STRUCTURE PREDICTION OF PEPTIDES VIA GLOBAL OPTIMIZATION

通过全局优化预测肽的结构

• 批准号: 2415276
• 负责人: Christodoulos Achilleus Floudas
• 金额: $ 12.46万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-05-01 至 2000-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2415276
• 关键词: chemical hydration; computer simulation; protein folding; protein structure; technology /technique; thermodynamics

DESCRIPTION: The overall aim of this project is to improve our understanding of the three dimensional structure prediction of oligopeptides, polypeptides, and proteins. Based upon his recent advances in: (a) decomposition-based global optimization approach, GOP, (b) branch and bound with difference of convex functions transformation global optimization method, alphaBB, (c) the application of GOP to the structure prediction of Lennard-Jones Clusters, (d) the application of alphaBB to small acyclic molecules, (e) the application of the alphaBB coupled with ECEPP/3 to the naturally occurring amino acids and small oligopeptides, (f) the application of alphaBB coupled with ECEPP/3 to Met-enkephalin and its comparison to simulated annealing and other search methods, (g) the application of alphaBB to Decaglycine, and (h) the computational complexity that he has observed on the considered systems, the proposed research work is directed at determining (i) the global minimum potential energy conformation of peptides and proteins, (ii) low energy conformations of peptides close to the global minimum one, and (iii) saddle points of the potential energy hypersurface of the peptides that are close to the global minimum peptide structure. Dr. Floudas plans to focus on the following objectives: (a) Study the deterministic global optimization approach described in the preliminary studies section 3.3 for (i) oligopeptides such as Leu- enkephalin, Gramicidin S, and Mellitin, (ii) the incorporation of solvation effects and the application to the pentapeptides of Met- enkephalin and Leu-enkephalin in the presence of water, (iii) calculations of the relative entropy and relative free energy, and (iv) constrained peptide systems. (b) Investigate modifications of the global optimization method in (a) so as to be extended to handle polypeptide molecules such as the avian pancreatic polypeptide, models of fibrous proteins such as collagen,a nd globular proteins such as bovine trypsin inhibitor. (c) Study the topography of the total potential energy surface by developing and applying a new method for the determination of saddle points of the peptide energy hyersurface that are close to the global minimum one. (d) Develop distributed computing algorithms for global optimization methods for (a), (b), and (c), apply them to olgopeptides, polypeptides, proteins, and develop tools for the prediction of three-dimensional structures of peptides.

描述：该项目的总体目标是改善我们的 三维结构预测的理解 寡肽、多肽和蛋白质。 根据他最近的 在以下方面取得进展：(a) 基于分解的全局优化方法，GOP， (b) 具有凸函数变换差异的分支定界 全局优化方法，alphaBB，(c) GOP 的应用 Lennard-Jones 簇的结构预测，(d) 应用 alphaBB 到无环小分子，(e) alphaBB 的应用 与 ECEPP/3 结合到天然存在的氨基酸和小分子中 寡肽，(f) αBB 与 ECEPP/3 结合的应用 甲硫氨酸脑啡肽及其与模拟退火和其他搜索的比较 方法，(g) 将 alphaBB 应用于 Decaglycine，以及 (h) 他在所考虑的系统上观察到的计算复杂性， 拟议的研究工作旨在确定(i) 全球 肽和蛋白质的最小势能构象，(ii) 低 肽的能量构象接近全局最小值，并且 (iii) 肽势能超曲面的鞍点 接近全局最小肽结构。 弗洛达斯博士 计划重点实现以下目标： (a) 研究确定性全局优化方法 初步研究第 3.3 节针对 (i) 寡肽，例如 Leu- 脑啡肽、短杆菌肽 S 和蜂毒肽，(ii) 并入 溶剂化效应及其在Met-五肽中的应用 脑啡肽和亮氨酸脑啡肽在水存在下，(iii) 相对熵和相对自由能的计算，以及 (iv) 受限肽系统。 (b) 调查修改 (a)中的全局优化方法以便扩展处理 多肽分子，例如禽胰多肽、模型 纤维状蛋白质（例如胶原蛋白）和球状蛋白质（例如 牛胰蛋白酶抑制剂。 (c) 研究总地形 势能面通过开发和应用一种新方法来 肽能量超表面鞍点的测定 接近全球最低值。 (d) 发展分布式计算 (a)、(b) 和 (c) 的全局优化方法的算法，适用 将它们转化为寡肽、多肽、蛋白质，并开发用于 肽三维结构的预测。