Development and Application of Generalized Ensemble Algorithms for Protein Studies

Ulrich Hansmann教授在理论化学和分子生物物理学项目的支持下，开发、分发和应用广义集成算法来研究蛋白质。这项工作的主要重点是复杂的方法发展和随后输出的结果方法对其他群体感兴趣的大规模模拟生物过程。具体来说，Hansmann开发了新的计算方法来提高有趣的低能态之间跃迁的频率。此外，对观察到的跃迁进行分析，以确定化学上相关的反应坐标。动机是基于需要提高模拟效率的一个数量级。这将通过包含先进的物理概念来实现。此外，一种计算溶质-溶质相互作用的精确方法正在开发中。应用集中于研究b-淀粉样肽的螺旋状和片状结构之间的相对稳定性和过渡。片状结构的形成和聚集是许多神经系统疾病的共同特征。蛋白质是生命系统中常见而又重要的一类分子。作为酶，蛋白质催化和调节细胞的生化反应。作为抗体，它们对免疫系统有贡献。由于这些功能与它们的三维形状密切相关，微小的缺陷会导致错误折叠，从而导致各种疾病。从计算机模拟中理解这些影响需要理论模型和用于研究模型表现形式的计算方法的额外复杂性。除了解决生化模拟的理论和计算问题外，这项工作还集中在理解b-淀粉样肽的错误折叠结构是如何形成和聚集的。这种异常结构的发生与阿尔茨海默病有关。

Professor Ulrich Hansmann is supported by the Theoretical Chemistry and Molecular Biophysics Programs to develop, distribute and apply generalized ensemble algorithms to the study of proteins. A primary emphasis of this work is on complicated methodological developments and subsequent export of resulting methodologies to other groups interested in large-scale simulation of biological processes. Specifically, Hansmann develops new means for computationally enhancing the frequency of transitions between interesting low-energy states. In addition, observed transitions are analyzed to determine chemically relevant reaction coordinates. Motivation is based on the need to increase simulation efficiency by an order of magnitude. This will be accomplished by inclusion of advanced physical concepts. In addition, an accurate means for accounting for solvent-solute interactions is being developed. Applications concentrate on investigating relative stabilities of and transitions between the helical and sheet-like structures of the b-amyloid peptide. Formation and aggregation of the sheet-like structures is a feature that is common to a number of neurological diseases.Proteins are a common yet important class of molecules in living systems. As enzymes, proteins catalyze and regulate a cell's biochemical reactions. As antibodies they contribute to the immune system. Since such functions are closely related to their three-dimensional shapes, small defects can cause misfolding which can cause a variety of diseases. Understanding these effects from computer simulation requires additional levels of complexity in both the theoretical models and in the computational approach employed to investigate the manifestations of the models. In addition to addressing the theoretical and computational issues for biochemical simulation, this work concentrates on understanding how misfolded structures of the b-amyloid peptide form and aggregate. The occurrence of such abnormal structures has been associated with Alzheimer's disease.