Computational exploration of flavonoids from the genus Knema with anti-inflammatory potential

Author:

Salihu Abubakar1ORCID,Salleh Wan2ORCID,Ogunwa Tomisin3

Affiliation:

1. Department of Chemistry, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia + Department of Pure and Industrial Chemistry, Faculty of Natural and Applied Sciences, Umaru Musa Yar’adua University, Katsina, Nigeria

2. Department of Chemistry, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia

3. Centre for Biocomputing and Drug Design, Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria, and Department of Biochemistry, Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria

Abstract

Inflammation, a widespread biological process linked to various diseases, poses a significant global health challenge. Recent research targeting the development of new anti-inflammatory drugs has prioritized plant-derived compounds due to their cost-effectiveness and minimal side effects compared to synthetic drugs. Flavonoids, polyphenolic compounds in plants, show potential for treating inflammation-related diseases. This study evaluates the anti-inflammatory activity of flavonoids from the Knema genus, a member of the Myristicaceae family. We focused on inhibiting two pro-inflammatory proteins, human and murine interleukin-1B (IL-1) and human interleukin-6 (IL-6). Molecular docking and ADMET prediction identified sulfuretin and (-)-catechin with high binding affinity to IL-6, whereas 4'-hydroxy-7-methoxyflavanone and 7,2'-dihydroxy-6,8-dimethyl-4',5'-methylenedioxyflavan stably bind IL-6. Molecular interaction analyses revealed that hydrogen and pi-sigma bonds contribute to the interaction. Notably, these flavonoids exhibited affinities comparable to celecoxib. Our computational predictions support the suitability of these flavonoids as drug candidates, indicating their promise as natural anti-inflammatory agents capable of modulating pro-inflammatory signaling pathways.

Publisher

National Library of Serbia

Subject

General Chemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3