Insilico evaluation on potential Mt-Sp1/matriptase inhibitors data: DFT and molecular modelling approaches

Nine heterocyclic compounds were investigated using density functional theory, molecular operating environment software, material studio, swissparam (Swiss drug design) software. In this work, the descriptors generated from the optimized compounds proved to be efficient and explain the level of reac...

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Bibliographic Details
Published in:Data in brief 2024-08, Vol.55, p.110565, Article 110565
Main Authors: Oyebamiji, Abel Kolawole, Akintelu, Sunday Adewale, Adekunle, David O, Oke, David Gbenga, Olanrewaju, Adesoji Alani, Akinola, Omowumi Temitayo
Format: Article
Language:English
Subjects:
Data
DFT
Docking
GFA
Inhibitors
Mt-Sp1/Matriptase
Target prediction
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Summary:Nine heterocyclic compounds were investigated using density functional theory, molecular operating environment software, material studio, swissparam (Swiss drug design) software. In this work, the descriptors generated from the optimized compounds proved to be efficient and explain the level of reactivity of the investigated compound. The developed quantitative structure activity relationship (QSAR) model was predictive and reliable. Also, compound 9 proved to be capable of inhibiting Mt-Sp1/Matriptase (pdb id: 1eax) than other examined heterocyclic compounds. Target prediction analysis was carried out on the compound with highest binding affinity (Compound 9) and the results were reported.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2024.110565