Viral DNA polymerase structures reveal mechanisms of antiviral drug resistance.

DNA polymerases are important drug targets, and many structural studies have captured them in distinct conformations. However, a detailed understanding of the impact of polymerase conformational dynamics on drug resistance is lacking. We determined cryoelectron microscopy (cryo-EM) structures of DNA-bound herpes simplex virus polymerase holoenzyme in multiple conformations and interacting with antivirals in clinical use. These structures reveal how the catalytic subunit Pol and the processivity factor UL42 bind DNA to promote processive DNA synthesis. Unexpectedly, in the absence of an incoming nucleotide, we observed Pol in multiple conformations with the closed state sampled by the fingers domain. Drug-bound structures reveal how antivirals may selectively bind enzymes that more readily adopt the closed conformation. Molecular dynamics simulations and the cryo-EM structure of a drug-resistant mutant indicate that some resistance mutations modulate conformational dynamics rather than directly impacting drug binding, thus clarifying mechanisms that drive drug selectivity.

Activation and Desensitization Mechanism of AMPA Receptor-TARP Complex by Cryo-EM.

AMPA receptors mediate fast excitatory neurotransmission in the mammalian brain and transduce the binding of presynaptically released glutamate to the opening of a transmembrane cation channel. Within the postsynaptic density, however, AMPA receptors coassemble with transmembrane AMPA receptor regulatory proteins (TARPs), yielding a receptor complex with altered gating kinetics, pharmacology, and pore properties. Here, we elucidate structures of the GluA2-TARP γ2 complex in the presence of the partial agonist kainate or the full agonist quisqualate together with a positive allosteric modulator or with quisqualate alone. We show how TARPs sculpt the ligand-binding domain gating ring, enhancing kainate potency and diminishing the ensemble of desensitized states. TARPs encircle the receptor ion channel, stabilizing M2 helices and pore loops, illustrating how TARPs alter receptor pore properties. Structural and computational analysis suggests the full agonist and modulator complex harbors an ion-permeable channel gate, providing the first view of an activated AMPA receptor.

Velcrin-induced selective cleavage of tRNALeu(TAA) by SLFN12 causes cancer cell death.

Velcrin compounds kill cancer cells expressing high levels of phosphodiesterase 3A (PDE3A) and Schlafen family member 12 (SLFN12) by inducing complex formation between these two proteins, but the mechanism of cancer cell killing by the PDE3A-SLFN12 complex is not fully understood. Here, we report that the physiological substrate of SLFN12 RNase is tRNALeu(TAA). SLFN12 selectively digests tRNALeu(TAA), and velcrin treatment promotes the cleavage of tRNALeu(TAA) by inducing PDE3A-SLFN12 complex formation in vitro. We found that distinct sequences in the variable loop and acceptor stem of tRNALeu(TAA) are required for substrate digestion. Velcrin treatment of sensitive cells results in downregulation of tRNALeu(TAA), ribosome pausing at Leu-TTA codons and global inhibition of protein synthesis. Velcrin-induced cleavage of tRNALeu(TAA) by SLFN12 and the concomitant global inhibition of protein synthesis thus define a new mechanism of apoptosis initiation.

Computational Dissection of Membrane Transport at a Microscopic Level.

Membrane transporters are key gatekeeper proteins at cellular membranes that closely control the traffic of materials. Their function relies on structural rearrangements of varying degrees that facilitate substrate translocation across the membrane. Characterizing these functionally important molecular events at a microscopic level is key to our understanding of membrane transport, yet challenging to achieve experimentally. Recent advances in simulation technology and computing power have rendered molecular dynamics (MD) simulation a powerful biophysical tool to investigate a wide range of dynamical events spanning multiple spatial and temporal scales. Here, we review recent studies of diverse membrane transporters using computational methods, with an emphasis on highlighting the technical challenges, key lessons learned, and new opportunities to illuminate transporter structure and function.

Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

Structural basis of co-translational quality control by ArfA and RF2 bound to ribosome.

Quality control mechanisms intervene appropriately when defective translation events occur, in order to preserve the integrity of protein synthesis. Rescue of ribosomes translating on messenger RNAs that lack stop codons is one of the co-translational quality control pathways. In many bacteria, ArfA recognizes stalled ribosomes and recruits the release factor RF2, which catalyses the termination of protein synthesis. Although an induced-fit mechanism of nonstop mRNA surveillance mediated by ArfA and RF2 has been reported, the molecular interaction between ArfA and RF2 in the ribosome that is responsible for the mechanism is unknown. Here we report an electron cryo-microscopy structure of ArfA and RF2 in complex with the 70S ribosome bound to a nonstop mRNA. The structure, which is consistent with our kinetic and biochemical data, reveals the molecular interactions that enable ArfA to specifically recruit RF2, not RF1, into the ribosome and to enable RF2 to release the truncated protein product in this co-translational quality control pathway. The positively charged C-terminal domain of ArfA anchors in the mRNA entry channel of the ribosome. Furthermore, binding of ArfA and RF2 induces conformational changes in the ribosomal decoding centre that are similar to those seen in other protein-involved decoding processes. Specific interactions between residues in the N-terminal domain of ArfA and RF2 help RF2 to adopt a catalytically competent conformation for peptide release. Our findings provide a framework for understanding recognition of the translational state of the ribosome by new proteins, and expand our knowledge of the decoding potential of the ribosome.

X-ray structures define human P2X(3) receptor gating cycle and antagonist action.

P2X receptors are trimeric, non-selective cation channels activated by ATP that have important roles in the cardiovascular, neuronal and immune systems. Despite their central function in human physiology and although they are potential targets of therapeutic agents, there are no structures of human P2X receptors. The mechanisms of receptor desensitization and ion permeation, principles of antagonism, and complete structures of the pore-forming transmembrane domains of these receptors remain unclear. Here we report X-ray crystal structures of the human P2X3 receptor in apo/resting, agonist-bound/open-pore, agonist-bound/closed-pore/desensitized and antagonist-bound/closed states. The open state structure harbours an intracellular motif we term the 'cytoplasmic cap', which stabilizes the open state of the ion channel pore and creates lateral, phospholipid-lined cytoplasmic fenestrations for water and ion egress. The competitive antagonists TNP-ATP and A-317491 stabilize the apo/resting state and reveal the interactions responsible for competitive inhibition. These structures illuminate the conformational rearrangements that underlie P2X receptor gating and provide a foundation for the development of new pharmacological agents.

Protein Flexibility and Dissociation Pathway Differentiation Can Explain Onset of Resistance Mutations in Kinases.

Understanding how mutations render a drug ineffective is a problem of immense relevance. Often the mechanism through which mutations cause drug resistance can be explained purely through thermodynamics. However, the more perplexing situation is when two proteins have the same drug binding affinities but different residence times. In this work, we demonstrate how all-atom molecular dynamics simulations using recent developments grounded in statistical mechanics can provide a detailed mechanistic rationale for such variances. We discover dissociation mechanisms for the anti-cancer drug Imatinib (Gleevec) against wild-type and the N368S mutant of Abl kinase. We show how this point mutation triggers far-reaching changes in the protein's flexibility and leads to a different, much faster, drug dissociation pathway. We believe that this work marks an efficient and scalable approach to obtain mechanistic insight into resistance mutations in biomolecular receptors that are hard to explain using a structural perspective.

Charge Transfer and Chemo-Mechanical Coupling in Respiratory Complex I.

The mitochondrial respiratory chain, formed by five protein complexes, utilizes energy from catabolic processes to synthesize ATP. Complex I, the first and the largest protein complex of the chain, harvests electrons from NADH to reduce quinone, while pumping protons across the mitochondrial membrane. Detailed knowledge of the working principle of such coupled charge-transfer processes remains, however, fragmentary due to bottlenecks in understanding redox-driven conformational transitions and their interplay with the hydrated proton pathways. Complex I from Thermus thermophilus encases 16 subunits with nine iron-sulfur clusters, reduced by electrons from NADH. Here, employing the latest crystal structure of T. thermophilus complex I, we have used microsecond-scale molecular dynamics simulations to study the chemo-mechanical coupling between redox changes of the iron-sulfur clusters and conformational transitions across complex I. First, we identify the redox switches within complex I, which allosterically couple the dynamics of the quinone binding pocket to the site of NADH reduction. Second, our free-energy calculations reveal that the affinity of the quinone, specifically menaquinone, for the binding-site is higher than that of its reduced, menaquinol form-a design essential for menaquinol release. Remarkably, the barriers to diffusive menaquinone dynamics are lesser than that of the more ubiquitous ubiquinone, and the naphthoquinone headgroup of the former furnishes stronger binding interactions with the pocket, favoring menaquinone for charge transport in T. thermophilus. Our computations are consistent with experimentally validated mutations and hierarchize the key residues into three functional classes, identifying new mutation targets. Third, long-range hydrogen-bond networks connecting the quinone-binding site to the transmembrane subunits are found to be responsible for proton pumping. Put together, the simulations reveal the molecular design principles linking redox reactions to quinone turnover to proton translocation in complex I.

Flexible Fitting of Small Molecules into Electron Microscopy Maps Using Molecular Dynamics Simulations with Neural Network Potentials.

Despite significant advances in resolution, the potential for cryo-electron microscopy (EM) to be used in determining the structures of protein-drug complexes remains unrealized. Determination of accurate structures and coordination of bound ligands necessitates simultaneous fitting of the models into the density envelopes, exhaustive sampling of the ligand geometries, and, most importantly, concomitant rearrangements in the side chains to optimize the binding energy changes. In this article, we present a flexible-fitting pipeline where molecular dynamics flexible fitting (MDFF) is used to refine structures of protein-ligand complexes from 3 to 5 Å electron density data. Enhanced sampling is employed to explore the binding pocket rearrangements. To provide a model that can accurately describe the conformational dynamics of the chemically diverse set of small-molecule drugs inside MDFF, we use QM/MM and neural-network potential (NNP)/MM models of protein-ligand complexes, where the ligand is represented using the QM or NNP model, and the protein is represented using established molecular mechanical force fields (e.g., CHARMM). This pipeline offers structures commensurate to or better than recently submitted high-resolution cryo-EM or X-ray models, even when given medium to low-resolution data as input. The use of the NNPs makes the algorithm more robust to the choice of search models, offering a radius of convergence of 6.5 Å for ligand structure determination. The quality of the predicted structures was also judged by density functional theory calculations of ligand strain energy. This strain potential energy is found to systematically decrease with better fitting to density and improved ligand coordination, indicating correct binding interactions. A computationally inexpensive protocol for computing strain energy is reported as part of the model analysis protocol that monitors both the ligand fit as well as model quality.

Allosteric Interactions in Human Cytochrome P450 CYP3A4: The Role of Phenylalanine 213.

The role of Phe213 in the allosteric mechanism of human cytochrome P450 CYP3A4 was studied using a combination of progesterone (PGS) and carbamazepine (CBZ) as probe substrates. We expressed, purified, and incorporated into POPC Nanodiscs three mutants, F213A, F213S, and F213Y, and compared them with wild-type (WT) CYP3A4 by monitoring spectral titration, the rate of NADPH oxidation, and steady-state product turnover rates with pure substrates and substrate mixtures. All mutants demonstrated higher activity with CBZ, lower activity with PGS, and a reduced level of activation of CBZ epoxidation by PGS, which was most pronounced in the F213A mutant. Using all-atom molecular dynamics simulations, we compared the dynamics of WT CYP3A4 and the F213A mutant incorporated into the lipid bilayer and the effect of the presence of the PGS molecule at the allosteric peripheral site and evaluated the critical role of Phe213 in mediating the heterotropic allosteric interactions in CYP3A4.

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

Accurate structure determination from electron density maps at 3-5 Šresolution 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 ß-galactosidase at 3.2 Šand 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.

Target-driven machine learning-enabled virtual screening (TAME-VS) platform for early-stage hit identification.

High-throughput screening (HTS) methods enable the empirical evaluation of a large scale of compounds and can be augmented by virtual screening (VS) techniques to save time and money by using potential active compounds for experimental testing. Structure-based and ligand-based virtual screening approaches have been extensively studied and applied in drug discovery practice with proven outcomes in advancing candidate molecules. However, the experimental data required for VS are expensive, and hit identification in an effective and efficient manner is particularly challenging during early-stage drug discovery for novel protein targets. Herein, we present our TArget-driven Machine learning-Enabled VS (TAME-VS) platform, which leverages existing chemical databases of bioactive molecules to modularly facilitate hit finding. Our methodology enables bespoke hit identification campaigns through a user-defined protein target. The input target ID is used to perform a homology-based target expansion, followed by compound retrieval from a large compilation of molecules with experimentally validated activity. Compounds are subsequently vectorized and adopted for machine learning (ML) model training. These machine learning models are deployed to perform model-based inferential virtual screening, and compounds are nominated based on predicted activity. Our platform was retrospectively validated across ten diverse protein targets and demonstrated clear predictive power. The implemented methodology provides a flexible and efficient approach that is accessible to a wide range of users. The TAME-VS platform is publicly available at https://github.com/bymgood/Target-driven-ML-enabled-VS to facilitate early-stage hit identification.

High-resolution structures with bound Mn2+ and Cd2+ map the metal import pathway in an Nramp transporter.

Transporters of the Nramp (Natural resistance-associated macrophage protein) family import divalent transition metal ions into cells of most organisms. By supporting metal homeostasis, Nramps prevent diseases and disorders related to metal insufficiency or overload. Previous studies revealed that Nramps take on a LeuT fold and identified the metal-binding site. We present high-resolution structures of Deinococcus radiodurans (Dra)Nramp in three stable conformations of the transport cycle revealing that global conformational changes are supported by distinct coordination geometries of its physiological substrate, Mn2+, across conformations, and by conserved networks of polar residues lining the inner and outer gates. In addition, a high-resolution Cd2+-bound structure highlights differences in how Cd2+ and Mn2+ are coordinated by DraNramp. Complementary metal binding studies using isothermal titration calorimetry with a series of mutated DraNramp proteins indicate that the thermodynamic landscape for binding and transporting physiological metals like Mn2+ is different and more robust to perturbation than for transporting the toxic Cd2+ metal. Overall, the affinity measurements and high-resolution structural information on metal substrate binding provide a foundation for understanding the substrate selectivity of essential metal ion transporters like Nramps.

Revealing a Hidden Intermediate of Rotatory Catalysis with X-ray Crystallography and Molecular Simulations.

The mechanism of rotatory catalysis in ATP-hydrolyzing molecular motors remains an unresolved puzzle in biological energy transfer. Notwithstanding the wealth of available biochemical and structural information inferred from years of experiments, knowledge on how the coupling between the chemical and mechanical steps within motors enforces directional rotatory movements remains fragmentary. Even more contentious is to pinpoint the rate-limiting step of a multistep rotation process. Here, using vacuolar or V1-type hexameric ATPase as an exemplary rotational motor, we present a model of the complete 4-step conformational cycle involved in rotatory catalysis. First, using X-ray crystallography, a new intermediate or "dwell" is identified, which enables the release of an inorganic phosphate (or Pi) after ATP hydrolysis. Using molecular dynamics simulations, this new dwell is placed in a sequence with three other crystal structures to derive a putative cyclic rotation path. Free-energy simulations are employed to estimate the rate of the hexameric protein transformations and delineate allosteric effects that allow new reactant ATP entry only after hydrolysis product exit. An analysis of transfer entropy brings to light how the side-chain-level interactions transcend into larger-scale reorganizations, highlighting the role of the ubiquitous arginine-finger residues in coupling chemical and mechanical information. An inspection of all known rates encompassing the 4-step rotation mechanism implicates the overcoming of the ADP interactions with V1-ATPase to be the rate-limiting step of motor action.

An Iterative Approach Guides Discovery of the FabI Inhibitor Fabimycin, a Late-Stage Antibiotic Candidate with In Vivo Efficacy against Drug-Resistant Gram-Negative Infections.

Genomic studies and experiments with permeability-deficient strains have revealed a variety of biological targets that can be engaged to kill Gram-negative bacteria. However, the formidable outer membrane and promiscuous efflux pumps of these pathogens prevent many candidate antibiotics from reaching these targets. One such promising target is the enzyme FabI, which catalyzes the rate-determining step in bacterial fatty acid biosynthesis. Notably, FabI inhibitors have advanced to clinical trials for Staphylococcus aureus infections but not for infections caused by Gram-negative bacteria. Here, we synthesize a suite of FabI inhibitors whose structures fit permeation rules for Gram-negative bacteria and leverage activity against a challenging panel of Gram-negative clinical isolates as a filter for advancement. The compound to emerge, called fabimycin, has impressive activity against >200 clinical isolates of Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii, and does not kill commensal bacteria. X-ray structures of fabimycin in complex with FabI provide molecular insights into the inhibition. Fabimycin demonstrates activity in multiple mouse models of infection caused by Gram-negative bacteria, including a challenging urinary tract infection model. Fabimycin has translational promise, and its discovery provides additional evidence that antibiotics can be systematically modified to accumulate in Gram-negative bacteria and kill these problematic pathogens.

Correction to "An Iterative Approach Guides Discovery of the FabI Inhibitor Fabimycin, a Late-Stage Antibiotic Candidate with In Vivo Efficacy against Drug-Resistant Gram-Negative Infections".

[This corrects the article DOI: 10.1021/acscentsci.2c00598.].

Poor Person's pH Simulation of Membrane Proteins.

pH conditions are central to the functioning of all biomolecules. However, implications of pH changes are nontrivial on a molecular scale. Though a rigorous microscopic definition of pH exists, its implementation in classical molecular dynamics (MD) simulations is cumbersome, and more so in large integral membrane systems. In this chapter, an integrative pipeline is described that combines Multi-Conformation Continuum Electrostatics (MCCE) computations with MD simulations to capture the effect of transient protonation states on the coupled conformational changes in transmembrane proteins. The core methodologies are explained, and all the software required to set up this pipeline are outlined with their key parameters. All associated analyses of structure and function are provided using two case studies, namely those of bioenergetic complexes: NADH dehydrogenase (complex I) and Vo domain of V-type ATPase. The hybrid MCCE-MD pipeline has allowed the discovery of hydrogen bond networks, ligand binding pathways, and disease-causing mutations.

CryoFold: determining protein structures and data-guided ensembles from cryo-EM density maps.

Cryo-electron microscopy (EM) requires molecular modeling to refine structural details from data. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins that cannot be resolved by cryo-EM. Here, we introduce CryoFold - a pipeline of molecular dynamics simulations that determines ensembles of protein structures directly from sequence by integrating density data of varying sparsity at 3-5 Å resolution with coarse-grained topological knowledge of the protein folds. We present six examples showing its broad applicability for folding proteins between 72 to 2000 residues, including large membrane and multi-domain systems, and results from two EMDB competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations, unseen by traditional methods, are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python GUI.