Department of Physics, Sapienza University of Rome, Rome, Italy.
PLoS One. 2011;6(7):e22270. doi: 10.1371/journal.pone.0022270. Epub 2011 Jul 20.
The function of proteins is often mediated by short linear segments of their amino acid sequence, called Short Linear Motifs or SLiMs, the identification of which can provide important information about a protein function. However, the short length of the motifs and their variable degree of conservation makes their identification hard since it is difficult to correctly estimate the statistical significance of their occurrence. Consequently, only a small fraction of them have been discovered so far. We describe here an approach for the discovery of SLiMs based on their occurrence in evolutionarily unrelated proteins belonging to the same biological, signalling or metabolic pathway and give specific examples of its effectiveness in both rediscovering known motifs and in discovering novel ones. An automatic implementation of the procedure, available for download, allows significant motifs to be identified, automatically annotated with functional, evolutionary and structural information and organized in a database that can be inspected and queried. An instance of the database populated with pre-computed data on seven organisms is accessible through a publicly available server and we believe it constitutes by itself a useful resource for the life sciences (http://www.biocomputing.it/modipath).
蛋白质的功能通常是由其氨基酸序列的短线性片段介导的，这些短线性片段被称为短线性基序（Short Linear Motifs 或 SLiMs），其鉴定可以提供有关蛋白质功能的重要信息。然而，由于 motifs 的短长度和它们可变的保守程度，使得它们的鉴定变得困难，因为很难正确估计它们出现的统计显著性。因此，到目前为止，只有一小部分被发现。我们在这里描述了一种基于在属于同一生物学、信号或代谢途径的进化上无关的蛋白质中出现的短线性基序的发现方法，并给出了其在重新发现已知基序和发现新基序方面的有效性的具体示例。该方法的自动实现可下载，允许鉴定出重要的基序，并自动注释功能、进化和结构信息，并组织到一个可以检查和查询的数据库中。通过一个公共可用的服务器可以访问一个用预计算数据填充的数据库实例，我们相信它本身就是生命科学的一个有用资源（http://www.biocomputing.it/modipath）。
