Docking Finds GPCR Ligands in Dark Chemical Matter

Structure-based virtual screening discovers potent and selective adenosine A1 receptor antagonists

Development of subtype-selective leads is essential in drug discovery campaigns targeting G protein-coupled receptors (GPCRs). Herein, a structure-based virtual screening approach to rationally design subtype-selective ligands was applied to the A₁ and A_2A adenosine receptors (A₁R and A_2AR). Crystal structures of these closely related subtypes revealed a non-conserved subpocket in the binding sites that could be exploited to identify A₁R selective ligands. A library of 4.6 million compounds was screened computationally against both receptors using molecular docking and 20 A₁R selective ligands were predicted. Of these, seven antagonized the A₁R with micromolar activities and several compounds displayed slight selectivity for this subtype. Twenty-seven analogs of two discovered scaffolds were designed, resulting in antagonists with nanomolar potency and up to 76-fold A₁R-selectivity. Our results show the potential of structure-based virtual screening to guide discovery and optimization of subtype-selective ligands, which could facilitate the development of safer drugs.

SARS-CoV2 billion-compound docking

This dataset contains ligand conformations and docking scores for 1.4 billion molecules docked against 6 structural targets from SARS-CoV2, representing 5 unique proteins: MPro, NSP15, PLPro, RDRP, and the Spike protein. Docking was carried out using the AutoDock-GPU platform on the Summit supercomputer and Google Cloud. The docking procedure employed the Solis Wets search method to generate 20 independent ligand binding poses per compound. Each compound geometry was scored using the AutoDock free energy estimate, and rescored using RFScore v3 and DUD-E machine-learned rescoring models. Input protein structures are included, suitable for use by AutoDock-GPU and other docking programs. As the result of an exceptionally large docking campaign, this dataset represents a valuable resource for discovering trends across small molecule and protein binding sites, training AI models, and comparing to inhibitor compounds targeting SARS-CoV-2. The work also gives an example of how to organize and process data from ultra-large docking screens.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

Preliminary modelling as the first stage of targeted organic synthesis

The review aims to present a classification and applicability analysis of methods for preliminary molecular modelling for targeted organic, catalytic and biocatalytic synthesis. The following three main approaches are considered as a primary classification of the methods: modelling of the target – ligand coordination without structural information on both the target and the resulting complex; calculations based on experimentally obtained structural information about the target; and dynamic simulation of the target – ligand complex and the reaction mechanism with calculation of the free energy of the reaction. The review is meant for synthetic chemists to be used as a guide for building an algorithm for preliminary modelling and synthesis of structures with specified properties.

The bibliography includes 353 references.

Purinergic GPCR transmembrane residues involved in ligand recognition and dimerization

We compare the GPCR-ligand interactions and highlight important residues for recognition in purinergic receptors-from both X-ray crystallographic and cryo-EM structures. These include A1 and A2A adenosine receptors, and P2Y1 and P2Y12 receptors that respond to ADP and other nucleotides. These receptors are important drug discovery targets for immune, metabolic and nervous system disorders. In most cases, orthosteric ligands are represented, except for one allosteric P2Y1 antagonist. This review catalogs the residues and regions that engage in contacts with ligands or with other GPCR protomers in dimeric forms. Residues that are in proximity to bound ligands within purinergic GPCR families are correlated. There is extensive conservation of recognition motifs between adenosine receptors, but the P2Y1 and P2Y12 receptors are each structurally distinct in their ligand recognition. Identifying common interaction features for ligand recognition within a receptor class that has multiple structures available can aid in the drug discovery process.

Property-Unmatched Decoys in Docking Benchmarks

Enrichment of ligands versus property-matched decoys is widely used to test and optimize docking library screens. However, the unconstrained optimization of enrichment alone can mislead, leading to false confidence in prospective performance. This can arise by over-optimizing for enrichment against property-matched decoys, without considering the full spectrum of molecules to be found in a true large library screen. Adding decoys representing charge extrema helps mitigate over-optimizing for electrostatic interactions. Adding decoys that represent the overall characteristics of the library to be docked allows one to sample molecules not represented by ligands and property-matched decoys but that one will encounter in a prospective screen. An optimized version of the DUD-E set (DUDE-Z), as well as Extrema and sets representing broad features of the library (Goldilocks), is developed here. We also explore the variability that one can encounter in enrichment calculations and how that can temper one's confidence in small enrichment differences. The new tools and new decoy sets are freely available at http://tldr.docking.org and http://dudez.docking.org.

G protein-coupled receptors: structure- and function-based drug discovery

As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.

Design and Application of Receptor-Targeted Fluorescent Probes Based on Small Molecular Fluorescent Dyes

In recent years, a variety of receptor-targeted fluorescent probes have been developed and widely used to realize the visualization of certain receptors, which facilitates the early diagnosis and treatment of diseases. In this Review, we focus on the recent achievements in design, chemical structure, imaging characterization, and potential applications of receptor-targeted fluorescent probes from the past 10 years. The development and application of receptor-targeted fluorescent probes will expand our knowledge of the distribution and function of disease-related receptors, shed light on the drug discovery for clinical diseases where receptors are implicated, and feed into the diagnosis and treatment of a plethora of diseases, including tumors.

Recent findings leading to the discovery of selective dopamine D4 receptor ligands for the treatment of widespread diseases

Since its discovery, the dopamine D₄ receptor (D₄R) has been suggested to be an attractive target for the treatment of neuropsychiatric diseases. Novel findings have renewed the interest in such a receptor as an emerging target for the management of different diseases, including cancer, Parkinson's disease, alcohol or substance use disorders, eating disorders, erectile dysfunction and cognitive deficits. The recently resolved crystal structures of D₄R in complexes with the potent ligands nemonapride and L-745870 strongly improved the knowledge on the molecular mechanisms involving the D₄R functions and may help medicinal chemists in drug design. This review is focused on the recent development of the subtype selective D₄R ligands belonging to classical or new chemotypes. Moreover, ligands showing functional selectivity toward G protein activation or β-arrestin recruitment and the effects of selective D₄R ligands on the above-mentioned diseases are discussed.

Consensus virtual screening of dark chemical matter and food chemicals uncover potential inhibitors of SARS-CoV-2 main protease

The pandemic caused by SARS-CoV-2 (COVID-19 disease) has claimed more than 500 000 lives worldwide, and more than nine million people are infected. Unfortunately, an effective drug or vaccine for its treatment is yet to be found. The increasing information available on critical molecular targets of SARS-CoV-2 and active compounds against related coronaviruses facilitates the proposal (or repurposing) of drug candidates for the treatment of COVID-19, with the aid of in silico methods. As part of a global effort to fight the COVID-19 pandemic, herein we report a consensus virtual screening of extensive collections of food chemicals and compounds known as dark chemical matter. The rationale is to contribute to global efforts with a description of currently underexplored chemical space regions. The consensus approach included combining similarity searching with various queries and fingerprints, molecular docking with two docking protocols, and ADMETox profiling. We propose compounds commercially available for experimental testing. The full list of virtual screening hits is disclosed.

As part of a global effort to identify drug candidates for the treatment of COVID-19, herein, we report small molecules commercially available selected from a consensus virtual screening strategy.