Interaction Pattern Based Predictor of Protein Structure

项目描述（申请人提供）：该项目的长期目标是发展基于结构的蛋白质分子功能预测方法，使基因组测序和结构基因组学提供的信息能够得到更充分的利用。为了实现这一总体目标，本提案进一步发展了一种非常有前途和紧密集成的，从序列到结构到功能的方法，该方法利用蛋白质结构来预测蛋白质-蛋白质相互作用，蛋白质分子功能和配体结合位点。它也为改进配体筛选提供了相当大的希望。具体而言，本文提出了以下具体目标：(1)将对基于单体序列轮廓的线程算法进行扩展和改进，该算法目前无法在PDB中找到约25%序列一致性极低的单域蛋白的良好模板结构来求解蛋白质结构。(2)当目标蛋白和模板蛋白在进化上距离较远或结构相似时，当前最好的线程算法具有很强的进化成分，限制了它们的结构识别能力，因此将开发一种纯粹基于结构的线程化算法。在这方面，适用于基于结构的穿线的平均力势将从一个新的琥珀相关的，基于物理的原子势中衍生出来，它显示出更接近天然结构的显著能力。(3)多聚体结构预测算法m-TASSER将通过提高界面侧链接触预测的准确性和使用基于物理的界面势来优化结构来增强。此外，利用单域蛋白结构库可能是完整的这一事实，全对全对接将提供单域蛋白可能的二聚体复合体数量的估计。(4)对基于FINDSITE结构的蛋白质分子功能预测算法进行扩展和改进。其中包括增强其配体筛选能力，这是基于对进化距离较远的蛋白质的认识，在蛋白质结合位点和2结合配体中都存在保守的锚定区域，可以用于快速预测和筛选配体结合姿态。(5) EFICAz是一种精确的酶功能推断方法，将与FINDSITE结合开发更强大的配体筛选方法。(6)在Aims 1-5中开发的整套工具将应用于所有已测序的蛋白质组，并由此产生的从序列到结构到功能的数据库向学术界开放。全蛋白质组结构预测将与EFICAz和FINDSITE相结合，以鉴定包括抗癌代谢物靶点在内的小调节分子的可能受体，并提供全蛋白质组筛选配体文库、蛋白质-蛋白质相互作用文库、四级结构和分子功能注释。在所有情况下，都将进行大规模、仔细的基准测试。因此，该项目有望在广泛的生物学重要问题上产生重大影响。

DESCRIPTION (provided by applicant): The long-term goal of this project is to develop a structure-based approach for the prediction of protein molecular function so that the information provided by both genome sequencing and structural genomics can be more fully exploited. To achieve this overall objective, this proposal further develops a very promising and tightly integrated, sequence-to-structure-to-function approach that employs protein structure to predict protein- protein interactions, protein molecular function, and ligand binding sites. It also holds considerable promise for improved ligand screening. In particular, the following Specific Aims are proposed: (1) Monomeric sequence profile-based threading algorithms, which currently fail to find the good template structures in the PDB for the ~25% of single domain proteins with very low sequence identity to solved protein structures, will be extended and improved. (2) A purely structure-based version of threading will be developed, as the best contemporary threading algorithms have a strong evolutionary component that limits their structure recognition ability when the target and template proteins are evolutionarily distant or have analogous structures. In that regard, potentials of mean force suitable for structure-based threading will be derived from a new AMBER-related, physics-based atomic potential that shows significant ability to refine structures closer to native. (3) The multimeric structure prediction algorithm, m-TASSER, will be enhanced by improving the accuracy of interfacial side chain contact predictions and the use of physics-based interfacial potentials for structure refinement. In addition, by exploiting the fact that the library of single domain protein structures is likely complete, all-against-all docking will provide an estimate of the number of possible dimer complexes of single domain proteins. (4) The FINDSITE structure-based protein molecular function prediction algorithm will be extended and improved. Included are enhancements of its ligand screening ability based on the insight that for evolutionarily distant proteins, there are conserved anchor regions in both the protein binding site and in the 2 bound ligands that can be exploited for rapid ligand binding pose prediction and screening. (5) EFICAz , a precise enzyme function inference approach, will be combined with FINDSITE to develop a more powerful ligand screening approach. (6) The entire set of tools developed in Aims 1-5 will be applied to all sequenced 2 proteomes and the resulting sequence-to-structure-to-function, S F, database made available to the academic 2 community. Whole proteome structure predictions will be combined with EFICAz and FINDSITE to identify possible receptors of small regulatory molecules including the targets of anticancer metabolites, and to provide whole proteome screened ligand libraries, libraries of protein-protein interactions, quaternary structures and molecular functional annotations. In all cases, large scale, careful benchmarking will be done. Thus, this project holds the promise of making a significant impact across a wide spectrum of biologically important problems. PUBLIC HEALTH RELEVANCE: The development and whole proteome application of the tightly integrated, protein sequence-to-structure- function approach described in this project will be of utility to a broad spectrum of researchers. By assisting in the early stages of drug discovery, the proposed algorithms could have significant therapeutic utility. Also, most of the estimated 650,000 protein-protein interactions in the human interactome are unknown; by providing predicted protein quaternary structures, insights into how these proteins perform their function will result.