DEVELOPMENT AND APPLICATION OF A HIERARCHICAL PROTOCOL FOR AB INITIO PREDICTION

该子项目是利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 目前计算生物学和生物信息学的研究主要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，仅仅三维结构不足以理解许多涉及蛋白质的生物化学过程。本提案中提出的研究基于我们基于物理学的粗粒度力场UNRES的参数化，不仅使用有关蛋白质天然状态的三维结构的信息，还使用有关其折叠机制和热力学稳定性的信息。我们期望这样的参数化和广泛的构象空间搜索使用分子动力学将使我们能够同时预测两个蛋白质的性质：结构和热力学稳定性的天然状态和折叠途径（S），导致从未折叠到折叠状态。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Most of current research in computational biology and bioinformatics is focused on predicting the three-dimensional structure of proteins. Using different approaches, researchers are trying to develope methodology for predicting protein structure based only on amino acid sequence. However, three-dimensional structure alone is not sufficient to understand many biochemical processes which involve proteins. Research presented in this proposal is based on parametrization of our physics-based coarse-grained force-field 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 parametrization and extensive conformational space search using molecular dynamics will 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.