ABI Development: Developing RaptorX Web Portal for Protein Structure and Functional Study

蛋白质在所有的生物过程中起着基本的作用。对蛋白质结构和功能的完整描述是理解生物生命的基本步骤，具有多种用途。数以百万计的蛋白质序列是可用的，但其中大多数没有实验解决的结构和功能。该项目旨在极大地改进RaptorX，一个用于蛋白质结构和功能计算预测的全自动web服务器，目标是提供一个长期可持续的门户网站，以促进生物学领域的变革研究。该门户网站将有利于广泛的生物和生物医学应用，如基因组注释、疾病过程的理解、药物设计、精准医疗甚至生物材料和生物能源的开发。研究结果将通过网络服务器、独立软件、出版物和讲座等各种渠道向更广泛的社区传播。自2011年底以来，RaptorX已经为包括中学生和高中生在内的25,000名全球用户提供服务。这些独立的程序已经被全球1500名用户下载。在这个项目完成后，RaptorX将为更广泛的社区做出更多贡献。参与该项目的学生将接受计算机科学、分子生物学、生物物理学和生物化学交叉领域的培训。本科生和代表性不足的学生将通过暑期实习项目和合作者招募。研究结果将被整合到课程材料中，并用于伊利诺斯在线生物信息学项目。RaptorX web服务器最初是为基于模板的蛋白质建模而开发的。该项目将通过首先开发一些新颖而强大的深度学习（例如，深度条件卷积神经场）和结构学习（例如，组图形lasso）方法来改造RaptorX，以显着提高蛋白质结构和功能预测的准确性，然后进行有效的实施。由此产生的RaptorX将能够更准确地预测蛋白质的二级和三级结构、溶剂可及性和无序区域，以及理论蛋白质3D模型的质量（在没有原生蛋白的情况下）。该项目还将扩展RaptorX服务器，以便对没有良好模板的蛋白质进行接触预测和接触辅助蛋白质折叠。RaptorX web服务器可从http://raptorx.uchicago.edu获得，用户也可以从那里下载独立程序。

Proteins play fundamental roles in all biological processes. Complete description of protein structures and functions is a fundamental step towards understanding biological life and has various applications. Millions of protein sequences are available, but a majority of them have no experimentally-solved structures and functions. This project aims to greatly improve RaptorX, a fully-automated web server for computational prediction of protein structure and function, with the goal to deliver a long-term sustainable web portal to facilitate transformative research in biology. This web portal shall benefit a broad range of biological and biomedical applications, such as genome annotation, understanding of disease processes, drug design, precision medicine and even biomaterial and bio-energy development. The results will be disseminated to the broader community through a variety of venues: web servers, standalone software, publications and talks. Since late in 2011, RaptorX has served 25,000 worldwide users including middle- and high-school students. The standalone programs have been downloaded by 1500 worldwide users. After this project is fulfilled, RaptorX will contribute much more to the broader community. Students involved in this project will receive training in the intersection of computer science, molecular biology, biophysics, and biochemistry. Undergraduate and underrepresented students will be recruited through summer intern programs and collaborators. The research results will be integrated into course materials and used in the Illinois online bioinformatics program. The RaptorX web server was originally developed for only template-based protein modeling. This project will transform RaptorX by first developing a few novel and powerful deep learning (e.g., Deep Conditional Convolutional Neural Fields) and structure learning (e.g., group graphical lasso) methods to significantly improve the accuracy of protein structure and functional prediction and then conducting an efficient implementation. The resultant RaptorX will be able to perform much more accurate prediction of protein secondary and tertiary structure, solvent accessibility and disordered regions, and the quality of a theoretical protein 3D model (in the absence of natives). This project will also expand the RaptorX server to perform contact prediction and contact-assisted protein folding for proteins without good templates. The RaptorX web server is available at http://raptorx.uchicago.edu, from which users can also download the standalone programs.