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Natural products contain a range of chemical structures optimized for biological interactions. Fragmenting these compounds could help to combine this diversity with the broad coverage of chemical space offered by fragment-based drug discovery, and help to improve the efficiency with which screening hits can become successful drugs.

As Nature Chemical Biology approaches its third decade we asked a collection of chemical biologists, “What do you think are the most exciting frontiers or the most needed developments in your main field of research?” — here is what they said.

Classifying G protein–coupled receptors by ligand binding similarity leads to unexpected links between receptors unrelated by sequence or structure, possibly revealing insights into receptor evolution.

Tummino et al. dock 74 million molecules against the human cannabinoid-1 receptor to find uM ligands. Optimization led to a nM agonist conferring analgesia with reduced side effects in mice, highlighting its potential as a pain therapeutic and the promise of a structure-based approach.

Structural studies of the itch receptors MRGPRX2 and MRGPRX4 in complex with endogenous and synthetic ligands provide a basis for the development of therapeutic compounds for pain, itch and mast cell-mediated hypersensitivity.

A computational screen of an ultra-large virtual library against the structure of the melatonin receptor found nanomolar ligands, and ultimately two selective MT₁ inverse agonists that induced phase advancement of the mouse circadian clock when given at subjective dusk.

Computational docking to the the μ-opioid-receptor identifies PZM21, a novel selective biased agonist that generates substantial affective analgesia in mice without altering respiration or inducing drug reinforcement.

The docking of a 1.7 billion- versus a 99 million-molecule virtual library against β-lactamase revealed that the larger-sized library produced improved hit rates and potency along with an increased number of scaffolds.

The cryo-EM structures of MRGPRX1–Gq complexes are reported, which revealed the activation and allosteric modulation mechanism of human MRGPRX1 receptor, which may enable the structure-based identification of novel analgesics.

Prediction of a protein's affinity for a ligand has been improved through fundamental physical modeling.

A negative allosteric modulator of the G-protein-coupled receptor β₂-adrenergic receptor binds to a membrane-facing surface adjacent to a molecular switch for receptor activation, and its binding disrupts a water-mediated polar network stabilizing an inactive switch conformation.

A human–SARS-CoV-2 protein interaction map highlights cellular processes that are hijacked by the virus and that can be targeted by existing drugs, including inhibitors of mRNA translation and predicted regulators of the sigma receptors.

This comprehensive study of the most enigmatic serotonin receptor 5-HT_5AR includes lots of pharmacological investigations, inactive and active state structures with antagonist, partial agonist and full agonists. Also, a highly potent and selective antagonist was developed.

Crystal structures of the σ₂ receptor are determined and used to perform a docking screen of nearly 500 million molecules, identifying σ₂-selective ligands and providing insight into the role of σ₂ in neuropathic pain.

A fluorogenic reporter allows visualization of spike protein and ACE2 receptor interaction and the identification of natural products that inhibit SARS-CoV-2 replication in vitro and in vivo.

Docking virtual libraries against protein structures has identified potent ligands for multiple targets. A comprehensive analysis reveals that the increased size of virtual libraries improves receptor fit but diverges from bio-like molecules.

This study reveals near-atomic interfacial details of an Alzheimer’s Positron Emission Tomography (PET) molecule MK-6240 with its target disease marker, tau amyloid, showing MK-6240 mostly interacts with itself, like a pancake stack, which stabilizes an otherwise small interface with the amyloid.

Non-addictive treatments for pain are much needed. Here, the authors identify in vivo active leads for inflammatory pain using large library docking against the EP4 prostaglandin receptor.

A large-scale computational effort is used to predict the activity of 656 drugs against 73 protein targets that have been associated with adverse drug reactions; the abdominal pain side effect of the synthetic oestrogen chlorotrianisene is shown to be mediated through its inhibition of cyclooxygenase-1.

Drugs that are chemically quite similar often bind to biologically diverse protein targets, and it is unclear how selective many of these compounds are. Because many drug–target combinations exist, it would be useful to explore possible interactions computationally. Here, 3,665 drugs are tested against hundreds of targets; chemical similarities between drugs and ligand sets are found to predict thousands of unanticipated associations.

A computational approach is used to predict the function of an uncharacterized enzyme by docking high-energy intermediate forms of candidate metabolites into its purported binding site. The docking experiments predicted that the enzyme would be able to deaminate intermediates of 5-methylthioadenosine and S-adenosylhomocysteine, a prediction confirmed by biochemical experiments and examination of the X-ray crystal structure of the protein.

TMEM16F is a Ca²⁺ activated ion channel and lipid scramblase involved in cell fusion. Here authors determine cryo-EM structures of TMEM16F with or without bound blockers, such as the FDA-approved drug niclosamide.

A proteomics and computational approach was developed to map the proximal proteome of the activated μ-opioid receptor and to extract subcellular location, trafficking and functional partners of G-protein-coupled receptor activity.

Probe molecules with systemic activity remain rare, and, as was realized in the pre-molecular era, even their off-target activity can illuminate biology. A study reporting a screen of over 600 kinase inhibitors found nine with bromodomain inhibitory activity and has implications for mechanism and compound optimization.

Using a multi-OMICS approach, Haas et al identify 54 human genes and 16 host-targeting chemical compounds that regulate influenza A virus infection in lung epithelial cells, including AHNAK and COBP1 which are also essential for SARS-CoV-2 infection.

A virtual screen of the GPCR D3R based on a homology model prior to publication of the crystal structure and a subsequent virtual screen based on the crystal structure of the receptor once it became available both identified new ligands with verified activities.

Using a make-on-demand library that contains hundreds-of-millions of molecules, structure-based docking was used to identify compounds that, after synthesis and testing, are shown to interact with AmpC β-lactamase and the D₄ dopamine receptor with high affinity.

New agonists of the serotonin 5-HT_2A receptor (5-HT_2AR) confer high brain permeability and antidepressant activity and—in contrast to classic 5-HT_2AR agonists—lack psychedelic activity.

Yeast-based screening identifies the benzodiazepine drug lorazepam as a non-selective positive allosteric modulator of the G-protein-coupled receptor (GPCR) GPR68; homology modelling and molecular docking of 3.1 million molecules found a new compound, ‘ogerin’, as a potent GPR68 modulator, which suppressed recall in fear conditioning in wild-type mice, and the general method of combining physical and structure-based screening may lead to the discovery of selective ligands for other GPCRs.

The adoption of multiple conformations by proteins presents a challenge for ligand discovery using docking simulations. Now, a method for representing the conformational behaviour of a flexible protein in docking screens, which is guided by experimental crystallography data, is shown to predict protein conformation, ligand pose and aid the discovery of new ligands.

High-throughput screening identifies opioid compounds and prodynorphin-derived peptide agonists of the G-protein-coupled receptor MRGPRX2 and informs a homology model that is used for in silico screening to find a small-molecule probe that provokes degranulation in mast cells, which express this receptor.

A modification of the in silico screening tool, DOCK, allows for identification of compounds that covalently modify catalytic and noncatalytic protein nucleophiles to modulate the activities of bacterial β-lactamase and the kinases RSK2, MSK1 and JAK3.

D2 dopamine receptor ligands biased for b-arrestin recruitment were developed based on a receptor homology model that identified conserved ligand contacts within the TM5 and EL2 regions as important for biased signaling.

Despite the need for new psychoactive drugs, there are few robust approaches for discovering novel neuroactive molecules. Development of a behavior-based high-throughput screen in zebrafish led to the discovery of molecules with neurological effects. Translating the complex behavioral phenotypes elicited by compounds into a simple barcode enabled identification of their mechanism of action.

Structure-based docking screens of compound libraries are common in early drug and probe discovery. This protocol outlines best practices and control calculations to evaluate docking parameters prior to undertaking a large-scale prospective screen.

A cheminformatics approach helps identify proteins such as GPCRs, ion channels and kinases that are targeted by small molecules that give phenotypes in a zebrafish behavioral assay.