AIMC Topic: Coronavirus 3C Proteases

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A Comparative Study of Deep Learning and Classical Modeling Approaches for Protein-Ligand Binding Pose and Affinity Prediction in Coronavirus Main Proteases.

Journal of chemical information and modeling Dec 22, 2025
The accurate prediction of protein-ligand binding poses and affinities is central to structure-based drug design. In this study, we first benchmarked three distinct pose generation strategies for data sets from the ASAP Antiviral Challenge 2025: mole...
Humans SARS-CoV-2 Molecular Docking Simulation Deep Learning Protein Conformation Middle East Respiratory Syndrome Coronavirus Binding Sites Coronavirus 3C Proteases Antiviral Agents Protein Binding Ligands
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Fingerprint-Based Machine Learning for SARS-CoV-2 and MERS-CoV Inhibition: Highlighting the Potential of Bayesian Neural Networks.

Journal of chemical information and modeling Dec 10, 2025
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) are two important targets in current drug discovery, mainly due to the COVID-19 pandemic and the MERS-CoV outbreaks in recent yea...
Middle East Respiratory Syndrome Coronavirus Protease Inhibitors Coronavirus 3C Proteases Humans Neural Networks, Computer Machine Learning Antiviral Agents Bayes Theorem SARS-CoV-2 Drug Discovery
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Design of Carbon Nanotube Inhibitors for Main Proteinase of SARS-CoV-2: A Combined Deep Learning and Molecular Dynamics Simulation Study.

The journal of physical chemistry. B Nov 10, 2025
The rapid development of machine learning (ML) and deep learning (DL) methods provides new opportunities for innovative drug discovery. While these techniques are widely used in docking organic molecules (drugs) with protein, an evaluation of the per...
Humans SARS-CoV-2 Molecular Docking Simulation Drug Design Binding Sites Protease Inhibitors Coronavirus 3C Proteases Deep Learning Molecular Dynamics Simulation Nanotubes, Carbon
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Integrating Physics-Based Simulations with Data-Driven Deep Learning Represents a Robust Strategy for Developing Inhibitors Targeting the Main Protease.

Journal of chemical information and modeling Aug 6, 2025
The coronavirus main protease, essential for viral replication, is a well-validated antiviral target. Here, we present Deep-CovBoost, a computational pipeline integrating deep learning with free energy perturbation (FEP) simulations to guide the stru...
Deep Learning Antiviral Agents Molecular Dynamics Simulation Coronavirus 3C Proteases Thermodynamics Protease Inhibitors Humans SARS-CoV-2 Drug Design
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Ionic liquids and lysosomotropic detergents as inhibitors of the SARS-CoV-2 main protease: QSAR modeling, synthesis and biological testing.

Biochemical and biophysical research communications Jun 28, 2025
SARS-CoV-2 infection is highly contagious, prompting the World Health Organization to classify it as a global public health emergency. The virus has numerous potential hosts, which complicates efforts for effective prevention, diagnosis, and treatmen...
Antiviral Agents Ionic Liquids COVID-19 Drug Treatment Quantitative Structure-Activity Relationship Machine Learning COVID-19 SARS-CoV-2 Protease Inhibitors Coronavirus 3C Proteases Detergents Humans
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Discovery of SARS-CoV-2 papain-like protease inhibitors through machine learning and molecular simulation approaches.

Drug discoveries & therapeutics Jun 27, 2025
The papain-like protease (PLpro), a cysteine protease found in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), plays a crucial role in viral replication by cleaving the viral polyproteins and interfering with the host's innate immune re...
Coronavirus 3C Proteases Coronavirus Papain-Like Proteases Cysteine Proteinase Inhibitors SARS-CoV-2 Humans Machine Learning COVID-19 Drug Treatment Antiviral Agents Molecular Docking Simulation COVID-19 Protease Inhibitors Molecular Dynamics Simulation Drug Discovery
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In-silico study of approved drugs as potential inhibitors against 3CLpro and other viral proteins of CoVID-19.

PloS one Jun 25, 2025
The global pandemic, due to the emergence of COVID-19, has created a public health crisis. It has a huge morbidity rate that was never comprehended in the recent decades. Despite numerous efforts, potent antiviral drugs are lacking. Repurposing of dr...
COVID-19 Computer Simulation SARS-CoV-2 Protein Binding Spike Glycoprotein, Coronavirus Molecular Docking Simulation Antiviral Agents Humans Machine Learning Coronavirus Nucleocapsid Proteins Drug Repositioning COVID-19 Drug Treatment Coronavirus 3C Proteases
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Enhancing the understandings on SARS-CoV-2 main protease (M) mutants from molecular dynamics and machine learning.

International journal of biological macromolecules Apr 10, 2025
While star drugs like Paxlovid have shown remarkable performance in combating SARS-CoV-2, we still face serious challenges such as viral mutants and resistance. In this study, we employ a computational framework combining molecular dynamics (MD) simu...
Coronavirus 3C Proteases Molecular Dynamics Simulation Drug Resistance, Viral Protease Inhibitors COVID-19 SARS-CoV-2 Humans Antiviral Agents Machine Learning Mutation
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Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease.

International journal of molecular sciences Mar 26, 2025
In this study, we utilized machine learning techniques to identify potential inhibitors of the MERS-CoV 3CL protease. Among the models evaluated, the Random Forest (RF) algorithm exhibited the highest predictive performance, achieving an accuracy of ...
Molecular Dynamics Simulation Catalytic Domain Humans Middle East Respiratory Syndrome Coronavirus Molecular Docking Simulation Machine Learning Coronavirus 3C Proteases Protease Inhibitors Drug Discovery Antiviral Agents
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Rational design and synthesis of pyrazole derivatives as potential SARS-CoV-2 M inhibitors: An integrated approach merging combinatorial chemistry, molecular docking, and deep learning.

Bioorganic & medicinal chemistry Feb 3, 2025
The global impact of SARS-CoV-2 has highlighted the urgent need for novel antiviral therapies. This study integrates combinatorial chemistry, molecular docking, and deep learning to design, evaluate and synthesize new pyrazole derivatives as potentia...
Structure-Activity Relationship Drug Design Humans Pyrazoles Deep Learning Combinatorial Chemistry Techniques SARS-CoV-2 Protease Inhibitors Antiviral Agents Molecular Docking Simulation Coronavirus 3C Proteases
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