DEVELOPMENT AND APPLICATION OF A HIERARCHICAL PROTOCOL FOR AB INITIO PREDICTION

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 计算生物学是一种生物信息学，目前的大部分研究都集中在预测蛋白质的三维结构上。使用不同的方法，研究人员正试图开发仅基于氨基酸序列预测蛋白质结构的方法。然而，仅有三维结构并不足以理解许多涉及蛋白质的生物过程。本提案中提出的研究基于我们基于物理的粗粒度力场UNRES的参数化，不仅使用关于蛋白质天然状态的三维结构的信息，还使用关于其折叠机制和热力学稳定性的信息。我们希望这种参数化和广泛的分子动力学构象空间搜索使我们能够同时预测蛋白质的两个性质：天然状态的结构和热力学稳定性以及从未折叠到折叠状态的折叠路径(S)。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Most of current research in computational biology an bioinformatics is focused on predicting the three-dimensional structure of proteins. Using different approaches, researches are trying to develop methodology for predicting proteins structure based only on amino acid sequence. However, three-dimensional structure alone is not sufficient to understand many biological processes which involve proteins. Research presented in this proposal is based on parameterization of our physics-based coarse-grained force-filed UNRES using information not only about the three dimensional structure of the native state of proteins but also about their folding mechanism and thermodynamic stability. We expect that such parameterization and extensive conformational space search using molecular dynamics enable us to simultaneously predict two protein properties: structure and thermodynamic stability of the native state and folding pathway(s) which lead from the unfolded to the folded state.