| Literature DB >> 33457478 |
Abel Kolawole Oyebamiji1,2, Oluwatumininu Abosede Mutiu3, Folake Ayobami Amao4, Olubukola Monisola Oyawoye5, Temitope A Oyedepo6, Babatunde Benjamin Adeleke7, Banjo Semire2.
Abstract
In this work, ten molecular compounds were optimised using density functional theory (DFT) method via Spartan 14. The obtained descriptors were used to develop quantitative structural activities relationship (QSAR) model using Gretl and Matlab software and the similarity between predicted IC50 and observed IC50 was investigated. Also, docking study revealed the non-bonding interactions between the studied compounds and the receptor. The molecular interactions between the observed ligands and brain cancer protein (PDB ID: 1q7f) were investigated. Adsorption, distribution, metabolism, excretion and toxicity (ADMET) properties were also investigated.Entities:
Keywords: ADMET; DFT; Docking; Glioblastoma; In-silico; Inhibitors; QSAR; Triazole
Year: 2020 PMID: 33457478 PMCID: PMC7797363 DOI: 10.1016/j.dib.2020.106703
Source DB: PubMed Journal: Data Brief ISSN: 2352-3409