GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis

Finding a novel drug is a very long and complex procedure. Using computer simulations, it is possible to accelerate the preliminary phases by performing a virtual screening that filters a large set of drug candidates to a manageable number. This paper presents the implementations and comparative analysis of two GPU-optimized implementations of a virtual screening algorithm targeting novel GPU architectures. This work focuses on the analysis of parallel computation patterns and their mapping onto the target architecture. The first method adopts a traditional approach that spreads the computation for a single molecule across the entire GPU. The second uses a novel batched approach that exploits the parallel architecture of the GPU to evaluate more molecules in parallel. Experimental results showed a different behavior depending on the size of the database to be screened, either reaching a performance plateau sooner or having a more extended initial transient period to achieve a higher throughput (up to 5x), which is more suitable for extreme-scale virtual screening campaigns

An extreme-scale virtual screening platform for drug discovery

Virtual screening is one of the early stages that aims to select a set of promising ligands from a vast chemical library. Molecular Docking is a crucial task in the process of drug discovery and it consists of the estimation of the position of a molecule inside the docking site. In the contest of urgent computing, we designed from scratch the EXSCALATE molecular docking platform to benefit from heterogeneous computation nodes and to avoid scaling issues

The contribution of primordial binaries to the blue straggler population in 47 Tucanae

The recent observation (Ferraro et al. 2003b) of the blue straggler population in 47 Tucanae gives the first detailed characterization of their spatial distribution in the cluster over its entire volume. Relative to the light distribution, blue stragglers appear to be overabundant in the core and at large radii. The observed surface density profile shows a central peak, a zone of avoidance and a rise beyond twenty core radii. In light of these findings we explored the evolution of blue stragglers mimicking their dynamics in a multi-mass King model for 47 Tucanae. We find that the observed spatial distribution can not be explained within a purely collisional scenario in which blue stragglers are generated exclusively in the core through direct mergers. An excellent fit is obtained if we require that a sizable fraction of blue stragglers is generated in the peripheral regions of the cluster inside primordial binaries that evolve in isolation experiencing mass-transfer.Comment: 5 pages, 3 figures, to appear in ApJL, version enlarged to include Table

A Comprehensive Mapping of the Druggable Cavities within the SARS-CoV-2 Therapeutically Relevant Proteins by Combining Pocket and Docking Searches as Implemented in Pockets 2.0

(1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies; (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines); such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs; (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection; and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download

Discovery of a double Blue Straggler sequence in M15: new insight into the core-collapse process

In this paper we report on the discovery of a double blue straggler star (BSS) sequence in the core of the core-collapsed cluster M15 (NGC 7078). We performed a detailed photometric analysis of the extremely dense core of the cluster using a set of images secured with the Advanced Camera for Survey in the High Resolution Channel mode on-board the Hubble Space Telescope. The proper combination of the large number of single frames in the near-UV (F220W), and blue (F435W) filters allowed us to perform a superb modeling of the Point Spread Function and an accurate deblending procedure. The Color-Magnitude diagram revealed the presence of two distinct parallel sequences of blue stragglers. In particular, the blue BSS sequence is characterized by the intriguing presence of two different branches. The first branch appears extremely narrow, it extends up to 2.5 magnitudes brighter than the cluster main-sequence turnoff (MS-TO) point, and it is nicely reproduced by a 2 Gyr-old collisional isochrone. The second branch extends up to 1.5 magnitudes from the MS-TO and it is reproduced by a 5.5 Gyr-old collisional isochrone. Our observations suggest that each of these branches is mainly constituted by a population of nearly coeval collisional BSS of different masses generated during two episodes of high collisional activity. We discuss the possibility that the oldest episode corresponds to the core-collapse event (occurred about 5.5 Gyr ago), while the most recent one (occurred about 2 Gyr ago) is associated with a core oscillation in the post-core collapse evolution. The discovery of these features provides further strong evidence in support of the connection between the BSS properties and GC dynamical evolution, and it opens new perspectives on the study of core-collapse and post core-collapse evolution.Comment: Accepted for publication on Ap

MEDIATE - Molecular DockIng at homE: Turning collaborative simulations into therapeutic solutions

IntroductionCollaborative computing has attracted great interest in the possibility of joining the efforts of researchers worldwide. Its relevance has further increased during the pandemic crisis since it allows for the strengthening of scientific collaborations while avoiding physical interactions. Thus, the E4C consortium presents the MEDIATE initiative which invited researchers to contribute via their virtual screening simulations that will be combined with AI-based consensus approaches to provide robust and method-independent predictions. The best compounds will be tested, and the biological results will be shared with the scientific community.Areas coveredIn this paper, the MEDIATE initiative is described. This shares compounds' libraries and protein structures prepared to perform standardized virtual screenings. Preliminary analyses are also reported which provide encouraging results emphasizing the MEDIATE initiative's capacity to identify active compounds.Expert opinionStructure-based virtual screening is well-suited for collaborative projects provided that the participating researchers work on the same input file. Until now, such a strategy was rarely pursued and most initiatives in the field were organized as challenges. The MEDIATE platform is focused on SARS-CoV-2 targets but can be seen as a prototype which can be utilized to perform collaborative virtual screening campaigns in any therapeutic field by sharing the appropriate input files

The SARS-CoV-2 spike protein binds and modulates estrogen receptors

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein binds angiotensin-converting enzyme 2 as its primary infection mechanism. Interactions between S and endogenous proteins occur after infection but are not well understood. We profiled binding of S against >9000 human proteins and found an interaction between S and human estrogen receptor alpha (ER alpha). Using bioinformatics, supercomputing, and experimental assays, we identified a highly conserved and functional nuclear receptor coregulator (NRC) LXD-like motif on the S2 sub-unit. In cultured cells, S DNA transfection increased ER alpha cytoplasmic accumulation, and S treatment induced ER-dependent biological effects. Non-invasive imaging in SARS-CoV-2-infected hamsters localized lung pathology with increased ER alpha lung levels. Postmortem lung experiments from infected hamsters and humans confirmed an increase in cytoplasmic ER alpha and its colocalization with S in alveolar macrophages. These findings describe the discovery of a S-ER alpha interaction, imply a role for S as an NRC, and advance knowledge of SARS-CoV-2 biology and coronavirus disease 2019 pathology

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (M^(pro)), which is essential for viral replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to M^(pro). In subsequent cell-based viral reduction assays, one peptidomimetic and six non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2

A community effort in SARS-CoV-2 drug discovery.

peer reviewedThe COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against Covid-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.R-AGR-3826 - COVID19-14715687-CovScreen (01/06/2020 - 31/01/2021) - GLAAB Enric