Research Initiation Award: The Rapid Evaluation and Global Minimization of Potential Energy Functions in Molecular and Protein Conformations

研究启动奖：分子和蛋白质构象中潜在能量函数的快速评估和全局最小化

• 批准号: 9409285
• 负责人: Guoliang Xue
• 金额: $ 9万
• 依托单位: University of Vermont & State Agricultural College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-08-01 至 1998-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9409285&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Rapid; Evaluation

Xue 9409285 The objective of this project is to produce more effective sequential and parallel algorithms and software for the rapid evaluation and global minimization of nonconvex potential energy functions that arise in molecular and protein conformation problems. The proposed research will combine the fast multipole algorithms and automatic differentiation to produce O (n) operation algorithms for both the function evaluation and the gradient vector evaluation for a system of n particles. Since all existing algorithms require at least O (n2) operations to evaluate the gradient vector, this research will improve almost all existing algorithms for molecular and protein conformations where repeated evaluation of the function and gradient is required. This success relies on two programming paradigms: a discrete-continuous programming paradigm that uses physical knowledge on the problem to guide continuous minimization searchers, and a parallel two-level simulated annealing programming paradigm which provides load balancing dynamically and moves from one local minimizer to another in an effort to locate a global minimizer.

雪9409285这个项目的目标是产生更有效的顺序和并行算法和软件，用于快速评估和全局最小化分子和蛋白质构象问题中出现的非凸势能函数。这项研究将结合快速多极算法和自动微分，为n个粒子系统的函数求值和梯度向量求值产生O(N)运算算法。由于所有现有的算法都需要至少O(N2)次运算来计算梯度向量，因此本研究将改进几乎所有需要重复计算函数和梯度的分子和蛋白质构象的现有算法。这种成功依赖于两种编程范式：一种是离散-连续编程范式，它使用问题的物理知识来指导连续最小化搜索；另一种是并行的两级模拟退火法编程范式，它动态地提供负载平衡，并从一个局部最小化程序移动到另一个局部最小化程序，以努力定位全局最小化程序。