AI meets physics in computational structure-based drug discovery for GPCRs.

NPJ drug discovery Pub Date : 2025-01-01 Epub Date: 2025-07-03 DOI:10.1038/s44386-025-00019-0
Mayako Michino, Jeremie Vendome, Irina Kufareva
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Abstract

G protein-coupled receptors (GPCRs) are a prominent class of therapeutic targets for which structure-based drug discovery (SBDD) has traditionally been challenging to apply. However, recent artificial intelligence (AI)-powered breakthroughs have opened new avenues. Here, we discuss the impact of computational models on hit discovery and lead optimization for GPCRs. We also provide best practices for generating and validating predictive models for prospective use.

人工智能在基于计算结构的gpcr药物发现中与物理学相结合。
G蛋白偶联受体(gpcr)是一类突出的治疗靶点,基于结构的药物发现(SBDD)传统上一直具有挑战性。然而,最近人工智能(AI)驱动的突破开辟了新的途径。在这里,我们讨论了计算模型对gpcr命中发现和先导优化的影响。我们还提供了生成和验证预测模型的最佳实践。
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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