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Network Modeling Analysis in Health Informatics and Bioinformatics

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01.12.2019 | Original Article

Design and prediction of favorable substitution site in trifluorophenyl-substituted homopiperazine, pyrazoline, triazepane derivatives as dipeptidyl peptidase IV Inhibitors: HQSAR and docking studies

verfasst von: M. C. Sharma, S. Jain

Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics | Ausgabe 1/2019

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Abstract

In this study, hologram quantitative structure–activity relationship (HQSAR) and molecular docking studies were performed on a dataset of 108 trifluorophenyl homopiperazine, pyrazoline, and triazepane derivatives as dipeptidyl peptidase IV inhibitors. HQSAR model was obtained using atoms, connection, donor, and acceptor as fragment distinction parameters with fragment size (4–7) using components (q² = 0.738, r² = 0.962). Molecular docking study was performed to identify novel potent inhibitors and the important amino acid residues, which formed an interaction with compound 105, were Ser-631, His-741, Tyr-663, Glu-204, Arg-123 and Ala-655 with receptor. These models were used to design new compounds for homopiperazine, pyrazoline, triazepane analogs and the results obtained from this study could be useful for further investigations.

Vorheriger Artikel Using multiple network alignment for studying connectomes

Nächster Artikel Melanoma risk modeling from limited positive samples

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Titel: Design and prediction of favorable substitution site in trifluorophenyl-substituted homopiperazine, pyrazoline, triazepane derivatives as dipeptidyl peptidase IV Inhibitors: HQSAR and docking studies
verfasst von: M. C. Sharma
S. Jain
Publikationsdatum: 01.12.2019
Verlag: Springer Vienna
Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics / Ausgabe 1/2019
Print ISSN: 2192-6662
Elektronische ISSN: 2192-6670
DOI: https://doi.org/10.1007/s13721-019-0184-6

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