Suppr超能文献

探索海洋来源的化合物:用于代谢疾病治疗的选择性己酮糖激酶 (KHK) 抑制剂的计算发现。

Exploring Marine-Derived Compounds: In Silico Discovery of Selective Ketohexokinase (KHK) Inhibitors for Metabolic Disease Therapy.

机构信息

Department of Pharmaceutical Chemistry, College of Clinical Pharmacy, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.

出版信息

Mar Drugs. 2024 Oct 3;22(10):455. doi: 10.3390/md22100455.

Abstract

The increasing prevalence of metabolic diseases, including nonalcoholic fatty liver disease (NAFLD), obesity, and type 2 diabetes, poses significant global health challenges. Ketohexokinase (KHK), an enzyme crucial in fructose metabolism, is a potential therapeutic target due to its role in these conditions. This study focused on the discovery of selective KHK inhibitors using in silico methods. We employed structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches, beginning with molecular docking to identify promising compounds, followed by induced-fit docking (IFD), molecular mechanics generalized Born and surface area continuum solvation (MM-GBSA), and molecular dynamics (MD) simulations to validate binding affinities. Additionally, shape-based screening was conducted to assess structural similarities. The findings highlight several potential inhibitors with favorable ADMET profiles, offering promising candidates for further development in the treatment of fructose-related metabolic disorders.

摘要

代谢疾病(包括非酒精性脂肪肝疾病、肥胖症和 2 型糖尿病)的发病率不断上升,对全球健康构成了重大挑战。在果糖代谢中起关键作用的酶——己酮糖激酶(KHK),因其在这些病症中的作用,成为了一个有潜力的治疗靶点。本研究旨在通过计算方法发现选择性 KHK 抑制剂。我们采用基于结构的药物设计(SBDD)和基于配体的药物设计(LBDD)方法,从分子对接开始识别有前途的化合物,然后进行诱导契合对接(IFD)、分子力学广义 Born 和表面面积连续溶剂化(MM-GBSA)以及分子动力学(MD)模拟以验证结合亲和力。此外,还进行了基于形状的筛选,以评估结构相似性。这些发现突出了几种具有良好 ADMET 特性的潜在抑制剂,为进一步开发治疗果糖相关代谢紊乱的药物提供了有前景的候选物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1de2/11509851/f2f7b50b903f/marinedrugs-22-00455-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验