Molecular descriptors and in silico studies of 4-((5-(decylthio)-4-methyl-4n-1,2,4-triazol-3-yl)methyl)morpholine as a potential drug for the treatment of fungal pathologies
{"title":"Molecular descriptors and in silico studies of 4-((5-(decylthio)-4-methyl-4n-1,2,4-triazol-3-yl)methyl)morpholine as a potential drug for the treatment of fungal pathologies","authors":"","doi":"10.1016/j.compbiolchem.2024.108206","DOIUrl":null,"url":null,"abstract":"<div><p>The article explores the polypharmacological profiling of 4-((5-(decylthio)-4-methyl-4H-1,2,4-triazole-3-yl)methyl)morpholine as a potential antimicrobial agent. The study utilized 15148 electronic pharmacophore models of organisms, ranked by the Tversky index. Detailed analysis revealed classical bonding patterns with selected enzymes, identifying key amino acid residues involved in complex formation. Protein target prediction was conducted through various stages using the Galaxy web service, including ligand structure creation, pharmacophore alignment, and target ranking. The activities of the molecules against 1G6C, 2W6O, 3G7F, 3OWU, 4IVR, and 4TZT proteins were compared. Docking studies with PyMOL and Discovery Studio Visualizer revealed binding to thymidine kinase, thiamine phosphate synthase, and biotin carboxylase with promising binding affinities. These interactions suggest potential antibacterial and antiviral effects, warranting further virtual screening and in-depth studies for the development of effective antimicrobial drugs. Calculations of the molecules were made with the gaussian package program. Calculations were made on the 6-31++g** basis set at B3LYP, HF, and M062X levels with Gaussian software. Afterwards, the 0–100 ns interaction of the molecule with the highest activity was examined.</p></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927124001944","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The article explores the polypharmacological profiling of 4-((5-(decylthio)-4-methyl-4H-1,2,4-triazole-3-yl)methyl)morpholine as a potential antimicrobial agent. The study utilized 15148 electronic pharmacophore models of organisms, ranked by the Tversky index. Detailed analysis revealed classical bonding patterns with selected enzymes, identifying key amino acid residues involved in complex formation. Protein target prediction was conducted through various stages using the Galaxy web service, including ligand structure creation, pharmacophore alignment, and target ranking. The activities of the molecules against 1G6C, 2W6O, 3G7F, 3OWU, 4IVR, and 4TZT proteins were compared. Docking studies with PyMOL and Discovery Studio Visualizer revealed binding to thymidine kinase, thiamine phosphate synthase, and biotin carboxylase with promising binding affinities. These interactions suggest potential antibacterial and antiviral effects, warranting further virtual screening and in-depth studies for the development of effective antimicrobial drugs. Calculations of the molecules were made with the gaussian package program. Calculations were made on the 6-31++g** basis set at B3LYP, HF, and M062X levels with Gaussian software. Afterwards, the 0–100 ns interaction of the molecule with the highest activity was examined.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.