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

Screen-printed electrode modified with carbon black and chitosan: a novel platform for acetylcholinesterase biosensor development

We report a screen-printed electrode (SPE) modified with a dispersion of carbon black (CB) and chitosan by drop casting. A cyclic voltammetry technique towards ferricyanide, caffeic acid, hydroquinone, and thiocholine was performed and an improvement of the electrochemical response with respect to bare SPE as well as SPE modified only with chitosan was observed. The possibility to detect thiocholine at a low applied potential with high sensitivity was exploited and an acetylcholinesterase (AChE) biosensor was developed. A dispersion of CB, chitosan, and AChE was used to fabricate this biosensor in one step by drop casting. The enzymatic activity of the immobilized AChE was determined measuring the enzymatic product thiocholine at +300 mV. Owing to the capability of organophosphorus pesticides to inhibit AChE, this biosensor was used to detect these pollutants, and paraoxon was taken as model compound. The enzyme inhibition was linearly related to the concentration of paraoxon up to 0.5 μg L–1, and a low detection limit equal to 0.05 μg L–1 (calculated as 10% of inhibition) was achieved. This biosensor was challenged for paraoxon detection in drinking waters with satisfactory recovery values. The use of AChE embedded in a dispersion of CB and chitosan allowed an easy and fast production of a sensitive biosensor suitable for paraoxon detection in drinking waters at legal limit levels

Red Cell Distribution Width and Patient Outcome in Cardiovascular Disease: A ‘’Real-World’’ Analysis

Red cell distribution width (RDW) has been shown to predict adverse outcomes in specific scenarios. We aimed to assess the association between RDW and all-cause death and a clinically relevant composite endpoint in a population with various clinical manifestations of cardiovascular diseases. We retrospectively analyzed 700 patients (median age 72.7 years [interquartile range, IQR, 62.6–80]) admitted to the Cardiology ward between January and November 2016. Patients were divided into tertiles according to baseline RDW values. After a median follow-up of 3.78 years (IQR 3.38–4.03), 153 (21.9%) patients died and 247 (35.3%) developed a composite endpoint (all-cause death, acute coronary syndromes, transient ischemic attack/stroke, and/or thromboembolic events). With multivariate Cox regression analysis, the highest RDW tertile was independently associated with an increased risk of all-cause death (adjusted hazard ratio [HR] 2.73, 95% confidence interval [CI] 1.63–4.56) and of the composite endpoint (adjusted HR 2.23, 95% CI 1.53–3.24). RDW showed a good predictive ability for all-cause death (C-statistics: 0.741, 95% CI 0.694–0.788). In a real-world cohort of patients, we found that higher RDW values were independently associated with an increased risk of all-cause death and clinical adverse cardiovascular events thus proposing RDW as a prognostic marker in cardiovascular patients

A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ∼30 000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ∼200 virtual screenings of compound libraries on selected protein structures, we redefine the protein’s druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites

A Blueprint for High Affinity SARS-CoV2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ∼30 000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ∼200 virtual screenings of compound libraries on selected protein structures, we redefine the protein’s druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites

A community effort to discover small molecule SARS-CoV-2 inhibitors

The 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 a 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 potentially active 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 activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (Nsp12 domain), and (alpha) spike protein S. Overall, 27 potential inhibitors were experimentally confirmed by binding-, cleavage-, and/or viral suppression assays and are presented here. All results are freely available and can be taken further downstream without IP restrictions. Overall, we show the effectiveness of computational techniques, community efforts, and communication across research fields (i.e., protein expression and crystallography, in silico modeling, synthesis and biological assays) to accelerate the early phases of drug discovery