Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel noncovalent smallmolecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (M pro ) by employing a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this M pro inhibitor with an inhibition constant (K i ) of 2.9 μM (95% CI 2.2, 4.0). Furthermore, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of M pro forming stable hydrogen bond and hydrophobic interactions. We then used multiple μs-time scale molecular dynamics (MD) simulations and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by M pro , involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits M pro and offers a springboard for further therapeutic design.
Grid technology is widely emerging. Still, there is an eminent shortage of real Grid users, mostly due to the lack of a "critical mass" of widely deployed and reliable higher-level Grid services, tailored to application needs. The GridLab project aims to provide fundamentally new capabilities for applications to exploit the power of Grid computing, thus bridging the gap between application needs and existing Grid middleware. We present an overview of GridLab, a large-scale, EU-funded Grid project spanning over a dozen groups in Europe and the US. We first outline our vision of Grid-empowered applications and then discuss GridLab's general architecture and its Grid Application Toolkit (GAT). We illustrate how applications can be Grid-enabled with the GAT and discuss GridLab's scheduler as an example of GAT services.
Core Grid technologies are rapidly maturing, but there remains a shortage of real Grid applications. One important reason is the lack of a simple and high-level application programming toolkit, bridging the gap between existing Grid middleware and application-level needs. The Grid Application Toolkit (GAT), as currently developed by the EC-funded project GridLab [1], provides this missing functionality. As seen from the application, the GAT provides a unified simple programming interface to the Grid infrastructure, tailored to the needs of Grid application programmers and users. A uniform programming interface will be needed for application developers to create a new generation of "Grid-aware" applications. The GAT implementation handles both the complexity and the variety of existing Grid middleware services via so-called adaptors. Complementing existing Grid middleware, GridLab also provides high-level services to implement the GAT functionality.We present the GridLab software architecture, consisting of the GAT, environment-specific adaptors, and GridLab services. We elaborate the concepts underlying the GAT and outline the corresponding application programming interface. We present the functionality of GridLab's high-level services and demonstrate how a dynamic Grid application can easily benefit from the GAT. All GridLab software is open source and can be downloaded from the project Web site.
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