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PubMed Central
Other literature type . 2020
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https://dx.doi.org/10.60692/a6...
Other literature type . 2020
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Other literature type . 2020
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Identification of potential TNF-α inhibitors: from in silico to in vitro studies

تحديد مثبطات TNF - α المحتملة: من في السيليكو إلى الدراسات المختبرية
Authors: Komal Zia; Sajda Ashraf; Almas Jabeen; Maria Saeed; Mohammad Nur‐e‐Alam; Sarfaraz Ahmed; Adnan J. Al‐Rehaily; +1 Authors

Identification of potential TNF-α inhibitors: from in silico to in vitro studies

Abstract

AbstractTumor Necrosis Factor Alpha (TNF-α) is a pleiotropic pro-inflammatory cytokine. It act as central biological regulator in critical immune functions, but its dysregulation has been linked with a number of diseases. Inhibition of TNF-α has considerable therapeutic potential for diseases such as cancer, diabetes, and especially autoimmune diseases. Despite the fact that many small molecule inhibitors have been identified against TNF-α, no orally active drug has been reported yet which demand an urgent need of a small molecule drug against TNF-α. This study focuses on the development of ligand-based selective pharmacophore model to perform virtual screening of plant origin natural product database for the identification of potential inhibitors against TNF-α. The resultant hits, identified as actives were evaluated by molecular docking studies to get insight into their potential binding interaction with the target protein. Based on pharmacophore matching, interacting residues, docking score, more affinity towards TNF-α with diverse scaffolds five compounds were selected for in vitro activity study. Experimental validation led to the identification of three chemically diverse potential compounds with the IC50 32.5 ± 4.5 µM, 6.5 ± 0.8 µM and 27.4 ± 1.7 µM, respectively.

Keywords

Virtual screening, Drug Target Identification, THP-1 Cells, Immunology, Drug Evaluation, Preclinical, Docking (animal), Nursing, FOS: Health sciences, Biochemistry, Gene, Article, Computational biology, Inhibitory Concentration 50, In vitro, FOS: Chemical sciences, Biochemistry, Genetics and Molecular Biology, Humans, Computer Simulation, Molecular Biology, Biology, Heterocyclic Compounds for Drug Discovery, Pharmacology, Biological Activities of Triterpenoids and Saponins, Pharmacophore, Tumor Necrosis Factor-alpha, Tumor necrosis factor alpha, Drug discovery, FOS: Clinical medicine, Organic Chemistry, In silico, Regulator, Reproducibility of Results, Life Sciences, Molecular Docking Simulation, Chemistry, Computational Theory and Mathematics, Computer Science, Physical Sciences, Medicine, Biological Assay, Drug, Small molecule, Computational Methods in Drug Discovery

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
68
Top 1%
Top 10%
Top 1%
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gold