LAAS-CNRS, Université de Toulouse, CNRS, 31400 Toulouse, France.
Centre de Biochimie Structurale. INSERM, CNRS, Université de Montpellier, 34090 Montpellier, France.
Molecules. 2019 Mar 22;24(6):1150. doi: 10.3390/molecules24061150.
Structural elements inserted in proteins are essential to define folding/unfolding mechanisms and partner recognition events governing signaling processes in living organisms. Here, we present an original approach to model the folding mechanism of these structural elements. Our approach is based on the exploitation of local, sequence-dependent structural information encoded in a database of three-residue fragments extracted from a large set of high-resolution experimentally determined protein structures. The computation of conformational transitions leading to the formation of the structural elements is formulated as a discrete path search problem using this database. To solve this problem, we propose a heuristically-guided depth-first search algorithm. The domain-dependent heuristic function aims at minimizing the length of the path in terms of angular distances, while maximizing the local density of the intermediate states, which is related to their probability of existence. We have applied the strategy to two small synthetic polypeptides mimicking two common structural motifs in proteins. The folding mechanisms extracted are very similar to those obtained when using traditional, computationally expensive approaches. These results show that the proposed approach, thanks to its simplicity and computational efficiency, is a promising research direction.
蛋白质中的结构元件对于定义折叠/展开机制以及控制生物体内信号转导过程的伴侣识别事件至关重要。在这里，我们提出了一种模拟这些结构元件折叠机制的新方法。我们的方法基于利用从大量高分辨率实验确定的蛋白质结构中提取的三残基片段数据库中编码的局部、序列依赖性结构信息。使用该数据库将导致结构元件形成的构象转变的计算表述为离散路径搜索问题。为了解决这个问题，我们提出了一种启发式引导的深度优先搜索算法。域相关启发式函数旨在根据角度距离最小化路径的长度，同时最大化中间状态的局部密度，这与它们的存在概率有关。我们已经将该策略应用于两个模拟蛋白质中两种常见结构基序的小型合成多肽。提取的折叠机制与使用传统、计算成本高昂的方法获得的机制非常相似。这些结果表明，由于其简单性和计算效率，所提出的方法是一个很有前途的研究方向。
