PARAMETERIZATION OF PROTEIN AMIDE VIBRATIONAL FORCE FIELD USING DENSITY FUNCTIO

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 红外吸收光谱在研究蛋白质折叠或酶反应等重要生化过程中的结构变化方面已被证明是有用的。我们已经证明，基于密度泛函理论(DFT)的计算对于解释多肽和简单蛋白质基序的振动光谱是非常有用的。结合对小肽片段的密度泛函计算和振动参数的转移，我们可以计算非常大的多肽结构的振动光谱。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，由于结构不规则，转移方案变得效率低下，这需要对许多不同的小片段进行密度泛函计算。我们的目标是为蛋白质中最常见的构象的小肽片段文库在密度泛函水平上推导出一组与结构相关的振动频率和强度参数。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的计算机时间来获得三、四等多肽的较长距离的振动偶合。为了有效地采样这些较大多肽的构象，我们将根据蛋白质数据库中已知的蛋白质结构构建构象偏好图，并最初专注于最流行的基序。振动参数的构象依赖性将为我们的采样提供反馈，以覆盖整个蛋白质构象空间。此外，我们将通过在计算中显式地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.