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Antimalarial phytochemicals as potential inhibitors of SARS-CoV-2 guanine N7-methyltransferase (nsp 14): an integrated computational approach.
Gyebi, Gideon A; Ogunyemi, Oludare M; Adefolalu, Adedotun A; López-Pastor, Juan F; Banegas-Luna, Antonio J; Rodríguez-Martínez, Alejandro; Pérez-Sánchez, Horacio; Adegunloye, Adegbenro P; Ogunro, Olalekan B; Afolabi, Saheed O; Baazeem, Alaa; Alotaibi, Saqer S; Batiha, Gaber El-Saber.
  • Gyebi GA; Department of Biochemistry, Bingham University, Karu, Nigeria.
  • Ogunyemi OM; Natural Products and Structural (Bio-Chem)-Informatics Research Laboratory (NpsBC-Rl), Bingham University, Karu, Nigeria.
  • Adefolalu AA; Human Nutraceuticals and Bioinformatics Research Unit, Department of Biochemistry, Salem University, Lokoja, Nigeria.
  • López-Pastor JF; Department of Biochemistry, Federal University of Lafia, Lafia, Nigeria.
  • Banegas-Luna AJ; Structural Bioinformatics and High-Performance Computing Research Group (BIO-HPC), Computer Engineering Department, Universidad Católica de Murcia (UCAM), Murcia, Spain.
  • Rodríguez-Martínez A; Structural Bioinformatics and High-Performance Computing Research Group (BIO-HPC), Computer Engineering Department, Universidad Católica de Murcia (UCAM), Murcia, Spain.
  • Pérez-Sánchez H; Structural Bioinformatics and High-Performance Computing Research Group (BIO-HPC), Computer Engineering Department, Universidad Católica de Murcia (UCAM), Murcia, Spain.
  • Adegunloye AP; Structural Bioinformatics and High-Performance Computing Research Group (BIO-HPC), Computer Engineering Department, Universidad Católica de Murcia (UCAM), Murcia, Spain.
  • Ogunro OB; Faculty of Life Sciences, Department of Biochemistry, University of Ilorin, Ilorin, Nigeria.
  • Afolabi SO; Department of Biological Sciences, KolaDaisi University, Ibadan, Nigeria.
  • Baazeem A; Faculty of Basic Medical Sciences, Department of Pharmacology and Therapeutics, University of Ilorin, Ilorin, Nigeria.
  • Alotaibi SS; Department of Biology, College of Science, Taif University, Taif, Saudi Arabia.
  • Batiha GE; Department of Biology, College of Science, Taif University, Taif, Saudi Arabia.
J Biomol Struct Dyn ; : 1-23, 2022 May 28.
Article in English | MEDLINE | ID: covidwho-20236420
ABSTRACT
The inhibition of capping enzymes such as guanine-N7-methyltransferase (GMT) is an attractive target for regulating viral replication, transcription, virulence, and pathogenesis. Thus, compounds that target the Severe Acute Respiratory Syndrome Corona Virus 2 GMT (S2GMT) will enhance drug development against COVID-19. In this study, an in-house library of 249 phytochemicals from African medicinal plants was screened using computational approaches including homology modeling, molecular docking, molecular dynamic simulations, binding free energy calculations based on molecular mechanics/Poisson-Boltzmann surface area (MMPBSA) and Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) analysis for inhibitors of S2GMT. The top-ten ranked phytochemicals (TTRP) obtained from the docking analysis to S2GMT were further docked to SARS-COV N7-MTase. Among the TTRP, the top-four ranked phytocompounds (TFRP) viz 3 alkaloids (Isocryptolepine, 10'-Hydroxyusambarensine and Isostrychnopentamine) and a flavonoid (Mulberrofuran F) interacted strongly with critical catalytic residues whose interference either reduce or completely abolish N7-MTase activity, indicating their potential as capping machinery disruptors. The interactions of TFRP with the catalytic residues of S2GMT were preserved in a 100 ns simulated dynamic environment, thereby, demonstrating high degree of structural stability. The MMPBSA binding free energy calculations corroborated the docking scores with biscryptolepine having the highest binding free energy to S2GMT. The TFRP showed favourable drug-likeness and ADMET properties over a wide range of molecular descriptors. Therefore, the TFRP can be further explored as potential S2GMT inhibitors in in vitro and in vivo experiments.Communicated by Ramaswamy H. Sarma.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Traditional medicine Language: English Journal: J Biomol Struct Dyn Year: 2022 Document Type: Article Affiliation country: 07391102.2022.2078408

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Traditional medicine Language: English Journal: J Biomol Struct Dyn Year: 2022 Document Type: Article Affiliation country: 07391102.2022.2078408