PARAMETERIZATION OF PROTEIN AMIDE VIBRATIONAL FORCE FIELD USING DENSITY FUNCTIO

这个子项目是许多研究子项目中的一个 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来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 红外吸收光谱已被证明可用于研究蛋白质在重要生化过程中的结构变化，如蛋白质折叠或酶反应。我们已经表明，基于密度泛函理论（DFT）的计算是非常有用的解释振动光谱的肽和简单的蛋白质基序。结合DFT计算的小肽片段和转移的振动参数，使我们能够计算非常大的肽结构的振动光谱。我们的目标是将DFT水平的振动计算扩展到蛋白质。对于蛋白质，由于不规则结构，转移方案变得低效，这需要对许多不同的小片段进行DFT计算。我们的目标是在DFT水平上推导出一组结构依赖的振动频率和强度参数，用于蛋白质中最常见的构象的小肽片段库。这些参数将允许模拟任何蛋白质结构的振动光谱。我们已经计算了一些二肽的光谱，并将使用NCSA计算机时间来获得三肽、四肽等的较长范围的振动耦合。为了有效地对这些较大肽的构象进行采样，我们将从蛋白质数据库中的已知蛋白质结构构建构象偏好图，并首先关注最普遍的基序。振动参数的构象依赖性将提供反馈，用于调整我们的采样以覆盖整个蛋白质构象空间。此外，我们将通过在计算中明确包括水分子来参数化溶剂化的影响。

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. Infrared absorption spectroscopy has proven its utility for studying structural changes in proteins during important biochemical processes, such as protein folding or enzyme reactions. We have shown that density functional theory (DFT) based calculations are extremely useful for interpreting vibrational spectra for peptides and simple protein motifs. Combination of DFT calculations for small peptide fragments and transfer of the vibrational parameters allowed us to calculate vibrational spectra for very large peptide structures. Our goal is to extend DFT-level vibrational calculations to proteins. For proteins the transfer scheme becomes inefficient due to irregular structures, which requires DFT calculations for many different small fragments. Our goal is to derive a set of structurally-dependent vibrational frequency and intensity parameters at the DFT level for a library of small peptide fragments with conformations that are most prevalent in proteins. These parameters will allow simulations of the vibrational spectra for any protein structure. We have already calculated a number of the dipeptide spectra and will use the NCSA computer time to obtain the longer-range vibrational couplings for tri-, tetra- etc. peptides. To efficiently sample the conformations of these larger peptides, we will construct maps for conformational preferences from known protein structures in the Protein Data Bank and initially focus on the most prevalent motifs. The conformational dependence of the vibrational parameters will provide feedback for adapting our sampling to cover the entire protein conformational space. In addition, we will parameterize the effect of solvation by explicitly including water molecules in the calculations.