The active site's electric field is integral to enzymatic catalysis (e.g., substrate recognition), and nature employs charge-altering post-translational modifications (e.g., phosphorylation) to perturb this electric field and regulate enzymes. A chromosomal translocation converts Abelson kinase (ABL) to BCR-ABL, the hyperactivity of which drives several cancers. Here, we developed a small molecule, BRD8833, that induces BCR-ABL phosphorylation, which perturbs its active site's electric field with loss of hyperactivity. Unlike "occupancy-driven" inhibitors that require stoichiometric concentrations, BRD8833 operates through an event-driven, substoichiometric mechanism by inducing the proximity between two BCR-ABL molecules to trigger the inhibitory phosphorylation and selective apoptosis of BCR-ABL-dependent cancer cells. Furthermore, BRD8833 is effective against other oncogenic ABL fusions or clinically observed resistance mutations, including those to occupancy-driven drugs with the same binding site as BRD8833, suggesting differences in their resistance mechanisms. These studies lay the foundation for electric-field and "event-driven" modalities to control hyperactive enzymes with orthogonal resistance mechanisms to occupancy-driven drugs.

Virtual screening for small-molecule binders is often limited by false positives from approximate scoring functions and rigid-receptor assumptions. These can be addressed downstream through accurate but expensive free energy calculations. At the same time, recent artificialintelligence-based co-folding methods have been proposed that claim to achieve accuracy of free energy methods at much lower cost, but these have not yet delivered consistent improvements in early enrichment and can be confounded by memorization. Here we address this gap by introducing c(t)-based metadynamics (CTMD), a physics-based, high-throughput hit-triaging protocol tailored for early enrichment. CTMD uses the nonequilibrium reversible-work estimator c(t) introduced by Tiwary and Parrinello (Journal of Physical Chemistry B, 2015 119 736), computed from a small number of short, independent well-tempered metadynamics trajectories, to rank binding stability without requiring converged binding free energies. Across diverse targets and chemotypes, CTMD provides robust early enrichment while remaining fast, transferable with minimal parameter tuning, and resistant to memorization-driven artifacts-underscoring both an immediately deployable physics-based alternative for screening. For these systems we show how co-folding, particularly Boltz-2, achieves enrichment directly proportional to similairty with training set, and more worrying, even in the presence of signficant modifications to active site. Given its simplicity of implementation, CTMD should thus be an "embarassingly" open-source, early enrichment method available for use by the broad pharma and academic community that sits right between approximate but fast docking or AI based co-folding methods, and more expensive but accurate free energy calculations, expected to lead to saving significant financial and human capital in drug discovery campaigns.

Herpesviruses are widespread double-stranded DNA viruses that establish lifelong latency and cause various diseases. Although DNA polymerase-targeting antivirals are effective, increasing drug resistance underscores the need for alternatives. Helicase-primase inhibitors (HPIs) are promising antivirals, but their mechanisms of action are poorly defined. Furthermore, how the helicase-primase (H/P) complex and DNA polymerase coordinate genome replication is not well understood for herpesviruses. Here, we report cryo-EM structures of the herpes simplex virus (HSV) H/P complex bound to HPIs, showing that these lock the helicase-primase complex in an inactive conformation. Single-molecule assays reveal that HPIs cause helicase-primase complexes to pause in unwinding activity on DNA. The structure of an HPI-bound replication fork complex, comprising the H/P complex (UL5, UL52, and UL8) and polymerase holoenzyme (UL30 and UL42), reveals a previously uncharacterized interface bridging these complexes. These findings provide a structural framework for understanding herpesvirus replisome assembly and advancing inhibitor development.

Herpesviruses are widespread double-stranded DNA viruses that establish lifelong latency and cause various diseases. Although DNA-polymerase-targeting antivirals are effective, increasing drug resistance underscores the need for alternatives. Helicase-primase inhibitors (HPIs) are promising antivirals, but their mechanisms of action are poorly defined. Furthermore, how the helicase-primase (H/P) complex and DNA polymerase coordinate genome replication is not well understood for herpesviruses. Here, we report cryo-electron microscopy (cryo-EM) structures of the herpes simplex virus 1 H/P complex bound to HPIs, showing that these lock the H/P complex in an inactive state. Single-molecule assays reveal that HPIs cause H/P complexes to pause in unwinding activity on DNA. The structure of an HPI-bound replication fork complex, comprising the H/P complex (UL5, UL52, and UL8) and the polymerase holoenzyme (UL30 and UL42), reveals a previously uncharacterized interface bridging these complexes. These findings provide a structural framework for understanding herpesvirus replisome assembly and advancing inhibitor development.

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.

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

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 userdefined protein target. The input target ID is used to perform a homologybased 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 modelbased 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.

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.

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 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 Nramp in three stable conformations of the transport cycle revealing that global conformational changes are supported by distinct coordination geometries of its physiological substrate, Mn 2+ , across conformations and conserved networks of polar residues lining the inner and outer gates. A Cd 2+ -bound structure highlights differences in coordination geometry for Mn 2+ and Cd 2+ . Measurements of metal binding using isothermal titration calorimetry indicate that the thermodynamic landscape for binding and transporting physiological metals like Mn 2+ is different and more robust to perturbation than for transporting the toxic Cd 2+ metal.

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.

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.

Abstract CSNK1A1 is a serine/threonine kinase involved in multiple cellular processes, including cell division, beta catenin signaling, and TP53 activation. Inhibition of CSNK1A1 has previously been validated as a therapeutic strategy in hematologic malignancy, and degradation of CSNK1A1 protein is the downstream mechanism of action for lenalidomide in 5q- myelodysplasia (Krönke, et al. Nature. 2015.). However, lenalidomide is inactive in most solid tumor models, thus limiting the study of CSNK1A1 inhibition in other contexts. Analysis of genetic loss-of-function data from the Cancer Dependency Map reveals multiple sensitive models, including lineage-specific enrichment in colorectal and gastric cancer. In an academic-industry collaboration, we a) developed first-in-class potent and selective ATP-competitive CSNK1A1 small molecule inhibitors with preclinical anti-cancer efficacy in vivo, and b) identified FAM83 expression as a key determinant of inhibitor sensitivity. We identified a tetrahydro-pyrrolopyridinone scaffold that was subsequently optimized to yield BAY-888 (CSNK1A1 IC50 4 nM @ 10 μM ATP; 63 nM @ 1 mM ATP) and BAY-204 (CSNK1A1 IC50 2 nM @ 10 μM ATP; 12 nM @ 1 mM ATP). The crystal structure of CSNK1A1 in complex with BAY-888 confirmed compound binding in the ATP binding pocket. Across the PRISM barcoded cell line panel of more than 500 solid tumor cell lines, inhibitors phenocopy the CSNK1A1 shRNA knockdown profile. To determine downstream mediators of CSNK1A1 inhibitor sensitivity, we performed co-IP mass spectrometry following CSNK1A1 pulldown and global phosphoproteomic assays following inhibitor treatment. We identified multiple interacting proteins that are also phosphorylation targets, including FAM83 family members. FAM83 was recently reported to mediate the subcellular localization of CSNK1A1 (Fulcher, et al. Sci Signal. 2018.). Excitingly, the baseline expression of FAM83B and FAM83H correlates with inhibitor and shRNA cell line sensitivity. Modulation of FAM83H expression altered CSNK1A1 localization and sensitivity to CSNK1A1 inhibition. BAY-888 and BAY-204 are orally bioavailable and were evaluated in multiple murine cell line xenograft models. We observed promising efficacy in DLBCL (TMD8) in vivo as well as in multiple FAM83-high solid tumor models, including colorectal (HCT116 and HT29), gastric (IM95), and urothelial cancer (KU19-19). We identified RPS6 phosphorylation as one of the PD biomarkers correlating with efficacy in vivo. In summary, CSNK1A1 is a promising target with anti-tumor efficacy and achievable therapeutic index in preclinical models of FAM83-high solid tumors. Citation Format: Steven M. Corsello, Huajia Zhang, Rajesha Rupaimoole, Volker K. Schulze, Clara Lemos, Kasia B. Handing, Douglas L. Orsi, Mrinal Shekhar, Ulrike Sack, Sven Christian, Wilhelm Bone, Ranad Humeidi, William Colgan, Stephanie Hoyt, Andrew Cherniack, Jens Schroder, Stefan Kaulfuss, Krzysztof Brzezinka, Oliver von Ahsen, Anne Mengel, Roman C. Hillig, Detlev Suelzle, Jeremie Mortier, Caitlin Harrington, Rohith Nagari, Justyna Wierzbinska, Derek Chiang, Georg Beckmann, Meagan Olive, Namrata Udeshi, Annie Apffel, Steven Carr, Philip Lienau, Christian Lechner, Ulf Boemer, Alisha Caliman, David McKinney, Florence Wagner, Dominik Mumberg, Marcus Bauser, Andrea Haegebarth, Knut Eis, Ashley Eheim, Todd R. Golub. Discovery of potent and selective CSNK1A1 inhibitors for solid tumor therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3588.

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 tRNA(Leu)(TAA). SLFN12 selectively digests tRNA(Leu)(TAA), and velcrin treatment promotes the cleavage oftRNA(Leu)(TAA) by inducing PDE3A-SLFN12 complex formation in vitro. We found that distinct sequences in the variable loop and acceptor stem oftRNA(Leu)(TAA) are required for substrate digestion. Velcrin treatment of sensitive cells results in downregulation of tRNA(Leu)(TAA), ribosome pausing at Leu-TTA codons and global inhibition of protein synthesis. Velcrin-induced cleavage of tRNA(Leu)(TAA) by SLFN12 and the concomitant global inhibition of protein synthesis thus define a new mechanism of apoptosis initiation.

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.

Cryo-EM is a powerful method for determining protein structures. But it requires computational assistance. Physics-based computations have the power to give low-free-energy structures and ensembles of populations, but have been computationally limited to only small soluble proteins. Here, we introduce CryoFold. By integrating data of varying sparsity from electron density maps of 3–5 Å resolution with coarse-grained physical knowledge of secondary and tertiary interactions, CryoFold determines ensembles of protein structures directly from sequence. We give six examples showing its broad capabilities, over proteins ranging from 72 to 2000 residues, including membrane and multi-domain proteins, and including results from two EMDB competitions. The ensembles CryoFold predicts starting from the density data of a single known protein conformation encompass multiple low-energy conformations, all of which are experimentally validated and biologically relevant.

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.

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.

We present a new approach to determining the conformational changes associated with biological function, and demonstrate its capabilities in the context of experimental single-particle cryo-EM snapshots of ryanodine receptor (RyR1), a Ca2+-channel involved in skeletal muscle excitation/contraction coupling. These results include the detailed conformational motions associated with functional paths including transitions between energy landscapes. The functional motions differ substantially from those inferred from discrete structures, shedding new light on the gating mechanism in RyR1. The differences include the conformationally active structural domains, the nature, sequence, and extent of conformational motions involved in function, and the way allosteric signals are transduced within and between domains. The approach is general, and applicable to a wide range of systems and processes.