Simulation of Multi-Protein systems

多蛋白系统的模拟

基本信息

批准号：
10680446
负责人：
Dmytro Kozakov
金额：
$ 31.08万
依托单位：
STATE UNIVERSITY NEW YORK STONY BROOK
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-20 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10680446
关键词：
3-Dimensional Agreement Algorithms Alzheimer&apos s disease model Aprotinin Area Award Binding Biological Models Biological Products Bovine Serum Albumin Capsid Cell physiology Cells Cellular biology Collaborations Complex Crowding Data Development Disease Erythrocytes Evaluable Disease Evaluation Formulation Fourier Transform Goals Grant Hemoglobin Image Compression Liquid substance Mass Spectrum Analysis Memory Methods Minor Modeling Molecular Conformation Multiprotein Complexes Mycoplasma genitalium National Institute of General Medical Sciences Nucleosome Core Particle Pathway interactions Peptides Performance Pharmaceutical Preparations Property Protein Conformation Proteins Resolution Rest Sampling Speed Structure Sum System Validation Variant Writing experimental group experimental study flexibility gamma-Crystallins improved innovation insight method development molecular assembly/self assembly molecular modeling mouse model multicatalytic endopeptidase complex novel strategies particle protein aggregation self assembly simulation therapeutic development

3-Dimensional Agreement Algorithms Alzheimer&apos s disease model Aprotinin Area Award Binding Biological Models Biological Products Bovine Serum Albumin Capsid Cell physiology Cells Cellular biology Collaborations Complex Crowding Data Development Disease Erythrocytes Evaluable Disease Evaluation Formulation Fourier Transform Goals Grant Hemoglobin Image Compression Liquid substance Mass Spectrum Analysis Memory Methods Minor Modeling Molecular Conformation Multiprotein Complexes Mycoplasma genitalium National Institute of General Medical Sciences Nucleosome Core Particle Pathway interactions Peptides Performance Pharmaceutical Preparations Property Protein Conformation Proteins Resolution Rest Sampling Speed Structure Sum System Validation Variant Writing experimental group experimental study flexibility gamma-Crystallins improved innovation insight method development molecular assembly/self assembly molecular modeling mouse model multicatalytic endopeptidase complex novel strategies particle protein aggregation self assembly simulation therapeutic development

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项目摘要

Simulation of large multi-component molecular assemblies with atomistic details is an important step toward understanding cellular processes. The goal of this proposal is to develop an efficient method for the simulation of multi-protein systems consisting of many copies of a few types of proteins, each in a number of discrete conformations. The basis for our approach is the observation that the interaction energy between two proteins (or discrete protein conformations within an ensemble) – can be efficiently calculated over the entire rotational-translational space using the fast Manifold Fourier transform (FMFT) correlation approach. Given any conformation of a complex multi-particle system, its energy can be easily obtained by summing the pairwise interaction energies extracted from the lookup tables. The key innovation to efficiently implement this method is our ability to compress and store the interaction energy lookup tables in memory using wavelet sets. We will apply the method in two application. The first is simulation of multi-protein assemblies and their association pathways, possibly in conjunction with low resolution Mass Spectrometry (MS) and EM data, providing mechanistic insight into cellular function. The second is simulation of protein aggregation and crowding, which is important for the fundamental understanding of cell biology and therapeutic development.

模拟具有原子细节的大型多组分分子组件是一个重要的迈向理解细胞过程的一步。该建议的目的是开发用于模拟多蛋白系统的有效方法，该系统由许多副本组成蛋白质的类型，每种蛋白质都具有多种离散构象。我们方法的基础是观察到两种蛋白质之间的相互作用能（或离散蛋白构象在合奏中） - 可以在整个旋转转换空间中有效计算使用快速歧管傅立叶变换（FMFT）相关方法。给定任何构象复杂的多粒子系统的能量可以通过成对来轻松获得从查找表中提取的相互作用能。有效的关键创新实施此方法是我们压缩和存储交互能量查找表的能力在内存中使用小波集。我们将在两个应用程序中应用该方法。第一个是多蛋白组件及其关联途径的仿真分辨率低质谱（MS）和EM数据，提供机械洞察力细胞功能。第二个是模拟蛋白质聚集和拥挤的模拟对细胞生物学和治疗发展的基本了解至关重要。