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(50) and observed IC(50) 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.
Dataset on in-silico investigation on triazole derivatives via molecular modelling approach: A potential glioblastoma inhibitors.
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作者:Oyebamiji Abel Kolawole, Mutiu Oluwatumininu Abosede, Amao Folake Ayobami, Oyawoye Olubukola Monisola, Oyedepo Temitope A, Adeleke Babatunde Benjamin, Semire Banjo
| 期刊: | Data in Brief | 影响因子: | 1.400 |
| 时间: | 2021 | 起止号: | 2020 Dec 30; 34:106703 |
| doi: | 10.1016/j.dib.2020.106703 | ||
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