AIMC Topic: Protease Inhibitors

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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...
Antiviral Agents COVID-19 SARS-CoV-2 Molecular Dynamics Simulation Molecular Docking Simulation Protease Inhibitors Humans COVID-19 Drug Treatment Drug Discovery Coronavirus 3C Proteases Machine Learning Coronavirus Papain-Like Proteases Cysteine Proteinase Inhibitors
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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...
Humans Mutation Molecular Dynamics Simulation Drug Resistance, Viral Protease Inhibitors Machine Learning COVID-19 SARS-CoV-2 Antiviral Agents Coronavirus 3C Proteases
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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 ...
Coronavirus 3C Proteases Molecular Dynamics Simulation Catalytic Domain Middle East Respiratory Syndrome Coronavirus Protease Inhibitors Molecular Docking Simulation Humans Drug Discovery Machine Learning Antiviral Agents
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Enhancing HCV NS3 Inhibitor Classification with Optimized Molecular Fingerprints Using Random Forest.

International journal of molecular sciences Mar 17, 2025
The classification of Hepatitis C virus (HCV) NS3 inhibitors is essential for identifying potential antiviral agents through computational methods. This study aims to develop an optimized machine learning (ML) model using random forest (RF) and molec...
DEAD-box RNA Helicases Viral Proteases Nucleoside-Triphosphatase Serine Endopeptidases Viral Nonstructural Proteins Protease Inhibitors Humans Machine Learning Drug Discovery Antiviral Agents Random Forest Hepacivirus
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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...
Antiviral Agents Structure-Activity Relationship Pyrazoles Protease Inhibitors Combinatorial Chemistry Techniques SARS-CoV-2 Coronavirus 3C Proteases Molecular Docking Simulation Humans Drug Design Deep Learning
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Applications of Machine Learning Approaches for the Discovery of SARS-CoV-2 PLpro Inhibitors.

Journal of chemical information and modeling Jan 16, 2025
The global impact of SARS-CoV-2 highlights the need for treatments beyond vaccination, given the limited availability of effective medications. While Pfizer introduced , an FDA-approved antiviral targeting the SARS-CoV-2 main protease (Mpro), this st...
Molecular Docking Simulation Drug Discovery Antiviral Agents COVID-19 Drug Treatment High-Throughput Screening Assays Protease Inhibitors Small Molecule Libraries Humans Coronavirus 3C Proteases Machine Learning Coronavirus Papain-Like Proteases SARS-CoV-2
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Generative adversarial network (GAN) model-based design of potent SARS-CoV-2 M inhibitors using the electron density of ligands and 3D binding pockets: insights from molecular docking, dynamics simulation, and MM-GBSA analysis.

Molecular diversity Nov 30, 2024
Deep learning-based generative adversarial network (GAN) frameworks have recently been developed to expedite the drug discovery process. These models generate novel molecules from scratch and validate them through molecular docking simulation to iden...
Molecular Docking Simulation Drug Design Deep Learning Antiviral Agents Humans COVID-19 SARS-CoV-2 Binding Sites Protease Inhibitors Coronavirus 3C Proteases Generative Adversarial Networks Protein Binding Molecular Dynamics Simulation Ligands COVID-19 Drug Treatment
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Machine-Learning Approach to Identify Potential Dengue Virus Protease Inhibitors: A Computational Perspective.

The journal of physical chemistry. B Nov 1, 2024
The global prevalence of dengue virus (DENV), a widespread flavivirus, has led to varied epidemiological impacts, economic burdens, and health consequences. The alarming increase in infections is exacerbated by the absence of approved antiviral agent...
Viral Protease Inhibitors Thermodynamics Protease Inhibitors Viral Proteases Antiviral Agents Molecular Dynamics Simulation Machine Learning Dengue Virus Serine Endopeptidases
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A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods.

SAR and QSAR in environmental research Jul 30, 2024
The 3C-like Proteinase (3CLpro) of novel coronaviruses is intricately linked to viral replication, making it a crucial target for antiviral agents. In this study, we employed two fingerprint descriptors (ECFP_4 and MACCS) to comprehensively character...
Antiviral Agents Support Vector Machine Quantitative Structure-Activity Relationship Protease Inhibitors Machine Learning COVID-19 SARS-CoV-2 Cysteine Endopeptidases Betacoronavirus Coronavirus 3C Proteases
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Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

Bioorganic & medicinal chemistry letters Jun 24, 2024
The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (M). The ligand-bi...
Molecular Dynamics Simulation SARS-CoV-2 Catalytic Domain Drug Design Humans Quantitative Structure-Activity Relationship Antiviral Agents Isoindoles Machine Learning Azoles Organoselenium Compounds COVID-19 Protease Inhibitors Coronavirus 3C Proteases
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