COMBINED EXPERIMENTAL AND COMPUTATIONAL VIBRATIONAL ANALYSIS OF SHORT HELICAL P

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。 多肽和蛋白质的结构、稳定性和动力学取决于折叠和未折叠状态。这些状态在热力学和动力学上都是联系在一起的。蛋白质的未折叠状态过去被描述为随机卷曲；然而，最近的研究表明，除了天然和非天然的三级接触外，还存在显著的相互作用，包括残留的局部二级结构(如短的α-螺旋)。尽管展开状态很重要，但在类似自然的条件下描述这种状态的研究相对较少，因为在这些条件下，平衡常数强烈有利于折叠状态。因此，我们建议使用同位素编辑红外光谱结合密度泛函理论计算来研究蛋白质在未折叠状态下发现的短螺旋长度对光谱的依赖关系。这种方法通过使用非扰动的同位素标记来探查具有足够时间分辨率的多肽骨架构象和水化作用来研究感兴趣的分子动力学，从而提供残基特异性。具体地说，将研究含有4、8或11个螺旋氨基酸的螺旋多肽，这些螺旋氨基酸由La3结合环稳定，以克服短螺旋多肽的典型不稳定性。在使用CHARMM对多个温度下的分子动力学模拟得到几何优化后，将使用Gauss03中实现的密度泛函理论来计算这些多肽的红外光谱。这些计算对于考察红外光谱与螺旋长度的依赖关系以及分析与这些肽的展开相对应的实验红外光谱将是至关重要的。这些信息将被用作研究更大的多肽和蛋白质中未折叠状态结构的基础。计算将从8螺旋残基开始，因为它的核磁共振结构已知。其他多肽结构最初将通过去除或添加该多肽的C-末端的残基而生成。计算将集中在同位素标记对模型多肽振动光谱的影响，以及多肽主链构象和水合作用。与以往螺旋体系的密度泛函计算类似，通过固定多肽主链的位置，这些计算的计算成本将被最小化。这一策略将允许在有或没有显式水分子的情况下计算多肽的振动光谱，以帮助分析实验IR结果。DFT显式水计算将涉及将水分子放置在关键位置以模拟多肽骨架上的氢键。这些计算研究还将探讨使用非天然氨基酸(如丁腈衍生的丙氨酸和苯丙氨酸残基)作为多肽和蛋白质局部二级结构的探针的可能性。

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. The structure, stability and dynamics of peptides and proteins depend on both the folded and unfolded states. These states are linked both thermodynamically and kinetically. The unfolded state of proteins used to be characterized as a random coil; however, recent studies have shown the presence of significant interactions including residual local secondary structure (such as short alpha-helices) in addition to native and non-native tertiary contacts. Despite the importance of the unfolded state, relatively few studies have characterized this state under native-like conditions, since the equilibrium constant strongly favors the folded state under these conditions. Therefore, here we propose to use isotope-edited infrared spectroscopy coupled with density functional theory calculations to investigate the spectral dependence on the length of short ?-helices found in unfolded states of proteins. This method provides residue-specificity through the use of non-perturbing isotopic labels to probe the peptide backbone conformation and hydration with sufficient temporal resolution to study the molecular dynamics of interest. Specifically, helical peptides containing 4, 8 or 11 helical amino acids stabilized by a La3+ binding loop to overcome the typical instability of short helical peptides will be investigated. Density functional theory as implemented in Gaussian 03 will be used to calculate the infrared spectra of these peptides following geometric optimization of structures resulting from molecular dynamic simulations at multiple temperatures utilizing CHARMM. These calculations will be critical in the examination of the dependence of the IR spectra on helix length and the analysis of the experimental IR spectra corresponding to the unfolding of these peptides. This information will then be used as the basis for the study of unfolded state structure in larger peptides and proteins. The computations will start with the 8 helical residue peptide, since its NMR structure is known. The other peptide structures will be initially generated by the removal or addition of residues to the C-terminus of this peptide. The calculations will focus on the effect of isotopic labels on the vibrational spectra of the model peptides in addition to peptide backbone conformation and hydration. Similar to previous DFT calculations of helical systems, the computational cost of these calculations will be minimized by fixing the position of the peptide backbone. This strategy will permit the vibrational spectra of the peptides to be calculated with and without explicit water molecules aiding in the analysis of the experimentally IR results. The DFT explicit water calculations will involve the placement of water molecules in key positions to model H-bonding to the peptide backbone. These computational studies will also investigate the potential of using un-natural amino acids such as nitrile-derivatized alanine and phenylalanine residues as probes of local secondary structure in peptides and proteins.