Interaction Pattern Based Predictor of Protein Structure

描述(申请人提供)：该项目的长期目标是开发一种基于结构的方法来预测蛋白质分子功能，以便更充分地利用基因组测序和结构基因组学提供的信息。为了实现这一总体目标，该建议进一步发展了一种非常有前途的紧密集成的、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。它还为改进配基筛选带来了相当大的希望。提出了以下具体目标：(1)基于单体序列图谱的穿线算法目前无法在PDB中找到好的模板结构，对于序列同源性很低的~25%的单域蛋白质，将对其进行扩展和改进。(2)将开发一个纯粹基于结构的线程版本，因为当代最好的线程算法具有强大的进化成分，当目标蛋白和模板蛋白质在进化上相距遥远或具有相似结构时，该成分限制了它们的结构识别能力。在这方面，适合于基于结构的线程的平均力势将从一种新的琥珀相关的、基于物理的原子势中推导出来，该原子势显示出显著的能力来精炼更接近自然的结构。(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精度和使用基于物理的界面势来进行结构精化而得到改进。此外，通过利用单域蛋白质结构的文库可能已经完成这一事实，All-And-All对接将提供单域蛋白质可能的二聚体复合体的数量的估计。(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。其中包括对其配体筛选能力的增强，这是基于以下认识：对于进化上遥远的蛋白质，在蛋白质结合部位和2个结合的配体中都有保守的锚定区，可用于快速的配体结合姿势预测和筛选。(5)EFICAz是一种精确的酶功能推断方法，它将与FINDSITE相结合，开发一种更强大的配基筛选方法。(6)在AIMS 1-5中开发的整套工具将应用于所有测序的2个蛋白质组，并将所产生的从序列到结构到功能的数据库S F提供给学术界2。整个蛋白质组结构预测将与EFICAz和FINDSITE相结合，以确定包括抗癌代谢物靶标在内的小调节分子的可能受体，并提供整个蛋白质组筛选的配体文库、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，这个项目有望在广泛的生物学重要问题上产生重大影响。 公共卫生相关性：本项目中描述的紧密集成的蛋白质序列到结构功能方法的开发和整体蛋白质组应用将对广泛的研究人员有用。通过在药物发现的早期阶段提供帮助，所提出的算法可能具有显著的治疗效用。此外，人类相互作用组中估计的650,000个蛋白质-蛋白质相互作用中的大多数是未知的；通过提供预测的蛋白质四级结构，将导致对这些蛋白质如何发挥其功能的洞察。

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.