Next generation computational tools for the analysis and prediction of protein disorder and related gene function

随着许多基因组现已完全测序，生命科学家面临着描述编码蛋白质的生物学作用的挑战，以促进我们对细胞生理学的理解。在过去的几十年里，一些实验研究加强了蛋白质的三维结构是其功能的先决条件的观点。进化优化了特定蛋白质原子的相对位置，使它们能够执行不同的任务，包括配体结合和催化反应。最近，根据真核物种的更多数据，这一观点得到了修订。事实上，一些观察证明，它们的大量蛋白质包括高度灵活的片段，当它们只识别它们的生物学伴侣时，它们呈现出固定的构象。这些片段-或完整蛋白质-通常被称为天然未折叠的，本质上非结构化或无序的，并且主要存在于多细胞生物体中，其中它们通过与蛋白质，核苷酸，核酸和金属离子结合在信号传导和调节过程中发挥关键作用。无序蛋白质的鉴定和功能表征越来越受到人们的关注。不同的分析可以产生关于无序区域位置的系统信息。然而，这些技术受到内在限制，不能合理地应用于典型真核生物表达的所有蛋白质。另一方面，彻底的分析表明，这些蛋白质的氨基酸序列具有清晰的模式，因此计算机程序可以相当准确和快速地区分它们。蛋白质天然未折叠的分类及其无序区域的位置是有价值的信息。然而，这还不足以详细描述蛋白质执行的分子作用以及它们与哪些生物过程相关。虽然我们知道某些功能类别在无序区域中特别丰富，但我们无法通过实验测试所有可能的替代方案。一个合理的解决方案是利用计算机进一步分析这些蛋白质，然后进行更少的实验室测定来验证计算分析的结果。该项目旨在开发一个网络服务器，每个人都可以通过互联网访问，并输出无序蛋白质的功能预测-即提示。该程序将首先使用我们以前开发的方法在输入序列中定位无序区域。然后，它将利用一些配体（如DNA和金属离子）的化学和物理特征，评估输入蛋白质序列通过其潜在的无序区域与它们相互作用的可能性。这些结果有望提高我们对这类重要蛋白质的认识，并优先进行旨在表征其功能的实验。

With many genomes now completely sequenced, life scientists face the challenge of characterizing the biological role of the encoded proteins as to advance our understanding of cell physiology. Over the past decades, several experimental studies reinforced the view that the three dimensional structure of a protein is a prerequisite to its function. Evolution optimized the relative positions of specific protein atoms so that they can perform different tasks, including ligand binding and catalysis of reactions. Recently this view has been revised in light of additional data from eukaryotic species. Indeed, several observations prove that a large number of their proteins include highly flexible segments, which assume a fixed conformation when they recognize their biological partners only. These fragments - or whole proteins - are usually called natively unfolded, intrinsically unstructured or disordered and are predominantly found in multi-cellular organisms where they play key roles in signalling and regulatory processes through the binding to proteins, nucleotides, nucleic acids and metal ions. The identification and functional characterization of disordered proteins has drawn increasing attention. Different assays can produce systematic information on the location of disordered regions. However, these techniques suffer from intrinsic limitations and cannot be reasonably applied to all the proteins that a typical eukaryotic organism expresses. On the other side, thorough analyses showed that the amino acid sequences of these proteins are characterized by clear patterns and so computer programs can distinguish them fairly accurately and quickly. The classification of a protein as natively unfolded and the location of its disordered regions are valuable information. Yet, this is not enough to describe in detail what molecular actions the protein performs and what biological processes they relate to. Although we know that some functional categories are particularly enriched in disordered regions, we cannot afford to experimentally test all possible alternatives. A reasonable solution consists in exploiting computers to further analyze these proteins and then in performing much less lab assays to validate the results of computational analyses. This project aims at the development of a web server that will be accessible to everyone through the Internet and that will output functional predictions - i.e. hints - for disordered proteins. The program will first locate disordered regions within the input sequence using a method we previously developed. It will then exploit the chemical and physical features of some ligands - such as DNA and metal ions - to assess the likelihood for the input protein sequence to interact with them through its potential disordered regions. The results are expected to improve our knowledge of this important class of proteins and prioritize experiments aimed at characterizing their functions.