Structural insight into TNF-α inhibitors through combining pharmacophore-based virtual screening and molecular dynamic simulation

Abstract

Tumor Necrosis Factor-alpha (TNF-α), a multifunctional cytokine responsible for providing resistance against infections, inflammation, and cancers. TNF-α has emerged as a promising drug target against several autoimmune and inflammatory disorders. Several synthetic antibodies (Infliximab, Etanercept, and Adalimumab) are available, but their potential to cause severe side effects has prompted them to develop alternative small molecules-based therapies for inhibition of TNF-α. In the present study, combined in silico approaches based on pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics studies were employed to understand significant direct interactions between TNF-α protein and small molecule inhibitors. Initially, four different small molecule libraries (∼17.5 million molecules) were virtually screened against the selected pharmacophore model. The identified hits were further subjected to molecular docking studies. The three potent lead compounds (ZINC05848961, ZINC09402309, ZINC04502991) were further subjected to 100 ns molecular dynamic studies to examine their stability. Our docking and molecular dynamic analysis revealed that the selected lead compounds target the TNF receptor (TNFR) and efficiently block the production of TNF. Moreover, in silico ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) analysis revealed that all the predicted compounds have good pharmacokinetic properties with high gastrointestinal absorption and a decent bioavailability score. Furthermore, toxicity profiles further evidenced that these compounds have no risk of being mutagenic, tumorigenic, reproductive and irritant except ZINC11915498. In conclusion, the present study could serve as the starting point to develop new therapeutic regimens to treat various TNF- related diseases.

Publication DOI: https://doi.org/10.1080/07391102.2020.1796794
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Biomolecular Structure and Dynamics on 24 July 2020, available online at: http://www.tandfonline.com/10.1080/07391102.2020.1796794
Uncontrolled Keywords: Autoimmunity,MD simulation,TNF receptor,docking,pharmacophore,Structural Biology,Molecular Biology
Publication ISSN: 1538-0254
Last Modified: 20 May 2024 07:35
Date Deposited: 04 Aug 2020 11:20
Full Text Link:
Related URLs: https://www.tan ... rnalCode=tbsd20 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021
Published Online Date: 2020-07-24
Accepted Date: 2020-07-06
Authors: Qaiser, Hina
Saeed, Maria
Nerukh, Dmitry (ORCID Profile 0000-0001-9005-9919)
Ul-Haq, Zaheer

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