针对前列腺癌膜蛋白标记物的结构药物设计进展。

IF 6.5 2区医学 Q1 PHARMACOLOGY & PHARMACY

Drug Discovery Today Pub Date : 2024-08-03 DOI:10.1016/j.drudis.2024.104130

João P. Batista-Silva , Diana Gomes , Sérgio F. Sousa , Ângela Sousa , Luís A. Passarinha

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引用次数: 0

摘要

前列腺癌（PCa）是男性的主要癌症之一，由于缺乏合适的生物标志物或其调节剂，导致预后不良。膜蛋白（MPs）在前列腺癌的发生和发展过程中起着至关重要的作用，可以成为有吸引力的治疗靶点。然而，针对 MPs 的实验限制阻碍了有效的生物标记物和抑制剂的发现。为了克服这一障碍，计算方法可以产生结构洞察力并筛选出大量化合物库，从而加速先导物的鉴定和优化。在这篇综述中，我们探讨了计算机辅助药物设计（CADD）目前取得的突破，重点是针对最相关的膜结合型 PCa 生物标志物的基于结构的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Advances in structure-based drug design targeting membrane protein markers in prostate cancer

Prostate cancer (PCa) is one of the leading cancers in men and the lack of suitable biomarkers or their modulators results in poor prognosis. Membrane proteins (MPs) have a crucial role in the development and progression of PCa and can be attractive therapeutic targets. However, experimental limitations in targeting MPs hinder effective biomarker and inhibitor discovery. To overcome this barrier, computational methods can yield structural insights and screen large libraries of compounds, accelerating lead identification and optimization. In this review, we examine current breakthroughs in computer-aided drug design (CADD), with emphasis on structure-based approaches targeting the most relevant membrane-bound PCa biomarkers.

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来源期刊

Drug Discovery Today 医学-药学

CiteScore

14.80

自引率

2.70%

发文量

293

审稿时长

6 months

期刊介绍： Drug Discovery Today delivers informed and highly current reviews for the discovery community. The magazine addresses not only the rapid scientific developments in drug discovery associated technologies but also the management, commercial and regulatory issues that increasingly play a part in how R&D is planned, structured and executed. Features include comment by international experts, news and analysis of important developments, reviews of key scientific and strategic issues, overviews of recent progress in specific therapeutic areas and conference reports.