Monkeypox is a zoonotic viral disease that mainly affects tropical rainforest regions of central and west Africa, with sporadic exportations to other places. Since there is no cure, treating monkeypox with an antiviral drug developed for smallpox is currently acceptable. Our study mainly focused on finding new therapeutics to target monkeypox from existing compounds or medications. It is a successful method for discovering or developing medicinal compounds with novel pharmacological or therapeutic applications. In this study, homology modelling developed the Monkeypox TMPK (IMNR) structure. Ligand-based pharmacophore was generated using the best docking pose of standard ticovirimat. Further, molecular docking analysis showed compounds, tetrahydroxycurcumin, procyanidin, rutin, vicenin-2, kaempferol 3-(6''-malonylglucoside) were the top five binding energy compounds against TMPK (1MNR). Furthermore, we carried out MD simulations for 100 ns for the six compounds, including reference based on the binding energies and interactions. MD studies revealed that as ticovirimat interacted with residues Lys17, Ser18, and Arg45, all the above five compounds interacted with the same amino acids at the active site during docking and simulation studies. Among all the compounds, ZINC4649679 (Tetrahydroxycurcumin) was shown to have the highest binding energy -9.7 kcal/mol and also observed stable protein-ligand complex during MD studies. ADMET profile estimation showed that the docked phytochemicals were safe. However, further biological assessment through a wet lab is essential to measure the efficacy and safety of the compounds.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2023.2188428 | DOI Listing |
J Cheminform
January 2025
Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, UK.
Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Sichuan University, Institute of New Energy and Low-Carbon Technology, CHINA.
Doping with non-metallic heteroatom is an effective approach to tailor the electronic structure of Ni for enhancing its alkaline hydrogen oxidation reaction (HOR) catalytic performance. However, the modulation of HOR activity of Ni by lattice carbon (LC) atoms has rarely been reported, especially to reveal the rule between the doping effect and activity caused by the content of LC atoms. Here, hydrogen is proposed as a scavenger for LC atoms in the pyrolytic reduction process to finely control the content of LC atoms in Ni.
View Article and Find Full Text PDFMethods Mol Biol
January 2025
Quantum-Si, Guilford, CT, USA.
Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique for studying the structural dynamics of protein molecules or detecting interactions between protein molecules in real time. Due to the high sensitivity in spatial and temporal resolution, smFRET can decipher sub-populations within heterogeneous native state conformations, which are generally lost in traditional measurements due to ensemble averaging. In addition, the single-molecule reconstitution allows protein molecules to be observed for an extensive period of time and can recapitulate the geometry of the cellular environment to retain biological function.
View Article and Find Full Text PDFJ Mol Neurosci
January 2025
Department of Biophysics, School of Life Sciences, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, is characterized by mitochondrial dysfunction and immune dysregulation. This study is aimed at developing a risk prediction model for AD by integrating multi-omics data and exploring the interplay between mitochondrial energy metabolism-related genes (MEMRGs) and immune cell dynamics. We integrated four GEO datasets (GSE132903, GSE29378, GSE33000, GSE5281) for differential gene expression analysis, functional enrichment, and weighted gene co-expression network analysis (WGCNA).
View Article and Find Full Text PDFThe quark-gluon plasma analysis relies on the heavy quark potential, which is influenced by the anisotropic plasma parameter temperature (t), and baryonic chemical potential (μ). Employing the generalized fractional derivative Nikiforov-Uvarov (GFD-NU) method, we solved the topologically-fractional Schrödinger equation. Two scenarios were explored: the classical model (α = β = 1) and the fractional model (α, β < 1).
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