Browsing by Author "Amao FA"

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    Dataset on in-silico investigation on triazole derivatives via molecular modelling approach: A potential glioblastoma inhibitors
    (2021) Oyebamiji AK; Mutiu OA; Amao FA; Oyawoye OM; Oyedepo TA; Adeleke BB; Semire B
    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.
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    Dataset on theoretical bio-evaluation of 1,2,4-thiadiazole-1,2,4-triazole analogues against epidermal growth factor receptor kinase down regulating human lung cancer
    (2021) Oyebamiji AK; Akintelu SA; Amao OP; Kaka MO; Morakinyo AE; Amao FA; Semire B
    Data from eight 1,2,4-thiadiazole-1,2,4-triazole derivatives were used to observe the anti-epidermal growth factor receptor kinase activities of 1,2,4-thiadiazole-1,2,4-triazole analogues thereby reducing human lung cancer. The software used to achieve this work were Spartan 14, Pymol, mgltools_win32_1.5.6, Auto dock vina and biovia2019.ds2019client. Also, the developed QSAR model was developed using the screened descriptors so as to inspect the closeness between the experimental IC50 and the predicted IC50. More so, the binding affinity from 1,2,4-thiadiazole-1,2,4-triazole derivatives - epidermal growth factor receptor kinase complexes using molecular docking approach were reported. Also, the ADMET properties for selected compounds and proposed compounds with better binding affinity were reported.