AIMC Topic: Protease 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 Machine Learning COVID-19 Molecular Dynamics Simulation Drug Resistance, Viral Protease Inhibitors Coronavirus 3C Proteases SARS-CoV-2 Antiviral Agents Mutation
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A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.

European journal of medicinal chemistry Apr 5, 2025
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituent optimization, a process that is often both time-consuming and expensive. To address this challenge...
Coronavirus 3C Proteases Molecular Structure COVID-19 Drug Treatment Protease Inhibitors Humans Antiviral Agents COVID-19 Structure-Activity Relationship Drug Discovery SARS-CoV-2 Deep Learning
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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 ...
Antiviral Agents Molecular Dynamics Simulation Catalytic Domain Middle East Respiratory Syndrome Coronavirus Machine Learning Molecular Docking Simulation Drug Discovery Protease Inhibitors Coronavirus 3C Proteases Humans
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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...
Machine Learning Drug Discovery Antiviral Agents Random Forest Humans Hepacivirus Serine Endopeptidases Viral Nonstructural Proteins Viral Proteases Nucleoside-Triphosphatase Protease Inhibitors DEAD-box RNA Helicases
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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 Coronavirus 3C Proteases Protease Inhibitors SARS-CoV-2 Combinatorial Chemistry Techniques Molecular Docking Simulation Drug Design Humans 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...
Coronavirus 3C Proteases Coronavirus Papain-Like Proteases Molecular Docking Simulation Drug Discovery Humans Protease Inhibitors Antiviral Agents Machine Learning Small Molecule Libraries COVID-19 Drug Treatment SARS-CoV-2 High-Throughput Screening Assays
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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...
Machine Learning Dengue Virus Serine Endopeptidases Antiviral Agents Viral Protease Inhibitors Molecular Dynamics Simulation Thermodynamics Protease Inhibitors Viral Proteases
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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...
Betacoronavirus Coronavirus 3C Proteases Support Vector Machine Quantitative Structure-Activity Relationship Protease Inhibitors Cysteine Endopeptidases COVID-19 SARS-CoV-2 Antiviral Agents Machine Learning
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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...
Drug Design Antiviral Agents Azoles Humans Molecular Dynamics Simulation Machine Learning Organoselenium Compounds Catalytic Domain COVID-19 Coronavirus 3C Proteases Protease Inhibitors Quantitative Structure-Activity Relationship SARS-CoV-2 Isoindoles
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Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network.

Journal of chemical information and modeling Mar 23, 2024
Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale b...
Deep Learning SARS-CoV-2 Coronavirus 3C Proteases Humans COVID-19 Drug Treatment Antiviral Agents Molecular Docking Simulation Neural Networks, Computer Protease Inhibitors Drug Discovery Protein Binding COVID-19
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