 channel. Hence, our results uncover the central role of the VL site for the selective interaction of TRPM7 with small molecules that can be explored in future drug design.

In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations.

The Critical Assessment of Computational Hit-Finding Experiments (CACHE) Challenge series is focused on identifying small molecule inhibitors of protein targets using computational methods. Each challenge contains two phases, hit-finding and follow-up optimization, each of which is followed by experimental validation of the computational predictions. For the CACHE Challenge #1, the Leucine-Rich Repeat Kinase 2 (LRRK2) WD40 Repeat (WDR) domain was selected as the target for in silico hit-finding and optimization. Mutations in LRRK2 are the most common genetic cause of the familial form of Parkinson's disease. The LRRK2 WDR domain is an understudied drug target with no known molecular inhibitors. Herein we detail the first phase of our winning submission to the CACHE Challenge #1. We developed a framework for the high-throughput structure-based virtual screening of a chemically diverse small molecule space. Hit identification was performed using the large-scale Deep Docking (DD) protocol followed by absolute binding free energy (ABFE) simulations. ABFEs were computed using an automated molecular dynamics (MD)-based thermodynamic integration (TI) approach. 4.1 billion ligands from Enamine REAL were screened with DD followed by ABFEs computed by MD TI for 793 ligands. 76 ligands were prioritized for experimental validation, with 59 compounds successfully synthesized and 5 compounds identified as hits, yielding a 8.5% hit rate. Our results demonstrate the efficacy of the combined DD and ABFE approaches for hit identification for a target with no previously known hits. This approach is widely applicable for the efficient screening of ultra-large chemical libraries as well as rigorous protein-ligand binding affinity estimation leveraging modern computational resources.

Spectroscopic and computational studies of a bifunctional iron- and 2-oxoglutarate dependent enzyme, AsqJ.

Iron and 2-oxoglutarate dependent (Fe/2OG) enzymes exhibit an exceedingly broad reaction repertoire. The most prevalent reactivity is hydroxylation, but many other reactivities have also been discovered in recent years, including halogenation, desaturation, epoxidation, endoperoxidation, epimerization, and cyclization. To fully explore the reaction mechanisms that support such a diverse reactivities in Fe/2OG enzyme, it is necessary to utilize a multi-faceted research methodology, consisting of molecular probe design and synthesis, in vitro enzyme assay development, enzyme kinetics, spectroscopy, protein crystallography, and theoretical calculations. By using such a multi-faceted research approach, we have explored reaction mechanisms of desaturation and epoxidation catalyzed by a bi-functional Fe/2OG enzyme, AsqJ. Herein, we describe the experimental protocols and computational workflows used in our studies.

A community effort in SARS-CoV-2 drug discovery.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.

Structural mechanisms of TRPM7 activation and inhibition.

The transient receptor potential channel TRPM7 is a master regulator of the organismal balance of divalent cations that plays an essential role in embryonic development, immune responses, cell mobility, proliferation, and differentiation. TRPM7 is implicated in neuronal and cardiovascular disorders, tumor progression and has emerged as a new drug target. Here we use cryo-EM, functional analysis, and molecular dynamics simulations to uncover two distinct structural mechanisms of TRPM7 activation by a gain-of-function mutation and by the agonist naltriben, which show different conformational dynamics and domain involvement. We identify a binding site for highly potent and selective inhibitors and show that they act by stabilizing the TRPM7 closed state. The discovered structural mechanisms provide foundations for understanding the molecular basis of TRPM7 channelopathies and drug development.

Structural basis of AMPA receptor inhibition by trans-4-butylcyclohexane carboxylic acid.

BACKGROUND AND PURPOSE: AMPA receptors, which shape excitatory postsynaptic currents and are directly involved in overactivation of synaptic function during seizures, represent a well-accepted target for anti-epileptic drugs. Trans-4-butylcyclohexane carboxylic acid (4-BCCA) has emerged as a new promising anti-epileptic drug in several in vitro and in vivo seizure models, but the mechanism of its action remained unknown. The purpose of this study is to characterize structure and dynamics of 4-BCCA interaction with AMPA receptors. EXPERIMENTAL APPROACH: We studied the molecular mechanism of AMPA receptor inhibition by 4-BCCA using a combination of X-ray crystallography, mutagenesis, electrophysiological assays, and molecular dynamics simulations. KEY RESULTS: We identified 4-BCCA binding sites in the transmembrane domain (TMD) of AMPA receptor, at the lateral portals formed by transmembrane segments M1-M4. At this binding site, 4-BCCA is very dynamic, assumes multiple poses, and can enter the ion channel pore. CONCLUSION AND IMPLICATIONS: 4-BCCA represents a low-affinity inhibitor of AMPA receptors that acts at the TMD sites distinct from non-competitive inhibitors, such as the anti-epileptic drug perampanel and the ion channel blockers. Further studies might examine the possibsility of synergistic use of these inhibitors in treatment of epilepsy and a wide range of neurological disorders and gliomas. LINKED ARTICLES: This article is part of a themed issue on Structure Guided Pharmacology of Membrane Proteins (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.14/issuetoc.

Inhibition of NMDA receptors through a membrane-to-channel path.

N-methyl-D-aspartate receptors (NMDARs) are transmembrane proteins that are activated by the neurotransmitter glutamate and are found at most excitatory vertebrate synapses. NMDAR channel blockers, an antagonist class of broad pharmacological and clinical significance, inhibit by occluding the NMDAR ion channel. A vast literature demonstrates that NMDAR channel blockers, including MK-801, phencyclidine, ketamine, and the Alzheimer's disease drug memantine, can bind and unbind only when the NMDAR channel is open. Here we use electrophysiological recordings from transfected tsA201 cells and cultured neurons, NMDAR structural modeling, and custom-synthesized compounds to show that NMDAR channel blockers can enter the channel through two routes: the well-known hydrophilic path from extracellular solution to channel through the open channel gate, and also a hydrophobic path from plasma membrane to channel through a gated fenestration ("membrane-to-channel inhibition" (MCI)). Our demonstration that ligand-gated channels are subject to MCI, as are voltage-gated channels, highlights the broad expression of this inhibitory mechanism.

Design, synthesis, and in vitro and in vivo characterization of new memantine analogs for Alzheimer's disease.

Currently, of the few accessible symptomatic therapies for Alzheimer's disease (AD), memantine is the only N-methyl-d-aspartate receptor (NMDAR) blocker approved by the FDA. This work further explores a series of memantine analogs featuring a benzohomoadamantane scaffold. Most of the newly synthesized compounds block NMDARs in the micromolar range, but with lower potency than previously reported hit IIc, results that were supported by molecular dynamics simulations. Subsequently, electrophysiological studies with the more potent compounds allowed classification of IIc, a low micromolar, uncompetitive, voltage-dependent, NMDAR blocker, as a memantine-like compound. The excellent in vitro DMPK properties of IIc made it a promising candidate for in vivo studies in Caenorhabditis elegans (C. elegans) and in the 5XFAD mouse model of AD. Administration of IIc or memantine improved locomotion and rescues chemotaxis behavior in C. elegans. Furthermore, both compounds enhanced working memory in 5XFAD mice and modified NMDAR and CREB signaling, which may prevent synaptic dysfunction and modulate neurodegenerative progression.

Protein-Ligand Binding Free-Energy Calculations with ARROW─A Purely First-Principles Parameterized Polarizable Force Field.

Protein-ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)─a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein-ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ∼0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

Accurate determination of solvation free energies of neutral organic compounds from first principles.

The main goal of molecular simulation is to accurately predict experimental observables of molecular systems. Another long-standing goal is to devise models for arbitrary neutral organic molecules with little or no reliance on experimental data. While separately these goals have been met to various degrees, for an arbitrary system of molecules they have not been achieved simultaneously. For biophysical ensembles that exist at room temperature and pressure, and where the entropic contributions are on par with interaction strengths, it is the free energies that are both most important and most difficult to predict. We compute the free energies of solvation for a diverse set of neutral organic compounds using a polarizable force field fitted entirely to ab initio calculations. The mean absolute errors (MAE) of hydration, cyclohexane solvation, and corresponding partition coefficients are 0.2 kcal/mol, 0.3 kcal/mol and 0.22 log units, i.e. within chemical accuracy. The model (ARROW FF) is multipolar, polarizable, and its accompanying simulation stack includes nuclear quantum effects (NQE). The simulation tools' computational efficiency is on a par with current state-of-the-art packages. The construction of a wide-coverage molecular modelling toolset from first principles, together with its excellent predictive ability in the liquid phase is a major advance in biomolecular simulation.