Ligand recognition and allosteric modulation of the human MRGPRX1 receptor.

The human MAS-related G protein-coupled receptor X1 (MRGPRX1) is preferentially expressed in the small-diameter primary sensory neurons and involved in the mediation of nociception and pruritus. Central activation of MRGPRX1 by the endogenous opioid peptide fragment BAM8-22 and its positive allosteric modulator ML382 has been shown to effectively inhibit persistent pain, making MRGPRX1 a promising target for non-opioid pain treatment. However, the activation mechanism of MRGPRX1 is still largely unknown. Here we report three high-resolution cryogenic electron microscopy structures of MRGPRX1-Gαq in complex with BAM8-22 alone, with BAM8-22 and ML382 simultaneously as well as with a synthetic agonist compound-16. These structures reveal the agonist binding mode for MRGPRX1 and illuminate the structural requirements for positive allosteric modulation. Collectively, our findings provide a molecular understanding of the activation and allosteric modulation of the MRGPRX1 receptor, which could facilitate the structure-based design of non-opioid pain-relieving drugs.

Discovery of an Allosteric Ligand Binding Site in SMYD3 Lysine Methyltransferase.

SMYD3 is a multifunctional epigenetic enzyme with lysine methyltransferase activity and various interaction partners. It is implicated in the pathophysiology of cancers but with an unclear mechanism. To discover tool compounds for clarifying its biochemistry and potential as a therapeutic target, a set of drug-like compounds was screened in a biosensor-based competition assay. Diperodon was identified as an allosteric ligand; its R and S enantiomers were isolated, and their affinities to SMYD3 were determined (KD =42 and 84 µM, respectively). Co-crystallization revealed that both enantiomers bind to a previously unidentified allosteric site in the C-terminal protein binding domain, consistent with its weak inhibitory effect. No competition between diperodon and HSP90 (a known SMYD3 interaction partner) was observed although SMYD3-HSP90 binding was confirmed (KD =13 µM). Diperodon clearly represents a novel starting point for the design of tool compounds interacting with a druggable allosteric site, suitable for the exploration of noncatalytic SMYD3 functions and therapeutics with new mechanisms of action.

The Mac1 ADP-ribosylhydrolase is a Therapeutic Target for SARS-CoV-2.

SARS-CoV-2 continues to pose a threat to public health. Current therapeutics remain limited to direct acting antivirals that lack distinct mechanisms of action and are already showing signs of viral resistance. The virus encodes an ADP-ribosylhydrolase macrodomain (Mac1) that plays an important role in the coronaviral lifecycle by suppressing host innate immune responses. Genetic inactivation of Mac1 abrogates viral replication in vivo by potentiating host innate immune responses. However, it is unknown whether this can be achieved by pharmacologic inhibition and can therefore be exploited therapeutically. Here we report a potent and selective lead small molecule, AVI-4206, that is effective in an in vivo model of SARS-CoV-2 infection. Cellular models indicate that AVI-4206 has high target engagement and can weakly inhibit viral replication in a gamma interferon- and Mac1 catalytic activity-dependent manner; a stronger antiviral effect for AVI-4206 is observed in human airway organoids. In an animal model of severe SARS-CoV-2 infection, AVI-4206 reduces viral replication, potentiates innate immune responses, and leads to a survival benefit. Our results pharmacologically validate Mac1 as a therapeutic target via a novel immune-restoring mechanism that could potentially synergize with existing therapies targeting distinct, essential aspects of the coronaviral life cycle. This approach could be more widely used to target other viral macrodomains to develop antiviral therapeutics beyond COVID-19.

Predicting how drug molecules bind to their protein targets.

There have been substantial advances in the application of molecular modelling and simulation to drug discovery in recent years, as massive increases in computer power are coupled with continued development in the underlying methods and understanding of how to apply them. Here, we survey recent advances in one particular area-predicting how a known ligand binds to a particular protein. We focus on the four contributing classes of calculation: predicting where a binding site is on a protein; characterizing where chemical functional groups will bind to that site; molecular docking to generate a binding mode for a ligand and dynamics simulations to refine that pose and allow for protein conformation change. Examples of successful application are provided for each class.