Dataset on Investigation on Triazole Derivatives Via Molecular Modelling Approach: A Potential Glioblastoma Inhibitors

Overview

Journal Data Brief

Date 2021 Jan 18

PMID 33457478

Citations 3

Authors

Abel Kolawole Oyebamiji

Oluwatumininu Abosede Mutiu

Folake Ayobami Amao

Olubukola Monisola Oyawoye

Temitope A Oyedepo

Babatunde Benjamin Adeleke

Banjo Semire

Affiliations

Soon will be listed here.

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 IC and observed IC 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.

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