ABI Development: Utilization of diverse data in exploring protein-protein interactions

每个活着的细胞都充满了蛋白质，这些蛋白质不断地相互作用，以响应环境和其他信号，控制细胞的生长和最终的命运。对这种相互作用的分析对于理解在生物发育过程中和整个生命过程中驱动细胞分化的信号转导途径至关重要。这些途径通常与癌症等疾病的进展有关，因此了解这些途径的更广泛影响可能是设计出调节这些途径的药物。此外，对蛋白质相互作用的这种理解可能有助于蛋白质生物材料的发展。目前的技术可以为大型蛋白质相互作用网络提供蓝图，但更深入的理解需要蛋白质对或伙伴形成的复合体的详细结构。结构信息往往很难甚至不可能通过实验工具获得，强调了计算方法的必要性。波士顿大学的Vajda和Kozakov开发了基于Web的服务器ClusPro，用于预测蛋白质-蛋白质复合体的三维结构。根据全球实验CAPRI(预测相互作用的关键评估)，ClusPro一直是最好的蛋白质-蛋白质对接服务器。它拥有5000多名注册用户，每月进行约3500次对接计算。由服务器生成的结构已在350多篇研究论文中报告。该项目的目标是开发下一代ClusPro，它将能够最佳地利用公共生物信息学数据库中积累的海量数据，以提高预测结构的可靠性和准确性。由于服务器主要由生物和化学科学家使用，他们可能不具备使用当前生物信息学工具的专业知识，因此新版本将提供使用最先进方法的便利途径。生物信息学和计算生物物理学方法的结合，与实验验证相结合，将产生一种独特而强大的研究工具。蛋白质复杂结构的增加将对生物学、生物化学和生物技术的许多领域产生重大影响。所有开发的软件将免费发布，供学术和政府使用。此外，该项目将用于培养新一代研究生，他们将能够以最佳方式将各种实验和生物信息学技术的数据与高性能计算相结合。服务器的使用也将被纳入本科课程，教授生物信息学和分子识别的生物物理原理。当前版本的ClusPro系统地对目标蛋白质复合体的构象空间进行采样，并使用基于物理的能量函数对结构进行评分。这种方法的主要缺点是，它执行对接时没有考虑公共数据库中可用的大量相互作用、序列、结构和实验信息。新方法不是简单地生成和评分起始蛋白质的对接结构，而是使用它们的序列来收集所有同源序列，以识别可能包含短线状基序(SLIM)的球状结构域和结构域间区域。出现在许多相互作用的蛋白质对中的结构域可能介导相互作用，从而能够识别与伙伴蛋白的结构域或纤细相互作用的特定结构域。叠加来自不同同源基因的结构域识别保守区域。由于复合体中的界面相对于蛋白质的其余部分在序列和结构上更加保守，对于结构域相互作用的情况，仅对接关键片段通常会产生接近自然对接的结构。对接来自不同直系物的关键片段，并选择一致的模型，提高了预测结构的可靠性。这种方法大大改善了具有柔性环的蛋白质的对接，并将扩展到同源模型的对接。如果界面包括一个细长的、包含基序的多肽片段的对接结构，则将该方法扩展到由柔性区域或非结构化区域介导的相互作用的蛋白质。将要开发的算法将在ClusPro中实现，这将提供关于蛋白质-蛋白质复合体的大量新信息。可以在http://cluspro.bu.edu.上访问ClustPro软件

Each living cell is packed with proteins that continuously interact with each other in response to envirtonmental and other signals to control the cell's growth and eventual fate. The analysis of such interactions is crucial for understanding signal transduction pathways that drive cell differentian during development and throughout the life an an organism. These pathways are often involed in disease progression, such as cancer, so a broader impact of understanding these pathways could be the design of drugs to modulate such pathways. Moreover, such an understanding of protein protein interactions may aid the develpment of protein-based biomaterials. Current technologies exist for providing a blueprint for large protein interaction networks, but a deeper understanding requires detailed structures of the complexes formed by protein pairs or partners. Structural information is frequently difficult or even impossible to obtain by experimental tools, emphasizing the need for computational approaches. Vajda and Kozakov at Boston University have developed the web based server ClusPro for predicting the three dimensional structures of protein-protein complexes. According to the worldwide experiment CAPRI (Critical Assessment of Predicted Interactions), ClusPro consistently has been the best protein-protein docking server. It has over 5000 registered users and performs around 3500 docking calculations each month. Structures generated by the server have been reported in over 350 research papers. The goal of this project is to develop the next generation of ClusPro that will be able to optimally utilize the vast amount of data accumulated in public bioinformatics databases in order to improve the reliability and accuracy of the predicted structures. Since the server is used primarily by biological and chemical scientists who may not have expertise in the use of current bioinformatics tools, the new version will provide convenient access to state-of-art methods. Integration of bioinformatics and computational biophysics approaches, in combination with experimental validation, will result in a unique and powerful research tool. The increased availability of protein complex structures will have a major impact in many areas of biology, biochemistry, and biotechnology. All software developed will be released free of charge for academic and governmental use. In addition, the project will be used to train a new generation of graduate students, who will be able to optimally combine data from a variety of experimental and bioinformatics techniques with high performance computing. The use of the server will also be incorporated into undergraduate courses to teach aspects of bioinformatics and biophysical principles of molecular recognition. The current version of ClusPro systematically samples the conformational space of a target protein complex, and scores the structures using physics based energy functions. The major shortcoming of this approach is that it performs docking without consideration of the large body of interaction, sequence, structural, and experimental information available in public databases. Rather than simply generating and scoring docked structures of the starting proteins, the new approach will use their sequences to collect all orthologs to identify the globular domains and inter-domain regions that may contain short linear motifs (SLIMs). Domains that occur in a number of interacting protein pairs are likely to mediate the interaction, enabling the identification of the specific domains that interact with domains or SLIMs of the partner protein. Superimposing the domains from different orthologs identifies the conserved regions. Since the interface in complexes is sequentially and structurally more conserved relative to the rest of the protein, for the case of domain-domain interactions docking just the key segments generally yields near-native docked structures. Docking key segments from different orthologs and selecting consensus models improves the reliability of predicted structures. This approach substantially improves the docking of proteins that have flexible loops, and will be extended to the docking of homology models. If the interface includes a SLIM, docking structures of peptide fragments that contain the motif extends the method to proteins with interactions mediated by flexible or unstructured regions. The algorithms to be developed will be implemented in ClusPro, which will provide substantial new information on protein-protein complexes. ClustPro software can be accessed at http://cluspro.bu.edu.