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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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