Modeling Boltzmann-weighted structural ensembles of proteins using artificial intelligence–based methods

IF 6.1 2区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Current opinion in structural biology Pub Date : 2025-02-08 DOI:10.1016/j.sbi.2025.103000

Akashnathan Aranganathan , Xinyu Gu , Dedi Wang , Bodhi P. Vani , Pratyush Tiwary

引用次数: 0

Abstract

This review highlights recent advances in AI-driven methods for generating Boltzmann-weighted structural ensembles, which are crucial for understanding biomolecular dynamics and drug discovery. With the rise of deep learning models such as AlphaFold2, there has been a shift toward more accurate and efficient sampling of structural ensembles. The review discusses the integration of AI with traditional molecular dynamics techniques as well as experiments, the challenges of conformational sampling, and future directions for AI-driven research in structural biology, particularly in drug discovery and protein dynamics.

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利用基于人工智能的方法对蛋白质的玻尔兹曼加权结构集合进行建模

本文综述了人工智能驱动方法在生成玻尔兹曼加权结构集成方面的最新进展，这对于理解生物分子动力学和药物发现至关重要。随着像AlphaFold2这样的深度学习模型的兴起，人们已经转向更准确、更有效的结构集合采样。本文讨论了人工智能与传统分子动力学技术以及实验的整合，构象采样的挑战，以及人工智能驱动的结构生物学研究的未来方向，特别是在药物发现和蛋白质动力学方面。

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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来源期刊

Current opinion in structural biology 生物-生化与分子生物学

CiteScore

12.20

自引率

2.90%

发文量

179

审稿时长

6-12 weeks

期刊介绍： Current Opinion in Structural Biology (COSB) aims to stimulate scientifically grounded, interdisciplinary, multi-scale debate and exchange of ideas. It contains polished, concise and timely reviews and opinions, with particular emphasis on those articles published in the past two years. In addition to describing recent trends, the authors are encouraged to give their subjective opinion of the topics discussed. In COSB, we help the reader by providing in a systematic manner: 1. The views of experts on current advances in their field in a clear and readable form. 2. Evaluations of the most interesting papers, annotated by experts, from the great wealth of original publications. [...] The subject of Structural Biology is divided into twelve themed sections, each of which is reviewed once a year. Each issue contains two sections, and the amount of space devoted to each section is related to its importance. -Folding and Binding- Nucleic acids and their protein complexes- Macromolecular Machines- Theory and Simulation- Sequences and Topology- New constructs and expression of proteins- Membranes- Engineering and Design- Carbohydrate-protein interactions and glycosylation- Biophysical and molecular biological methods- Multi-protein assemblies in signalling- Catalysis and Regulation