Rosetta Design Group LLC, Fairfax, VA 22030, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA.
Rosetta Design Group LLC, Fairfax, VA 22030, USA.
J Struct Biol. 2014 Feb;185(2):136-46. doi: 10.1016/j.jsb.2013.03.012. Epub 2013 Apr 1.
Computational protein design efforts aim to create novel proteins and functions in an automated manner and, in the process, these efforts shed light on the factors shaping natural proteins. The focus of these efforts has progressed from the interior of proteins to their surface and the design of functions, such as binding or catalysis. Here we examine progress in the development of robust methods for the computational design of non-natural interactions between proteins and molecular targets such as other proteins or small molecules. This problem is referred to as the de novo computational design of interactions. Recent successful efforts in de novo enzyme design and the de novo design of protein-protein interactions open a path towards solving this problem. We examine the common themes in these efforts, and review recent studies aimed at understanding the nature of successes and failures in the de novo computational design of interactions. While several approaches culminated in success, the use of a well-defined structural model for a specific binding interaction in particular has emerged as a key strategy for a successful design, and is therefore reviewed with special consideration.
计算蛋白质设计工作旨在以自动化的方式创造新的蛋白质和功能，在此过程中，这些工作揭示了塑造天然蛋白质的因素。这些工作的重点已经从蛋白质的内部发展到表面，并设计了新的功能，如结合或催化。在这里，我们检查了在计算设计蛋白质与分子靶标（如其他蛋白质或小分子）之间的非天然相互作用方面，开发稳健方法的进展。这个问题被称为相互作用的从头计算设计。最近在从头酶设计和从头设计蛋白质-蛋白质相互作用方面的成功努力为解决这个问题开辟了一条道路。我们研究了这些努力中的共同主题，并回顾了最近旨在了解相互作用从头计算设计中成功和失败的本质的研究。虽然几种方法最终都取得了成功，但在特定的结合相互作用中使用明确的结构模型尤其已成为成功设计的关键策略，因此特别考虑进行了审查。
