GPU Accelerated Protein Docking Software with Flexible Refinement

具有灵活细化功能的 GPU 加速蛋白质对接软件

• 批准号: 8394398
• 负责人: MARTIN C HERBORDT
• 金额: $ 10.49万
• 依托单位: ACPHARIS, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-28 至 2014-09-27
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8394398
• 关键词: Academia; Acceleration; Address; Affinity; Algorithms; Architecture; Biological; Biological Models; Boston; Code; Collaborations; Communication; Complex; Computer software; Computing Methodologies; Consult; Data; Development; Disease Pathway; Docking; Drug Delivery Systems; Drug Industry; Evaluation; Fourier Transform; Goals; Homology Modeling; Hour; Industry; Letters; Licensing; Maps; Market Research; Marketing; Methodology; Methods; Molecular Conformation; Molecular Models; Pathway interactions; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Procedures; Process; Production; Proteins; Relaxation; Research Contracts; Rotation; Running; Side; Specificity; Speed; Staging; Structure; System; Therapeutic Intervention; Time; Universities; Vertebral column; Work; X-Ray Crystallography; antibody engineering; base; commercialization; computational chemistry; computing resources; cost effective; cost effectiveness; design; extracellular; flexibility; innovation; molecular modeling; novel; programs; protein complex; protein protein interaction; receptor; simulation; Academia; Acceleration; Address; Affinity; Algorithms; Architecture; Biological; Biological Models; Boston; Code; Collaborations; Communication; Complex; Computer software; Computing Methodologies; Consult; Data; Development; Disease Pathway; Docking; Drug Delivery Systems; Drug Industry; Evaluation; Fourier Transform; Goals; Homology Modeling; Hour; Industry; Letters; Licensing; Maps; Market Research; Marketing; Methodology; Methods; Molecular Conformation; Molecular Models; Pathway interactions; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Procedures; Process; Production; Proteins; Relaxation; Research Contracts; Rotation; Running; Side; Specificity; Speed; Staging; Structure; System; Therapeutic Intervention; Time; Universities; Vertebral column; Work; X-Ray Crystallography; antibody engineering; base; commercialization; computational chemistry; computing resources; cost effective; cost effectiveness; design; extracellular; flexibility; innovation; molecular modeling; novel; programs; protein complex; protein protein interaction; receptor; simulation

DESCRIPTION (provided by applicant): Protein-protein interactions are involved at multiple points in virtually all biological pathways. Understanding such interactions is also important for the design of biologics that can target extracellular receptors with high affinity and specificity. Since determining the structure of protein complexes by X-ray crystallography is expensive and slow, it is important to develop computational docking methods that, starting from the structures of component proteins or homology models, can determine the structure of their complexes. Accordingly, there is increasing demand for protein docking methods in the pharmaceutical industry. Based on the results of CAPRI (Critical Assessment of Predicted Interactions), a worldwide protein docking competition, PIPER, developed at Boston University and licensed to Acpharis, is the best protein-protein docking program currently available. A major problem is that the flexible refinement of the PIPER-generated structures requires computational resources that are generally not available in industry. The general goal of this proposal is to develop efficient flexible refinement methods, and to implement the computationally expensive steps on GPUs. The refinement will employ two novel algorithms. First, given a putative interface defined by a cluster, Acpharis will develop a program to identify the "key" variable side chains in the interface and their potential conformational states. Second, we will develop a Monte Carlo minimization algorithm for flexible refinement, which combines search in the space of the selected side chain rotamers with an innovative minimization method in the rotational/translational space based on manifold concepts. A number of the resulting structures will be subjected to further refinement involving backbone relaxation. In addition to the use of more powerful flexible refinement algorithms, further speed-up will be achieved by implementing the time consuming components of both docking and refinement on GPUs. Profiling the algorithms we have found two such components, namely (1) correlation calculations that use fast Fourier transforms (FFTs) in docking, and (2) the non-bonded energy evaluation in the flexible refinement step. For the docking step we will perform rotation and grid assignment on the CPU while the FFT and filtering will be computed on the GPU. Acceleration of the energy evaluation steps will require changing the underlying data structures and statically mapping the work onto GPU threads in a way that allows parallel energy evaluations. With the above algorithmic and architectural speed-up, we can expect that a docking and refinement problem that previously required several hours on a 128 CPU cluster will be solved in the same amount of time by a single CPU and 2 NVIDIA Fermi GPU cards. Such a system can currently be assembled for $3500, which is clearly within reach for small pharmaceutical start-up companies or computational chemistry units. PUBLIC HEALTH RELEVANCE: Understanding protein-protein interactions is crucial for discovery of certain drugs and biologics. The goal of this proposal is obtaining the information by novel computational methods implemented on cost effective graphic processing units. (GPUs).

描述（由申请人提供）：几乎所有生物途径的蛋白质 - 蛋白质相互作用都涉及多个点。了解这种相互作用对于可以针对具有高亲和力和特异性的细胞外受体的生物制剂的设计也很重要。 由于通过X射线晶体学确定蛋白质复合物的结构是昂贵且缓慢的，因此开发计算对接方法很重要，从组件蛋白或同源性模型的结构开始，可以确定其复合物的结构。因此，制药行业对蛋白质对接方法的需求不断增加。根据CAPRI的结果（对预测相互作用的批判性评估），在波士顿大学开发的全球蛋白质对接竞赛和获得Acpharis许可的Piper是当前可用的蛋白质 - 蛋白质对接计划。一个主要的问题是，吹笛者生成的结构的灵活改进需要行业通常不可用的计算资源。该建议的一般目标是开发有效的灵活改进方法，并在GPU上实施计算昂贵的步骤。精炼将采用两种新型算法。首先，鉴于由集群定义的推定接口，Acpharis将开发一个程序，以识别接口中的“键”可变侧链及其潜在的构象状态。其次，我们将开发一种用于灵活改进的蒙特卡洛最小化算法，该算法将基于多种概念的旋转/转换空间中的旋转/转换空间中的创新最小化方法结合在一起。许多结果结构将进行进一步的细化，涉及主链松弛。除了使用更强大的灵活改进算法外​​，还将通过在GPU上实现对接和改进的耗时组件来进一步加速。分析了算法，我们发现了两个这样的组件，即（1）相关计算，它们在对接中使用快速的傅立叶变换（FFT），以及（2）在灵活的细化步骤中进行的非键入能量评估。对于对接步骤，我们将在CPU上执行旋转和网格分配，而FFT和过滤将在GPU上计算。能源评估步骤的加速度将需要更改基础数据结构，并以允许并行能量评估的方式将工作统计地映射到GPU线程上。通过上述算法和建筑加速，我们可以预期，以前需要在128 CPU群集上需要几个小时的对接和改进问题将在相同的时间内通过单个CPU和2个Nvidia fermi GPU卡在相同的时间内解决。当前，这样的系统可以以3500美元的价格组装，这对于小型制药初创公司或计算化学单元显然可以触及。 公共卫生相关性：了解蛋白质 - 蛋白质相互作用对于发现某些药物和生物制剂至关重要。该提案的目的是通过针对经济有效的图形处理单元实施的新计算方法获得信息。 （GPU）。