While small molecule internal strain is crucial to molecular docking, using it in evaluating ligand scores has remained elusive. Here, we investigate a technique that calculates strain using relative torsional populations in the Cambridge Structural Database, enabling fast precalculation of these energies. In retrospective studies of large docking screens of the dopamine D4 receptor and of AmpC β-lactamase, where close to 600 docking hits were tested experimentally, including such strain energies improved hit rates by preferentially reducing the ranks of strained high-scoring decoy molecules. In a 40-target subset of the DUD-E benchmark, we found two thresholds that usefully distinguished between ligands and decoys: one based on the total strain energy of the small molecules and another based on the maximum strain allowed for any given torsion within them. Using these criteria, about 75% of the benchmark targets had improved enrichment after strain filtering. Relying on precalculated population distributions, this approach is rapid, taking less than 0.04 s to evaluate a conformation on a standard core, making it pragmatic for precalculating strain in even ultralarge libraries. Since it is scoring function agnostic, it may be useful to multiple docking approaches; it is openly available at http://tldr.docking.org.

GPR68, an orphan G-protein coupled receptor, senses protons, couples to multiple G-proteins, and is also activated or inhibited by divalent metal ions. It has seven extracellular histidine residues, although it is not clear how these histidine residues play a role in both proton-sensing and metal ion modulation. Here we demonstrate that divalent metal ions are allosteric modulators that can activate or inhibit proton activity in a concentration- and pH-dependent manner. We then show that single histidine mutants have differential and varying degrees of effects on proton-sensing and metal ion modulation. Some histidine residues play dual roles in proton-sensing and metal ion modulation, while others are important in one or the other but not both. Two extracellular disulfide bonds are predicted to constrain histidine residues to be spatially close to each other. Combining histidine mutations leads to reduced proton activity and resistance to metal ion modulation, while breaking the less conserved disulfide bond results in a more severe reduction in proton-sensing over metal modulation. The small-molecule positive allosteric modulators (PAMs) ogerin and lorazepam are not affected by these mutations and remain active at mutants with severely reduced proton activity or are resistant to metal ion modulation. These results suggest GPR68 possesses two independent allosteric modulation systems, one through interaction with divalent metal ions at the extracellular surface and another through small-molecule PAMs in the transmembrane domains. A new GPR68 model is developed to accommodate the findings which could serve as a template for further studies and ligand discovery by virtual ligand docking.

The TMEM16 family of calcium-activated membrane proteins includes ten mammalian paralogs (TMEM16A-K) playing distinct physiological roles with some implicated in cancer and airway diseases. Their modulators with therapeutic potential include 1PBC, a potent inhibitor with anti-tumoral properties, and the FDA-approved drug niclosamide that targets TMEM16F to inhibit syncytia formation induced by SARS-CoV-2 infection. Here, we report cryo-EM structures of TMEM16F associated with 1PBC and niclosamide, revealing that both molecules bind the same drug binding pocket. We functionally and computationally validate this binding pocket in TMEM16A as well as TMEM16F, thereby showing that drug modulation also involves residues that are not conserved between TMEM16A and TMEM16F. This study establishes a much-needed structural framework for the development of more potent and more specific drug molecules targeting TMEM16 proteins.

The dual functions of TMEM16F as Ca²⁺-activated ion channel and lipid scramblase raise intriguing questions regarding their molecular basis. Intrigued by the ability of the FDA-approved drug niclosamide to inhibit TMEM16F-dependent syncytia formation induced by SARS-CoV-2, we examined cryo-EM structures of TMEM16F with or without bound niclosamide or 1PBC, a known blocker of TMEM16A Ca²⁺-activated Cl^- channel. Here, we report evidence for a lipid scrambling pathway along a groove harboring a lipid trail outside the ion permeation pore. This groove contains the binding pocket for niclosamide and 1PBC. Mutations of two residues in this groove specifically affect lipid scrambling. Whereas mutations of some residues in the binding pocket of niclosamide and 1PBC reduce their inhibition of TMEM16F-mediated Ca²⁺ influx and PS exposure, other mutations preferentially affect the ability of niclosamide and/or 1PBC to inhibit TMEM16F-mediated PS exposure, providing further support for separate pathways for ion permeation and lipid scrambling.

Antiviral therapeutics to treat SARS-CoV-2 are needed to diminish the morbidity of the ongoing COVID-19 pandemic. A well-precedented drug target is the main viral protease (M^Pro ), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure-based approach, we docked 1.2 billion non-covalent lead-like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC₅₀ of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of M^Pro inhibitors for SARS-CoV-2, the modest success rate also reveals weaknesses in our approach for challenging targets like M^Pro versus other targets where it has been more successful, and versus other structure-based techniques against M^Pro itself.