小柯机器人

中国科学技术大学刘海燕和陈泉等研究人员合作开发出一个用于蛋白质设计的神经网络能量函数。这一研究成果于2022年2月9日在线发表在国际学术期刊《自然》上。

研究人员表示，如果存在大量的氨基酸序列可以自主地折叠到一个蛋白质骨架结构中，那么这个结构就是可设计的。有人认为，骨架的可设计性主要由不依赖侧链或不依赖侧链类型的分子相互作用所支配，这表明设计新骨架（准备用于氨基酸选择）的方法是基于对骨架中心能量表面的连续采样和优化。然而，一个足够全面和精确的能量函数还没有为此目的而建立。

研究人员表明，这个目标可以通过一个名为SCUBA（代表侧链-未知骨架排列）的统计模型来实现，该模型使用神经网络形式的能量条件。这些条件是通过两步法学习的，包括核密度估计和神经网络训练，并能分析性地代表已知蛋白质结构中的多维、高阶关联性。研究人员报告了9个新蛋白质的晶体结构，这些蛋白质的骨架是用SCUBA高精度设计的，其中4个具有新颖的、非自然的整体结构。通过避免使用现有蛋白质结构的片段，SCUBA驱动的结构设计促进了对可设计骨架空间的深远探索，从而扩展了可进行重新设计蛋白质的新颖性和多样性。

附：英文原文

Title: A backbone-centred energy function of neural networks for protein design

Author: Huang, Bin, Xu, Yang, Hu, Xiuhong, Liu, Yongrui, Liao, Shanhui, Zhang, Jiahai, Huang, Chengdong, Hong, Jingjun, Chen, Quan, Liu, Haiyan

Issue&Volume: 2022-02-09

Abstract: A protein backbone structure is designable if a substantial number of amino acid sequences exist that autonomously fold into it1,2. It has been suggested that the designability of backbones is governed mainly by side chain-independent or side chain type-insensitive molecular interactions3,4,5, indicating an approach for designing new backbones (ready for amino acid selection) based on continuous sampling and optimization of the backbone-centred energy surface. However, a sufficiently comprehensive and precise energy function has yet to be established for this purpose. Here we show that this goal is met by a statistical model named SCUBA (for Side Chain-Unknown Backbone Arrangement) that uses neural network-form energy terms. These terms are learned with a two-step approach that comprises kernel density estimation followed by neural network training and can analytically represent multidimensional, high-order correlations in known protein structures. We report the crystal structures of nine de novo proteins whose backbones were designed to high precision using SCUBA, four of which have novel, non-natural overall architectures. By eschewing use of fragments from existing protein structures, SCUBA-driven structure design facilitates far-reaching exploration of the designable backbone space, thus extending the novelty and diversity of the proteins amenable to de novo design.

DOI: 10.1038/s41586-021-04383-5

Source: https://www.nature.com/articles/s41586-021-04383-5

Nature：《自然》，创刊于1869年。隶属于施普林格·自然出版集团，最新IF：69.504
官方网址：http://www.nature.com/
投稿链接：http://www.nature.com/authors/submit_manuscript.html