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通过分子建模方法对三唑衍生物的研究数据集：潜在的胶质母细胞瘤抑制剂。

Dataset on investigation on triazole derivatives via molecular modelling approach: A potential glioblastoma inhibitors.

作者信息

Oyebamiji Abel Kolawole, Mutiu Oluwatumininu Abosede, Amao Folake Ayobami, Oyawoye Olubukola Monisola, Oyedepo Temitope A, Adeleke Babatunde Benjamin, Semire Banjo

机构信息

Department of Basic Sciences, Adeleke University, P.M.B. 250, Ede, Osun State, Nigeria.

Computational Chemistry Laboratory, Department of Pure and Applied Chemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Oyo State, Nigeria.

出版信息

Data Brief. 2020 Dec 30;34:106703. doi: 10.1016/j.dib.2020.106703. eCollection 2021 Feb.

DOI:10.1016/j.dib.2020.106703
PMID:33457478
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7797363/
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.

摘要

在本研究中，通过Spartan 14软件利用密度泛函理论（DFT）方法对十种分子化合物进行了优化。所得描述符用于使用Gretl和Matlab软件建立定量构效关系（QSAR）模型，并研究预测的IC与观察到的IC之间的相似性。此外，对接研究揭示了所研究化合物与受体之间的非键相互作用。研究了观察到的配体与脑癌蛋白（PDB ID：1q7f）之间的分子相互作用。还研究了吸附、分布、代谢、排泄和毒性（ADMET）特性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ddb/7797363/e266b9e11749/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ddb/7797363/5ba6cdd4df04/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ddb/7797363/e266b9e11749/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ddb/7797363/5ba6cdd4df04/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ddb/7797363/e266b9e11749/gr2.jpg

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