Toulouse Biotechnology Institute, TBI, CNRS, INRAE, INSA, ANITI, Toulouse 31400, France.
Laboratoire d'Analyse et d'Architecture des Systèmes, LAAS CNRS, Université de Toulouse, CNRS, Toulouse 31400, France.
Protein Eng Des Sel. 2021 Feb 15;34. doi: 10.1093/protein/gzab011.
Computational protein design (CPD) is a powerful technique for engineering new proteins, with both great fundamental implications and diverse practical interests. However, the approximations usually made for computational efficiency, using a single fixed backbone and a discrete set of side chain rotamers, tend to produce rigid and hyper-stable folds that may lack functionality. These approximations contrast with the demonstrated importance of molecular flexibility and motions in a wide range of protein functions. The integration of backbone flexibility and multiple conformational states in CPD, in order to relieve the inaccuracies resulting from these simplifications and to improve design reliability, are attracting increased attention. However, the greatly increased search space that needs to be explored in these extensions defines extremely challenging computational problems. In this review, we outline the principles of CPD and discuss recent effort in algorithmic developments for incorporating molecular flexibility in the design process.
计算蛋白质设计(CPD)是一种强大的工程新蛋白质的技术,具有重要的基础意义和广泛的实际应用。然而,为了计算效率而通常进行的近似处理,使用单一固定的骨架和离散的侧链构象旋转,往往会产生刚性和超稳定的折叠,可能缺乏功能。这些近似处理与分子灵活性和运动在广泛的蛋白质功能中所表现出的重要性形成对比。在 CPD 中整合骨架灵活性和多种构象状态,以减轻这些简化所导致的不准确性并提高设计可靠性,正引起越来越多的关注。然而,在这些扩展中需要探索的大大增加的搜索空间定义了极其具有挑战性的计算问题。在这篇综述中,我们概述了 CPD 的原理,并讨论了最近在算法开发方面的努力,以将分子灵活性纳入设计过程中。