STRUCTURE PREDICTION OF PEPTIDES VIA GLOBAL OPTIMIZATION

通过全局优化预测肽的结构

• 批准号: 2701646
• 负责人: Christodoulos Achilleus Floudas
• 金额: $ 13.78万
• 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/2701646
• 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：该项目的总体目的是改善我们的 理解三维结构的预测 寡肽，多肽和蛋白质。 根据他最近的 进展：（a）基于分解的全球优化方法，共和党， （b）分支并与凸函数变换的差异结合 全局优化方法，Alphabb，（c）GOP应用于 Lennard-Jones集群的结构预测，（d）应用 alphabb到小的无环分子，（e）alphabb的应用 与ecepp/3结合到天然存在的氨基酸和小 寡肽，（f）Alphabb与Ecepp/3的应用 Met-enkephalin及其与模拟退火和其他搜索的比较 方法，（g）将alphabb应用于脱甘氨酸，以及（h） 他在考虑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 接近全球最低肽的肽的能量构象， （iii）肽的势能超表面的鞍点 接近全球最小肽结构。 Floudas博士 计划关注以下目标： （a）研究中描述的确定性全球优化方法 初步研究第3.3节，用于（i）寡肽，例如leu- Enkephalin，Gramicidin s和Mellitin，（ii）掺入 溶剂化效应以及对Met-五肽的应用 在水存在的情况下，Enkephalin和Leu-enkephalin（III） 相对熵和相对自由能的计算，以及（iv） 受约束的肽系统。 （b）调查修改 （a）中的全局优化方法，以便扩展以处理 多肽分子，例如禽胰多肽，模型 纤维蛋白，例如胶原蛋白，以及球状蛋白，例如 牛胰蛋白酶抑制剂。 （c）研究总的地形 势能表面通过开发和应用新方法 确定肽能量hyersurface的鞍点 接近全球最低。 （d）开发分布式计算 用于（a），（b）和（c）的全局优化方法的算法，应用 它们将橄榄肽，多肽，蛋白质和开发工具 肽的三维结构的预测。