AIMC Topic: Coronavirus 3C Proteases

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AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

International journal of molecular sciences Apr 29, 2023
Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs use...
Models, Molecular COVID-19 Drug Treatment Small Molecule Libraries Coronavirus 3C Proteases Neural Networks, Computer Artificial Intelligence Drug Discovery
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Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds.

Molecular diversity Feb 24, 2023
To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of S...
Biological Products Molecular Dynamics Simulation COVID-19 Drug Treatment Protease Inhibitors Humans Machine Learning COVID-19 Coronavirus 3C Proteases SARS-CoV-2 Molecular Docking Simulation Antiviral Agents
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Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen.

European journal of medicinal chemistry Oct 3, 2022
SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known SARS-CoV-2 3CL protease inhibitors act by covalently binding to the active site cysteine. Yet, computational screens against this enzyme were mainly f...
Humans Deep Learning Protease Inhibitors SARS-CoV-2 Antiviral Agents Coronavirus 3C Proteases COVID-19 Drug Treatment Cysteine
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Development of a deep learning-based quantitative structure-activity relationship model to identify potential inhibitors against the 3C-like protease of SARS-CoV-2.

Future medicinal chemistry Sep 30, 2022
In the recent COVID-19 pandemic, SARS-CoV-2 infection spread worldwide. The 3C-like protease (3CLpro) is a promising drug target for SARS-CoV-2. We constructed a deep learning-based convolutional neural network-quantitative structure-activity relat...
COVID-19 SARS-CoV-2 Molecular Docking Simulation Deep Learning Humans Pandemics Peptide Hydrolases Antiviral Agents Coronavirus 3C Proteases Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Protease Inhibitors
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Screening Anti-inflammatory, Anticoagulant, and Respiratory Agents for SARS-CoV-2 3CL Inhibition from Chemical Fingerprints Through a Deep Learning Approach.

Revista de investigacion clinica; organo del Hospital de Enfermedades de la Nutricion Jan 3, 2022
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), triggers a pathophysiological process linked not only to viral mechanisms of infectivity, but also to the pattern of...
Antiviral Agents Anticoagulants Anti-Inflammatory Agents COVID-19 Drug Treatment Humans SARS-CoV-2 Deep Learning Coronavirus 3C Proteases Respiratory System Agents
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Computational investigation of drug bank compounds against 3C-like protease (3CL) of SARS-CoV-2 using deep learning and molecular dynamics simulation.

Molecular diversity Oct 12, 2021
Blocking the main replicating enzyme, 3 Chymotrypsin-like protease (3CL) is the most promising drug development strategy against the SARS-CoV-2 virus, responsible for the current COVID-19 pandemic. In the present work, 9101 drugs obtained from the dr...
Coronavirus 3C Proteases Pandemics SARS-CoV-2 Molecular Docking Simulation Deep Learning Antiviral Agents Molecular Dynamics Simulation COVID-19 Drug Treatment Protease Inhibitors Humans
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Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.

BioMed research international May 25, 2021
A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world econom...
Protein Structure, Secondary Protein Interaction Domains and Motifs Coronavirus 3C Proteases Substrate Specificity Thermodynamics Protease Inhibitors Small Molecule Libraries Humans Neural Networks, Computer SARS-CoV-2 Molecular Docking Simulation Gene Expression Drug Design Kinetics Antiviral Agents COVID-19 Drug Treatment Protein Binding Catalytic Domain Biological Products
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Predicting cryptic ligand binding sites based on normal modes guided conformational sampling.

Proteins Dec 5, 2020
To greatly expand the druggable genome, fast and accurate predictions of cryptic sites for small molecules binding in target proteins are in high demand. In this study, we have developed a fast and simple conformational sampling scheme guided by norm...
Molecular Dynamics Simulation Hepacivirus Ligands Elasticity Protein Conformation Receptors, Cytoplasmic and Nuclear Binding Sites Coronavirus 3C Proteases Models, Statistical Regression Analysis Area Under Curve Antigens, CD ROC Curve Computational Biology Antigens, Neoplasm Interleukin-2 Machine Learning Coronavirus Papain-Like Proteases Humans Algorithms Karyopherins Reproducibility of Results Protein Tyrosine Phosphatase, Non-Receptor Type 1 SARS-CoV-2 Exportin 1 Protein
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Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.

Scientific reports Nov 23, 2020
COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SAR...
Drug Evaluation, Preclinical HIV-1 Humans COVID-19 Drug Treatment Cheminformatics Protease Inhibitors Anti-HIV Agents COVID-19 Coronavirus 3C Proteases SARS-CoV-2 Antiviral Agents Molecular Docking Simulation Infectious bronchitis virus Drug Repositioning Deep Learning Molecular Dynamics Simulation
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Profiling SARS-CoV-2 Main Protease (M) Binding to Repurposed Drugs Using Molecular Dynamics Simulations in Classical and Neural Network-Trained Force Fields.

ACS combinatorial science Oct 29, 2020
The current COVID-19 pandemic caused by a novel coronavirus SARS-CoV-2 urgently calls for a working therapeutic. Here, we report a computation-based workflow for efficiently selecting a subset of FDA-approved drugs that can potentially bind to the SA...
Catalytic Domain Protein Binding Neural Networks, Computer Coronavirus 3C Proteases Drug Repositioning Drug Discovery Coronavirus Protease Inhibitors Workflow Antiviral Agents Molecular Dynamics Simulation
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