生物分子识别计算建模的挑战与前沿。

Q3 Biochemistry, Genetics and Molecular Biology QRB Discovery Pub Date : 2022-01-01 Epub Date: 2022-08-19 DOI:10.1017/qrd.2022.11
Jinan Wang, Apurba Bhattarai, Hung Nguyen Do, Yinglong Miao
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引用次数: 0

摘要

生物分子识别(包括小分子、肽和蛋白质与其目标受体的结合)在细胞功能中发挥着关键作用,并已成为治疗药物设计的目标。然而,生物分子的高度灵活性以及缓慢的结合和解离过程给计算建模带来了挑战。在此,我们回顾了为表征生物分子结合所面临的挑战和开发的计算方法,包括分子对接、分子动力学(MD)模拟(尤其是增强采样)和机器学习。为了在未来准确有效地表征生物分子的结合结构、机理、热力学和动力学,还需要进一步的改进。
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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Challenges and frontiers of computational modelling of biomolecular recognition.

Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modeling. Here, we review the challenges and computational approaches developed to characterize biomolecular binding, including molecular docking, Molecular Dynamics (MD) simulations (especially enhanced sampling) and Machine Learning. Further improvements are still needed in order to accurately and efficiently characterize binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.

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来源期刊
QRB Discovery
QRB Discovery Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
3.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
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