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Current Topics in Medicinal Chemistry

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ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

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Research Article

Ligand-Based Pharmacophore Modeling and Virtual Screening to Discover Novel CYP1A1 Inhibitors

Author(s): Rana Adnan Tahir, Farwa Hassan, Abdul Kareem, Umer Iftikhar and Sheikh Arslan Sehgal*

Volume 19, Issue 30, 2019

Page: [2782 - 2794] Pages: 13

DOI: 10.2174/1568026619666191112104217

Price: $65

Abstract

Backgound: Cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) is an imperative enzyme due to its immersion in the biotransformation of a wide range of drugs and other xenobiotics. The involvement of enzymes in drug metabolism indicates an effective drug target for the development of novel therapeutics. The discovery of CYP1A1 specific inhibitors would be of particular relevance for the clinical pharmacology.

Methods: In the current work, in silico approaches were utilized to identify the novel potential compounds through a diverse set of reported inhibitors against CYP1A1. A dataset of reported compounds against CYP1 belongs to 10 different classes (alkaloids, coumarins, flavonoids, natural compounds, synthetic inhibitors, drugs, MBI’s, PAHs, naphthoquinone and stilbenoids) was retrieved and utilized for the comparative molecular docking analyses followed by pharmacophore modeling. The total eleven novel compounds were scrutinized on the basis of the highest binding affinities and least binding energy values.

Results: ZINC08792486 compound attained the highest gold fitness score of 90.11 against CYP1A1 among all the scrutinized molecules.

Conclusion: It has been elucidated that the residues Phe-224, Gly-316 and Ala-317 were conserved in all ligand-receptor interactions and critical for the development of effective therapies. The ADMET property analyses also predict better absorption and distribution of the selected hits that may be used in the future for in vitro validations and drug development.

Keywords: Cytochromes P450, CYP1A1, Molecular Docking, Pharmacophore, Virtual Screening, ADMET, Bioinformatics.

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Graphical Abstract

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