β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (M) that plays an indispensable role in viral replication. The availability of over 270 M X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV M. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three M enzymes with a single pan inhibitor.
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http://dx.doi.org/10.1021/acs.jcim.1c00449 | DOI Listing |
Comput Struct Biotechnol J
December 2024
Department of Electrical Engineering and Computer Science, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
More than 50 % of proteins bind to metal ions. Interactions between metal ions and proteins, especially coordinated interactions, are essential for biological functions, such as maintaining protein structure and signal transport. Physiological metal-ion binding prediction is pivotal for both elucidating the biological functions of proteins and for the design of new drugs.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
G protein-coupled receptors (GPCRs) play essential roles in numerous physiological processes and are key targets for drug development. Among them, adhesion GPCRs (aGPCRs) stand out for their unique domain structures and diverse functions. ADGRG2 is a member of the aGPCR family and is involved in the regulation of various systems in the human body, including reproductive, nervous, cardiovascular, and endocrine systems.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210.
The homo-dodecameric ring-shaped RNA binding attenuation protein (TRAP) from binds up to twelve tryptophan ligands (Trp) and becomes activated to bind a specific sequence in the 5' leader region of the operon mRNA, thereby downregulating biosynthesis of Trp. Thermodynamic measurements of Trp binding have revealed a range of cooperative behavior for different TRAP variants, even if the averaged apparent affinities for Trp have been found to be similar. Proximity between the ligand binding sites, and the ligand-coupled disorder-to-order transition has implicated nearest-neighbor interactions in cooperativity.
View Article and Find Full Text PDFPhys Chem Chem Phys
January 2025
Center for Advanced Materials Research, Beijing Normal University at Zhuhai, Zhuhai, 519087, China.
Understanding the molecular mechanism of inhibitor binding to prostate-specific membrane antigen (PSMA) is of fundamental importance for designing targeted drugs for prostate cancer. Here we designed a series of PSMA-targeting inhibitors with distinct molecular structures, which were synthesized and characterized using both experimental and computational approaches. Microsecond molecular dynamics simulations revealed the structural and thermodynamic details of PSMA-inhibitor interactions.
View Article and Find Full Text PDFJ Med Chem
January 2025
Hangzhou Carbonsilicon AI Technology Company Limited, Hangzhou 310018, Zhejiang, China.
Applying artificial intelligence techniques to flexibly model the binding between the ligand and protein has attracted extensive interest in recent years, but their applicability remains improved. In this study, we have developed CarsiDock-Flex, a novel two-step flexible docking paradigm that generates binding poses directly from predicted structures. CarsiDock-Flex consists of an equivariant deep learning-based model termed CarsiInduce to refine ESMFold-predicted protein pockets with the induction of specific ligands and our existing CarsiDock algorithm to redock the ligand into the induced binding pockets.
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