Computer models of protein mutants for predictions of behaviors of protein folding and aggregation

用于预测蛋白质折叠和聚集行为的蛋白质突变体计算机模型

• 批准号: 261719-2008
• 负责人: Linhananta, Apichart
• 金额: $ 1.31万
• 依托单位: Lakehead University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2009
• 资助国家: 加拿大
• 起止时间: 2009-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=426768
• 关键词: Computer; models; protein; mutants; predictions

In protein engineering protein's sequence structures are altered by substituting one or more residues on wild type proteins to produce mutants. The mutants often possess different native structures, and exibit different folding and binding behaviors than the original wild type proteins. Computer simulation models have been instrumental in understanding this medically important and scientifically revealing field. However, sophisticated software such as AMBER, CHARMM and GROMACS are too computationally intensive, while simplified Go models requires knowledge of the native structures, which are usually not available for mutants. This project constructs Go model of mutants based on the known (usually) structure of the wild type proteins. The novel method uses advance simulation software to construct the ground state mutant structures, and then employs computationally efficient Go models to study the folding and aggregation (binding) mechanisms of the mutants. If successful, the method will help to guide protein engineering experiments, and lead to designed proteins whose folding speed approach the so-called "protein folding speed limit", or to protein systems with altered functional roles.

在蛋白质工程中，通过替换野生型蛋白质上的一个或多个残基来产生突变体，从而改变蛋白质的序列结构。突变体通常具有不同的天然结构，并表现出与原始野生型蛋白不同的折叠和结合行为。计算机模拟模型在理解这一医学上重要且科学上具有启示意义的领域方面发挥了重要作用。然而，像AMBER， CHARMM和GROMACS这样的复杂软件计算量太大，而简化的围棋模型需要了解原生结构，这通常是不可用于突变体的。本项目基于已知（通常）野生型蛋白的结构构建突变体Go模型。该方法利用先进的仿真软件构建基态突变体结构，然后利用计算效率高的Go模型研究突变体的折叠和聚集（结合）机制。如果成功，该方法将有助于指导蛋白质工程实验，并导致设计的蛋白质的折叠速度接近所谓的“蛋白质折叠速度限制”，或者改变功能角色的蛋白质系统。