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通过深度学习进行蛋白质设计。

Protein design via deep learning.

机构信息

School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing 210044, China.

School of Future Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China.

出版信息

Brief Bioinform. 2022 May 13;23(3). doi: 10.1093/bib/bbac102.

Abstract

Proteins with desired functions and properties are important in fields like nanotechnology and biomedicine. De novo protein design enables the production of previously unseen proteins from the ground up and is believed as a key point for handling real social challenges. Recent introduction of deep learning into design methods exhibits a transformative influence and is expected to represent a promising and exciting future direction. In this review, we retrospect the major aspects of current advances in deep-learning-based design procedures and illustrate their novelty in comparison with conventional knowledge-based approaches through noticeable cases. We not only describe deep learning developments in structure-based protein design and direct sequence design, but also highlight recent applications of deep reinforcement learning in protein design. The future perspectives on design goals, challenges and opportunities are also comprehensively discussed.

摘要

具有预期功能和特性的蛋白质在纳米技术和生物医药等领域很重要。从头设计蛋白质使得能够从无到有地生产以前从未见过的蛋白质,被认为是应对现实社会挑战的关键。最近将深度学习引入设计方法中,展现出变革性的影响,有望代表一个有前途和令人兴奋的未来方向。在这篇综述中,我们回顾了基于深度学习的设计程序的主要进展,并通过显著案例说明了它们与传统基于知识的方法相比的新颖性。我们不仅描述了基于结构的蛋白质设计和直接序列设计中的深度学习进展,还强调了深度强化学习在蛋白质设计中的最新应用。还全面讨论了设计目标、挑战和机遇的未来展望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0272/9116377/86d8ff1beb22/bbac102f1.jpg

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