The recent pandemic outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), raised global health and economic concerns. Phylogenetically, SARS-CoV-2 is closely related to SARS-CoV, and both encode the enzyme main protease (M/3CL), which can be a potential target inhibiting viral replication. Through this work, we have compiled the structural aspects of M conformational changes, with molecular modeling and 1-μs MD simulations. Long-scale MD simulation resolves the mechanism role of crucial amino acids involved in protein stability, followed by ensemble docking which provides potential compounds from the Traditional Chinese Medicine (TCM) database. These lead compounds directly interact with active site residues (His41, Gly143, and Cys145) of M, which plays a crucial role in the enzymatic activity. Through the binding mode analysis in the S1, S1', S2, and S4 binding subsites, screened compounds may be functional for the distortion of the oxyanion hole in the reaction mechanism, and it may lead to the inhibition of M in SARS-CoV-2. The hit compounds are naturally occurring compounds; they provide a sustainable and readily available option for medical treatment in humans infected by SARS-CoV-2. Henceforth, extensive analysis through molecular modeling approaches explained that the proposed molecules might be promising SARS-CoV-2 inhibitors for the inhibition of COVID-19, subjected to experimental validation.
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http://dx.doi.org/10.3389/fchem.2020.595273 | DOI Listing |
Sci Rep
January 2025
Department of Molecular Genetics and Infection Biology, University of Greifswald, 17489, Greifswald, Germany.
In recent years, increased numbers of severe Streptococcus dysgalactiae subsp. equisimilis (SDSE) infections, including necrotizing soft tissue infections (NSTIs), have been reported. One of the main virulence factors of SDSE is streptokinase (Ska).
View Article and Find Full Text PDFBiochemistry
January 2025
Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States.
In the wake of the pandemic, peptidyl protease inhibitors with Pro-based rigid Leu mimetics at the P position have emerged as potent drug candidates against the SARS-CoV-2 main protease. This success is intuitively attributed to the enhanced hydrophobic interactions and rigidity of Pro-based rigid Leu mimetics in the literature. However, the tertiary amide of proline P derivatives, which hinders the formation of a critical hydrogen bond with the enzyme active site, and the constrained PP conformation, which contradicts the protease preferred β-strand conformation, represent two overlooked disadvantages associated with these inhibitors over traditional inhibitors and, theoretically, should adversely affect their potency.
View Article and Find Full Text PDFPNAS Nexus
January 2025
Department of Refractory Viral Diseases, National Center for Global Health and Medicine Research Institute, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan.
We identified a 5-fluoro-benzothiazole-containing small molecule, TKB272, through fluorine-scanning of the benzothiazole moiety, which more potently inhibits the enzymatic activity of SARS-CoV-2's main protease (M) and more effectively blocks the infectivity and replication of all SARS-CoV-2 strains examined including Omicron variants such as SARS-CoV-2 and SARS-CoV-2 than two M inhibitors: nirmatrelvir and ensitrelvir. Notably, the administration of ritonavir-boosted nirmatrelvir and ensitrelvir causes drug-drug interactions warranting cautions due to their CYP3A4 inhibition, thereby limiting their clinical utility. When orally administered, TKB272 blocked SARS-CoV-2 replication without ritonavir in B6.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA, United States.
Introduction: Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training.
View Article and Find Full Text PDFSci Rep
January 2025
International Joint Research Laboratory for Perception Data Intelligent Processing of Henan, Anyang Normal University, Anyang, 455000, China.
Deconvoluting drug targets is crucial in modern drug development, yet both traditional and artificial intelligence (AI)-driven methods face challenges in terms of completeness, accuracy, and efficiency. Identifying drug targets, especially within complex systems such as the p53 pathway, remains a formidable task. The regulation of this pathway by myriad stress signals and regulatory elements adds layers of complexity to the discovery of effective p53 pathway activators.
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