In silico study to identify novel potential thiadiazole-based molecules as anti-Covid-19 candidates by hierarchical virtual screening and molecular dynamics simulations
Copyright policy )In silico study to identify novel potential thiadiazole-based molecules as anti-Covid-19 candidates by hierarchical virtual screening and molecular dynamics simulations
AbstractIn the present study, a new category of 1,3,4-thiadiazoles was developed by submitting methyl 2-(4-hydroxy-3-methoxybenzylidene) hydrazine-1-carbodithioate to react with the appropriate hydrazonoyl halides in presence of few drops of diisopropyl ethyl amine. The chemical structures of the newly synthesized derivatives were inferred by means of their micro-analytical and spectral data. Utilizing combined molecular docking and molecular dynamics techniques, the binding affinities and features of the synthesized compounds were evaluated against four SARS-CoV-2 target enzymes, namely, main protease (Mpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), and receptor-binding domain (RBD) of the spike protein. Compound 7 demonstrated promising binding affinities with the target enzymes Mpro, PLpro, RdRp, and RBD with docking scores of −11.4, −9.4, −8.2, and −6.8 kcal/mol, respectively. In addition, compound 7 exhibited MM-GBSA//100 ns MD docking score of −35.9 kcal/mol against Mpro. Structural and energetic analyses revealed the stability of the 7-Mpro complex over 100 ns MD simulations. In addition, compound 7 obeyed Lipinski’s rule of five, as it has acceptable absorption, distribution, and oral bioavailability inside the body. Therefore, compound 7 is considered as a promising starting point for designing potential therapeutic agents against Covid-19.
- South Valley University Zambia
- South Valley University Egypt
- National Research Centre Egypt
Virtual screening, Binding affinities, Computational chemistry, Docking (animal), Organic chemistry, Combinatorial chemistry, Nursing, Molecular dynamics, FOS: Health sciences, Biochemistry, Gene, Global Burden of Leishmaniasis Incidence and Treatment, FOS: Chemical sciences, Stereochemistry, Health Sciences, Imidazole, Heterocyclic Compounds for Drug Discovery, Original Research, Organic Chemistry, In silico, Public Health, Environmental and Occupational Health, Molecule, Protease, Chemistry, Thiazoles, Computational Theory and Mathematics, Lipinski's rule of five, RNA polymerase, Enzyme, Computer Science, Physical Sciences, Medicine, RNA, Computational Methods in Drug Discovery, Receptor
Virtual screening, Binding affinities, Computational chemistry, Docking (animal), Organic chemistry, Combinatorial chemistry, Nursing, Molecular dynamics, FOS: Health sciences, Biochemistry, Gene, Global Burden of Leishmaniasis Incidence and Treatment, FOS: Chemical sciences, Stereochemistry, Health Sciences, Imidazole, Heterocyclic Compounds for Drug Discovery, Original Research, Organic Chemistry, In silico, Public Health, Environmental and Occupational Health, Molecule, Protease, Chemistry, Thiazoles, Computational Theory and Mathematics, Lipinski's rule of five, RNA polymerase, Enzyme, Computer Science, Physical Sciences, Medicine, RNA, Computational Methods in Drug Discovery, Receptor
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