Petascale Integrative Approaches to Protein Structure Prediction

这个项目解决了生物学的一个中心挑战：从序列预测蛋白质结构。蛋白质结构的准确测定是理解生物机制和设计新药的关键。这项工作的目的是利用Blue Waters的千万亿级能力来克服目前结构确定的实验和计算工具的局限性。该项目将通过运行一种基于物理的模拟方法来实现这一点，该方法被称为MELD(建模采用有限数据)，它合理地结合了稀疏、噪声和模棱两可的实验或启发式信息。目前，大约15%的蛋白质靶标不能用已知的方法来解决。这项工作的变革性目标是使用运行在Blue Waters上的MELD来打破计算结构预测的大小和复杂性的障碍。这项工作有三个主要目标：(1)使用MELD为已知的小蛋白质提供结构，在生物信息学方法失败和数据库稀疏的情况下(例如膜蛋白质)，(2)通过播种具有MELD中间状态的马尔可夫状态模型(MSM)为蛋白质折叠提供动力学和路径信息，以及(3)使用准确的结合时折叠的相对自由能来更准确地设计肽。该项目将使用Blue Waters的千万亿级能力来突破完全基于原子物理的预测的规模界限。更大的科学界将可以免费获取该项目的软件和成果。

This project addresses a central challenge of biology: the prediction of protein structure from sequence. Accurate determination of protein structure is essential to understanding biological mechanism and designing new drugs. The purpose of this work is to use the petascale capabilities of Blue Waters to overcome limitations of current experimental and computational tools of structure determination. The project will do this by running a physics-based simulation method, called MELD (Modeling Employing Limited Data) that rationally incorporates sparse, noisy, and ambiguous experimental or heuristic information. Currently around 15% of protein targets cannot be tackled by known methods. The transformative goal of this work is to use MELD, running on Blue Waters, to break substantial barriers in size and complexity for computational structure prediction.This work has three major goals: (1) use MELD to provide structures for the known, small proteins were bioinformatics methods fail and where databases are sparse (e.g. membrane proteins), (2) provide kinetic and pathway information for protein folding by seeding Markov State Models (MSM) with MELD intermediate states, and (3) use accurate relative free energies of folding upon binding for more accurate peptide design. The project will use the the petascale capabilities of Blue Waters to push the size boundaries of full atomistic physics based predictions. Both the software and the results obtained from this project will be freely accessible to the larger scientific community.