Virtual screening combined with molecular docking for the !identification of new anti-adipogenic compounds.

IF 2.9 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Science Progress Pub Date : 2025-01-01 DOI:10.1177/00368504251320313
Gilberto Mandujano-Lázaro, María F Torres-Rojas, Esther Ramírez-Moreno, Laurence A Marchat
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Abstract

Obesity is an important risk factor for diabetes, cardiovascular diseases, and cancer, reducing the quality of life and expectancy of millions of people. Consequently, obesity has turned into one of the most health public problems worldwide, which highlights the urgent need for new and safe treatments. Obesity is mainly related to excessive fat accumulation; therefore, proteins participating in white adipose tissue increase and dysfunction are considered pertinent and attractive targets for developing new methods that can help with body weight control. In this context, virtual screening of libraries containing a large number of molecules represents a valuable strategy for the identification of potential anti-adipogenic compounds with reduced costs and time production. Here, we review the scientific literature about the prediction of new ligands of specific proteins through molecular docking and virtual screening of chemical libraries, with the aim of proposing new potential anti-adipogenic molecules. First, we present the targets related to adipogenesis and adipocyte functions that were selected for the following studies: PPARγ, Crif1, SIRT1, ERβ, PC1, FTO, Mss51, and FABP4. Then, we describe the obtention of new ligands according to the characteristics of the virtual screening approach, i.e. a structure-based drug design (SBDD) or a ligand-based drug design (LBDD). Finally, the critical analysis of these computational strategies and the corresponding results points out the necessity of combining computational and in vitro or in vivo assays for the identification of effective new anti-adipogenic molecules for obesity control. It also evidences that translating molecular docking and virtual screening results into successful drug candidates for adipogenesis and obesity control remains a huge challenge.

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虚拟筛选与分子对接相结合,鉴定新的抗脂肪生成化合物。
肥胖是糖尿病、心血管疾病和癌症的重要危险因素,降低了数百万人的生活质量和预期寿命。因此,肥胖已成为世界范围内最健康的公共问题之一,这突出表明迫切需要新的安全治疗方法。肥胖主要与脂肪堆积过多有关;因此,参与白色脂肪组织增加和功能障碍的蛋白质被认为是开发有助于控制体重的新方法的相关和有吸引力的目标。在这种情况下,包含大量分子的文库的虚拟筛选代表了一种有价值的策略,可以降低成本和生产时间,从而鉴定潜在的抗脂肪化合物。在此,我们回顾了通过分子对接和化学文库虚拟筛选来预测特定蛋白质新配体的科学文献,旨在提出新的潜在抗脂肪分子。首先,我们介绍了与脂肪形成和脂肪细胞功能相关的靶点,这些靶点被选择用于以下研究:PPARγ、Crif1、SIRT1、ERβ、PC1、FTO、Mss51和FABP4。然后,我们根据虚拟筛选方法的特点,即基于结构的药物设计(SBDD)或基于配体的药物设计(LBDD),描述了新配体的注意。最后,对这些计算策略和相应结果的批判性分析指出了将计算和体外或体内试验相结合的必要性,以确定有效的新型抗脂肪分子以控制肥胖。这也表明,将分子对接和虚拟筛选结果转化为脂肪形成和肥胖控制的成功候选药物仍然是一个巨大的挑战。
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来源期刊
Science Progress
Science Progress Multidisciplinary-Multidisciplinary
CiteScore
3.80
自引率
0.00%
发文量
119
期刊介绍: Science Progress has for over 100 years been a highly regarded review publication in science, technology and medicine. Its objective is to excite the readers'' interest in areas with which they may not be fully familiar but which could facilitate their interest, or even activity, in a cognate field.
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