Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors.

We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property-free knowledge base for future anticoronavirus drug discovery.

Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search.

Fragment merging is a promising approach to progressing fragments directly to on-scale potency: each designed compound incorporates the structural motifs of overlapping fragments in a way that ensures compounds recapitulate multiple high-quality interactions. Searching commercial catalogues provides one useful way to quickly and cheaply identify such merges and circumvents the challenge of synthetic accessibility, provided they can be readily identified. Here, we demonstrate that the Fragment Network, a graph database that provides a novel way to explore the chemical space surrounding fragment hits, is well-suited to this challenge. We use an iteration of the database containing >120 million catalogue compounds to find fragment merges for four crystallographic screening campaigns and contrast the results with a traditional fingerprint-based similarity search. The two approaches identify complementary sets of merges that recapitulate the observed fragment-protein interactions but lie in different regions of chemical space. We further show our methodology is an effective route to achieving on-scale potency by retrospective analyses for two different targets; in analyses of public COVID Moonshot and Mycobacterium tuberculosis EthR inhibitors, potential inhibitors with micromolar IC50 values were identified. This work demonstrates the use of the Fragment Network to increase the yield of fragment merges beyond that of a classical catalogue search.

Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease.

We present several workflows for protein-ligand docking and free energy calculation for use in the workflow management system Galaxy. The workflows are composed of several widely used open-source tools, including rDock and GROMACS, and can be executed on public infrastructure using either Galaxy's graphical interface or the command line. We demonstrate the utility of the workflows by running a high-throughput virtual screening of around 50000 compounds against the SARS-CoV-2 main protease, a system which has been the subject of intense study in the last year.

Selective cleavage of human IgG by the matrix metalloproteinases, matrilysin and stromelysin.

We have shown that two of the matrix metalloproteinases (MMPs), matrilysin and stromelysin-1, are capable of cleaving all of the human IgG subclasses. The cleavage occurs at a conserved site in the CH(2) domain of the heavy chain of IgG, releasing a single chain Fc-like fragment. We have not been able to demonstrate cleavage of IgA, IgD, IgM or IgE classes, which lack the cleavage site, nor could we show cleavage of IgG by collagenase, gelatinase, macrophage metalloelastase or membrane-type (MT)-MMP. This cleavage of IgG, by separating the antigen-binding (Fabprime prime or minute)(2) from the Fc portion, will remove much of the immunoglobulins' functionality, e.g. complement fixation, Fc receptor binding. In the context of a tumour producing matrilysin or stromelysin, this may represent a way in which the tumour protects itself from ADCC. In inflamed or damaged tissues where plasma protein leakage occurs, degradation by MMPs may be a mechanism for clearance of IgG.