Cumulative global prevalence of the emergent monkeypox (MPX) infection in the non-endemic countries has been professed as a global public health predicament. Lack of effective MPX-specific treatments sets the baseline for designing the current study. This research work uncovers the effective use of known antiviral polyphenols against MPX viral infection, and recognises their mode of interaction with the target F13 protein, that plays crucial role in formation of enveloped virions. Herein, we have employed state-of-the-art machine learning based AlphaFold2 to predict the three-dimensional structure of F13 followed by molecular docking and all-atoms molecular dynamics (MD) simulations to investigate the differential mode of F13-polyphenol interactions. Our extensive computational approach identifies six potent polyphenols Rutin, Epicatechingallate, Catechingallate, Quercitrin, Isoquecitrin and Hyperoside exhibiting higher binding affinity towards F13, buried inside a positively charged binding groove. Intermolecular contact analysis of the docked and MD simulated complexes divulges three important residues Asp, Ser and Ser that are observed to be involved in ligand binding through hydrogen bonds. Our findings suggest that ligand binding induces minor conformational changes in F13 to affect the conformation of the binding site. Concomitantly, essential dynamics of the six-MD simulated complexes reveals Catechin gallate, a known antiviral agent as a promising polyphenol targeting F13 protein, dominated with a dense network of hydrophobic contacts. However, assessment of biological activities of these polyphenols need to be confirmed through in vitro and in vivo assays, which may pave the way for development of new novel antiviral drugs.
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http://dx.doi.org/10.1016/j.compbiolchem.2024.108070 | DOI Listing |
J Chem Inf Model
January 2025
Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1218 S 5th Ave, Monrovia, California 91016, United States.
Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical data sets. Concurrently, our ability to perform long-time scale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially.
View Article and Find Full Text PDFJ Cereb Blood Flow Metab
January 2025
A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
Zero echo time (zero-TE) pulse sequences provide a quiet and artifact-free alternative to conventional functional magnetic resonance imaging (fMRI) pulse sequences. The fast readouts (<1 ms) utilized in zero-TE fMRI produce an image contrast with negligible contributions from blood oxygenation level-dependent (BOLD) mechanisms, yet the zero-TE contrast is highly sensitive to brain function. However, the precise relationship between the zero-TE contrast and neuronal activity has not been determined.
View Article and Find Full Text PDFPhys Chem Chem Phys
January 2025
College of Chemistry and Chemical Engineering, State Key Laboratory of Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082, China.
Herein, the interfacial effects on calcium carbonate clustering within two-dimensional (2D) graphene nanochannels were systematically investigated using molecular dynamics simulations. The distribution characteristics of the ions at the interface can be attributed to the ordered water layers within the 2D nanochannels. The orientation of CO is approximately perpendicular to the interface, which can be attributed to hydrogen bonding and its association with Ca at the interface region.
View Article and Find Full Text PDFBioinform Adv
December 2024
Structural and Computational Biology Group, Nutritional and Industrial Biochemistry Research Unit, Department of Biochemistry, College of Medicine, University of Ibadan, Ibadan 200005, Nigeria.
Motivation: Investigating novel drug-target interactions is crucial for expanding the chemical space of emerging therapeutic targets in human diseases. Herein, we explored the interactions of dipeptidyl peptidase-4 and protein tyrosine phosphatase 1B with selected terpenoids from African antidiabetic plants.
Results: Using molecular docking, molecular dynamics simulations, molecular mechanics with generalized Born and surface area solvation-free energy, and density functional theory analyses, the study revealed dipeptidyl peptidase-4 as a promising target.
Front Vet Sci
January 2025
Jiangsu Agri-animal Husbandry Vocational College, Taizhou, Jiangsu, China.
Introduction: The H9N2 avian influenza virus is widely disseminated in poultry and poses a zoonotic threat, despite vaccination efforts. Mutations at residue 198 of hemagglutinin (HA) are critical for antigenic variation and receptor-binding specificity, but the underlying molecular mechanisms remain unclear. This study explores the molecular mechanisms by which mutations at the HA 198 site affect the antigenicity, receptor specificity, and binding affinity of the H9N2 virus.
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