The Art and Science of Molecular Docking.

Molecular docking has become an essential part of a structural biologist's and medicinal chemist's toolkits. Given a chemical compound and the three-dimensional structure of a molecular target-for example, a protein-docking methods fit the compound into the target, predicting the compound's bound structure and binding energy. Docking can be used to discover novel ligands for a target by screening large virtual compound libraries. Docking can also provide a useful starting point for structure-based ligand optimization or for investigating a ligand's mechanism of action. Advances in computational methods, including both physics-based and machine learning approaches, as well as in complementary experimental techniques, are making docking an even more powerful tool. We review how docking works and how it can drive drug discovery and biological research. We also describe its current limitations and ongoing efforts to overcome them.

Structure-based discovery of CFTR potentiators and inhibitors.

The cystic fibrosis transmembrane conductance regulator (CFTR) is a crucial ion channel whose loss of function leads to cystic fibrosis, whereas its hyperactivation leads to secretory diarrhea. Small molecules that improve CFTR folding (correctors) or function (potentiators) are clinically available. However, the only potentiator, ivacaftor, has suboptimal pharmacokinetics and inhibitors have yet to be clinically developed. Here, we combine molecular docking, electrophysiology, cryo-EM, and medicinal chemistry to identify CFTR modulators. We docked ∼155 million molecules into the potentiator site on CFTR, synthesized 53 test ligands, and used structure-based optimization to identify candidate modulators. This approach uncovered mid-nanomolar potentiators, as well as inhibitors, that bind to the same allosteric site. These molecules represent potential leads for the development of more effective drugs for cystic fibrosis and secretory diarrhea, demonstrating the feasibility of large-scale docking for ion channel drug discovery.

Discovery of antimicrobial peptides in the global microbiome with machine learning.

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.

Direct interrogation of context-dependent GPCR activity with a universal biosensor platform.

G protein-coupled receptors (GPCRs) are the largest family of druggable proteins encoded in the human genome, but progress in understanding and targeting them is hindered by the lack of tools to reliably measure their nuanced behavior in physiologically relevant contexts. Here, we developed a collection of compact ONE vector G-protein Optical (ONE-GO) biosensor constructs as a scalable platform that can be conveniently deployed to measure G-protein activation by virtually any GPCR with high fidelity even when expressed endogenously in primary cells. By characterizing dozens of GPCRs across many cell types like primary cardiovascular cells or neurons, we revealed insights into the molecular basis for G-protein coupling selectivity of GPCRs, pharmacogenomic profiles of anti-psychotics on naturally occurring GPCR variants, and G-protein subtype signaling bias by endogenous GPCRs depending on cell type or upon inducing disease-like states. In summary, this open-source platform makes the direct interrogation of context-dependent GPCR activity broadly accessible.

First-in-class MKK4 inhibitors enhance liver regeneration and prevent liver failure.

Diminished hepatocyte regeneration is a key feature of acute and chronic liver diseases and after extended liver resections, resulting in the inability to maintain or restore a sufficient functional liver mass. Therapies to restore hepatocyte regeneration are lacking, making liver transplantation the only curative option for end-stage liver disease. Here, we report on the structure-based development and characterization (nuclear magnetic resonance [NMR] spectroscopy) of first-in-class small molecule inhibitors of the dual-specificity kinase MKK4 (MKK4i). MKK4i increased liver regeneration upon hepatectomy in murine and porcine models, allowed for survival of pigs in a lethal 85% hepatectomy model, and showed antisteatotic and antifibrotic effects in liver disease mouse models. A first-in-human phase I trial (European Union Drug Regulating Authorities Clinical Trials [EudraCT] 2021-000193-28) with the clinical candidate HRX215 was conducted and revealed excellent safety and pharmacokinetics. Clinical trials to probe HRX215 for prevention/treatment of liver failure after extensive oncological liver resections or after transplantation of small grafts are warranted.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics.

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Discovery of natural-product-derived sequanamycins as potent oral anti-tuberculosis agents.

The emergence of drug-resistant tuberculosis has created an urgent need for new anti-tubercular agents. Here, we report the discovery of a series of macrolides called sequanamycins with outstanding in vitro and in vivo activity against Mycobacterium tuberculosis (Mtb). Sequanamycins are bacterial ribosome inhibitors that interact with the ribosome in a similar manner to classic macrolides like erythromycin and clarithromycin, but with binding characteristics that allow them to overcome the inherent macrolide resistance of Mtb. Structures of the ribosome with bound inhibitors were used to optimize sequanamycin to produce the advanced lead compound SEQ-9. SEQ-9 was efficacious in mouse models of acute and chronic TB as a single agent, and it demonstrated bactericidal activity in a murine TB infection model in combination with other TB drugs. These results support further investigation of this series as TB clinical candidates, with the potential for use in new regimens against drug-susceptible and drug-resistant TB.

TScan-II: A genome-scale platform for the de novo identification of CD4+ T cell epitopes.

CD4+ T cells play fundamental roles in orchestrating immune responses and tissue homeostasis. However, our inability to associate peptide human leukocyte antigen class-II (HLA-II) complexes with their cognate T cell receptors (TCRs) in an unbiased manner has hampered our understanding of CD4+ T cell function and role in pathologies. Here, we introduce TScan-II, a highly sensitive genome-scale CD4+ antigen discovery platform. This platform seamlessly integrates the endogenous HLA-II antigen-processing machinery in synthetic antigen-presenting cells and TCR signaling in T cells, enabling the simultaneous screening of multiple HLAs and TCRs. Leveraging genome-scale human, virome, and epitope mutagenesis libraries, TScan-II facilitates de novo antigen discovery and deep exploration of TCR specificity. We demonstrate TScan-II's potential for basic and translational research by identifying a non-canonical antigen for a cancer-reactive CD4+ T cell clone. Additionally, we identified two antigens for clonally expanded CD4+ T cells in Sjögren's disease, which bind distinct HLAs and are expressed in HLA-II-positive ductal cells within affected salivary glands.

Molecular basis of anaphylatoxin binding, activation, and signaling bias at complement receptors.

The complement system is a critical part of our innate immune response, and the terminal products of this cascade, anaphylatoxins C3a and C5a, exert their physiological and pathophysiological responses primarily via two GPCRs, C3aR and C5aR1. However, the molecular mechanism of ligand recognition, activation, and signaling bias of these receptors remains mostly elusive. Here, we present nine cryo-EM structures of C3aR and C5aR1 activated by their natural and synthetic agonists, which reveal distinct binding pocket topologies of complement anaphylatoxins and provide key insights into receptor activation and transducer coupling. We also uncover the structural basis of a naturally occurring mechanism to dampen the inflammatory response of C5a via proteolytic cleavage of the terminal arginine and the G-protein signaling bias elicited by a peptide agonist of C3aR identified here. In summary, our study elucidates the innerworkings of the complement anaphylatoxin receptors and should facilitate structure-guided drug discovery to target these receptors in a spectrum of disorders.

Validating Small Molecule Chemical Probes for Biological Discovery.

Small molecule chemical probes are valuable tools for interrogating protein biological functions and relevance as a therapeutic target. Rigorous validation of chemical probe parameters such as cellular potency and selectivity is critical to unequivocally linking biological and phenotypic data resulting from treatment with a chemical probe to the function of a specific target protein. A variety of modern technologies are available to evaluate cellular potency and selectivity, target engagement, and functional response biomarkers of chemical probe compounds. Here, we review these technologies and the rationales behind using them for the characterization and validation of chemical probes. In addition, large-scale phenotypic characterization of chemical probes through chemical genetic screening is increasingly leading to a wealth of information on the cellular pharmacology and disease involvement of potential therapeutic targets. Extensive compound validation approaches and integration of phenotypic information will lay foundations for further use of chemical probes in biological discovery.

State-selective modulation of heterotrimeric Gαs signaling with macrocyclic peptides.

The G protein-coupled receptor cascade leading to production of the second messenger cAMP is replete with pharmacologically targetable proteins, with the exception of the Gα subunit, Gαs. GTPases remain largely undruggable given the difficulty of displacing high-affinity guanine nucleotides and the lack of other drug binding sites. We explored a chemical library of 1012 cyclic peptides to expand the chemical search for inhibitors of this enzyme class. We identified two macrocyclic peptides, GN13 and GD20, that antagonize the active and inactive states of Gαs, respectively. Both macrocyclic peptides fine-tune Gαs activity with high nucleotide-binding-state selectivity and G protein class-specificity. Co-crystal structures reveal that GN13 and GD20 distinguish the conformational differences within the switch II/α3 pocket. Cell-permeable analogs of GN13 and GD20 modulate Gαs/Gßγ signaling in cells through binding to crystallographically defined pockets. The discovery of cyclic peptide inhibitors targeting Gαs provides a path for further development of state-dependent GTPase inhibitors.

A general chemical principle for creating closure-stabilizing integrin inhibitors.

Integrins are validated drug targets with six approved therapeutics. However, small-molecule inhibitors to three integrins failed in late-stage clinical trials for chronic indications. Such unfavorable outcomes may in part be caused by partial agonism, i.e., the stabilization of the high-affinity, extended-open integrin conformation. Here, we show that the failed, small-molecule inhibitors of integrins αIIbß3 and α4ß1 stabilize the high-affinity conformation. Furthermore, we discovered a simple chemical feature present in multiple αIIbß3 antagonists that stabilizes integrins in their bent-closed conformation. Closing inhibitors contain a polar nitrogen atom that stabilizes, via hydrogen bonds, a water molecule that intervenes between a serine residue and the metal in the metal-ion-dependent adhesion site (MIDAS). Expulsion of this water is a requisite for transition to the open conformation. This change in metal coordination is general to integrins, suggesting broad applicability of the drug-design principle to the integrin family, as validated with a distantly related integrin, α4ß1.

BET inhibition blocks inflammation-induced cardiac dysfunction and SARS-CoV-2 infection.

Cardiac injury and dysfunction occur in COVID-19 patients and increase the risk of mortality. Causes are ill defined but could be through direct cardiac infection and/or inflammation-induced dysfunction. To identify mechanisms and cardio-protective drugs, we use a state-of-the-art pipeline combining human cardiac organoids with phosphoproteomics and single nuclei RNA sequencing. We identify an inflammatory "cytokine-storm", a cocktail of interferon gamma, interleukin 1ß, and poly(I:C), induced diastolic dysfunction. Bromodomain-containing protein 4 is activated along with a viral response that is consistent in both human cardiac organoids (hCOs) and hearts of SARS-CoV-2-infected K18-hACE2 mice. Bromodomain and extraterminal family inhibitors (BETi) recover dysfunction in hCOs and completely prevent cardiac dysfunction and death in a mouse cytokine-storm model. Additionally, BETi decreases transcription of genes in the viral response, decreases ACE2 expression, and reduces SARS-CoV-2 infection of cardiomyocytes. Together, BETi, including the Food and Drug Administration (FDA) breakthrough designated drug, apabetalone, are promising candidates to prevent COVID-19 mediated cardiac damage.

Ancestry matters: Building inclusivity into preclinical study design.

Human cell lines (CLs) are key assets for biomedicine but lack ancestral diversity. Here, we explore why genetic diversity among cell-based models is essential for making preclinical research more equitable and widely translatable. We lay out practical actions that can be taken to improve inclusivity in study design.

A Deep Learning Approach to Antibiotic Discovery.

Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed predictions on multiple chemical libraries and discovered a molecule from the Drug Repurposing Hub-halicin-that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens including Mycobacterium tuberculosis and carbapenem-resistant Enterobacteriaceae. Halicin also effectively treated Clostridioides difficile and pan-resistant Acinetobacter baumannii infections in murine models. Additionally, from a discrete set of 23 empirically tested predictions from >107 million molecules curated from the ZINC15 database, our model identified eight antibacterial compounds that are structurally distant from known antibiotics. This work highlights the utility of deep learning approaches to expand our antibiotic arsenal through the discovery of structurally distinct antibacterial molecules.

What Makes a Discovery Successful? The Story of Linda Buck and the Olfactory Receptors.

In 1991, Buck and Axel published a landmark study in Cell for work that was awarded the 2004 Nobel Prize. The identification of the olfactory receptors as the largest family of GPCRs catapulted olfaction into mainstream neurobiology. This BenchMark revisits Buck's experimental innovation and its surprising success at the time.

Structural Basis for Blocking Sugar Uptake into the Malaria Parasite Plasmodium falciparum.

Plasmodium species, the causative agent of malaria, rely on glucose for energy supply during blood stage. Inhibition of glucose uptake thus represents a potential strategy for the development of antimalarial drugs. Here, we present the crystal structures of PfHT1, the sole hexose transporter in the genome of Plasmodium species, at resolutions of 2.6 Å in complex with D-glucose and 3.7 Å with a moderately selective inhibitor, C3361. Although both structures exhibit occluded conformations, binding of C3361 induces marked rearrangements that result in an additional pocket. This inhibitor-binding-induced pocket presents an opportunity for the rational design of PfHT1-specific inhibitors. Among our designed C3361 derivatives, several exhibited improved inhibition of PfHT1 and cellular potency against P. falciparum, with excellent selectivity to human GLUT1. These findings serve as a proof of concept for the development of the next-generation antimalarial chemotherapeutics by simultaneously targeting the orthosteric and allosteric sites of PfHT1.

Cryo-EM Structure of the Human Cannabinoid Receptor CB2-Gi Signaling Complex.

Drugs selectively targeting CB2 hold promise for treating neurodegenerative disorders, inflammation, and pain while avoiding psychotropic side effects mediated by CB1. The mechanisms underlying CB2 activation and signaling are poorly understood but critical for drug design. Here we report the cryo-EM structure of the human CB2-Gi signaling complex bound to the agonist WIN 55,212-2. The 3D structure reveals the binding mode of WIN 55,212-2 and structural determinants for distinguishing CB2 agonists from antagonists, which are supported by a pair of rationally designed agonist and antagonist. Further structural analyses with computational docking results uncover the differences between CB2 and CB1 in receptor activation, ligand recognition, and Gi coupling. These findings are expected to facilitate rational structure-based discovery of drugs targeting the cannabinoid system.

T-Scan: A Genome-wide Method for the Systematic Discovery of T Cell Epitopes.

T cell recognition of specific antigens mediates protection from pathogens and controls neoplasias, but can also cause autoimmunity. Our knowledge of T cell antigens and their implications for human health is limited by the technical limitations of T cell profiling technologies. Here, we present T-Scan, a high-throughput platform for identification of antigens productively recognized by T cells. T-Scan uses lentiviral delivery of antigen libraries into cells for endogenous processing and presentation on major histocompatibility complex (MHC) molecules. Target cells functionally recognized by T cells are isolated using a reporter for granzyme B activity, and the antigens mediating recognition are identified by next-generation sequencing. We show T-Scan correctly identifies cognate antigens of T cell receptors (TCRs) from viral and human genome-wide libraries. We apply T-Scan to discover new viral antigens, perform high-resolution mapping of TCR specificity, and characterize the reactivity of a tumor-derived TCR. T-Scan is a powerful approach for studying T cell responses.

High-Throughput Mapping of B Cell Receptor Sequences to Antigen Specificity.

B cell receptor (BCR) sequencing is a powerful tool for interrogating immune responses to infection and vaccination, but it provides limited information about the antigen specificity of the sequenced BCRs. Here, we present LIBRA-seq (linking B cell receptor to antigen specificity through sequencing), a technology for high-throughput mapping of paired heavy- and light-chain BCR sequences to their cognate antigen specificities. B cells are mixed with a panel of DNA-barcoded antigens so that both the antigen barcode(s) and BCR sequence are recovered via single-cell next-generation sequencing. Using LIBRA-seq, we mapped the antigen specificity of thousands of B cells from two HIV-infected subjects. The predicted specificities were confirmed for a number of HIV- and influenza-specific antibodies, including known and novel broadly neutralizing antibodies. LIBRA-seq will be an integral tool for antibody discovery and vaccine development efforts against a wide range of antigen targets.