SCI: Collaborative Research: DAPLDS - a Dynamically Adaptive Protein-Ligand Docking System based on Multi-Scale Modeling

DAPLDS或动态自适应蛋白质-配体对接系统项目涉及德克萨斯大学埃尔帕索分校、斯克里普斯研究所(TSRI)和加州大学伯克利分校之间的合作。该项目通过实施和使用一种名为DAPLDS的网络工具，能够在全球计算环境(即使用“志愿”个人计算机的分布式、异质计算环境)中进行自适应多尺度建模，将进一步了解蛋白质-配体相互作用的原子细节，并通过这样做，将加速发现新的药物。该项目的目标是：(1)探索蛋白质-配体对接中算法适应的多尺度性质，以及(2)开发基于计算方法和模型的网络基础设施，以有效地适应这些适应。该项目的智力优势来自称为配体的小分子，它们在开启或关闭蛋白质功能或为酶催化的化学反应提供底物方面起着至关重要的作用。了解蛋白质-配体对接的原子水平细节是开发新药物的宝贵资源。对接过程取决于所涉及的蛋白质-配体复合体的特性，并给定一定的络合物，对接过程的表征和建模会影响解的精度和模型的执行时间。基于蛋白质配体构象的特征和计算资源的可用性和可靠性，DAPLDS在适当的时候调整模型和/或计算系统，以优化模型的精度和求解时间。DAPLDS中的多尺度建模自适应至少包括三个尺度：(1)蛋白质-配体表示从刚性到灵活地表示蛋白质-配体相互作用，(2)溶剂表示从不精确到更精确的溶剂处理建模，以及(3)从固定采样到自适应采样的蛋白质-配体对接空间的采样策略。我们的项目改变了应对重大挑战的方式，实现了一个可扩展到蛋白质-配体对接应用程序之外的自适应网络工具，例如，该工具可以被改造并用于蛋白质折叠和蛋白质结构预测。此外，利用公共计算资源在参与这项工作的个人计算机用户中促进和传播科学研究和科学知识。

The DAPLDS or Dynamically Adaptive Protein-Ligand Docking System project involves collaboration among the University of Texas, El Paso, The Scripps Research Institute (TSRI), and the University of California, Berkeley. This project, through implementation and use of a cybertool, DAPLDS, that enables adaptive multi-scale modeling in a global computing environment (i.e., distributed, heterogeneous computing environment using "volunteer" PC computers), will further knowledge of the atomic details of protein-ligand interactions and, by doing so, will accelerate the discovery of novel pharmaceuticals. The goals of the project are: (1) to explore the multi-scale nature of algorithmic adaptations in protein-ligand docking and (2) to develop cyber infrastructures based on computational methods and models that efficiently accommodate these adaptations.The intellectual merit of the project derives from small molecules, called ligands, which play an essential role in turning protein functions on or off, or in providing substrates for chemical reactions catalyzed by enzymes. Knowledge of the atomic level details of the protein-ligand docking is a valuable resource in the development of novel pharmaceuticals. The docking process depends on the characteristics of the protein-ligand complex involved and given a certain complex, the characterization and modeling of the docking process can affect both solution accuracy and model execution time. Based on characteristics of the protein-ligand conformations and the availability and reliability of computational resources, DAPLDS adapts, when appropriate, the model and/or the computational system to optimize model accuracy and time to solution. The multi-scale modeling adaptation in DAPLDS comprises at least three spanning scales: (1) protein-ligand representation spanning scale from rigid to flexible representation of protein-ligand interactions, (2) solvent representation spanning scale from less accurate to more accurate modeling of solvent treatment, and (3) sampling strategy spanning scale from fixed to adaptive sampling of the protein-ligand docking space.Broader Impact: DAPLDS applies multi-scale modeling to the search for putative drugs and drug leads. Our project changes the way in which grand challenges are approached by implementing an adaptive cybertool that scales beyond the protein-ligand docking application, e.g., this tool can be adapted and used for protein folding and protein structure prediction. Moreover, the use of public computing resources promotes and disseminates science research and science knowledge among the users of PCs involved in this effort.