Michaelis Monika, Cupellini Lorenzo, Mensch Carl, Perry Carole C, Delle Piane Massimo, Colombi Ciacchi Lucio
Hybrid Materials Interfaces Group, Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, University of Bremen Am Fallturm 1 Bremen 28359 Germany
Biomolecular and Materials Interface Research Group, Interdisciplinary Biomedical Research Centre, School of Science and Technology, Nottingham Trent University Clifton Lane Nottingham NG11 8NS UK.
Chem Sci. 2023 Jul 19;14(32):8483-8496. doi: 10.1039/d3sc02202a. eCollection 2023 Aug 16.
The most advanced structure prediction methods are powerless in exploring the conformational ensemble of disordered peptides and proteins and for this reason the "protein folding problem" remains unsolved. We present a novel methodology that enables the accurate prediction of spectroscopic fingerprints (circular dichroism, infrared, Raman, and Raman optical activity), and by this allows for "tidying up" the conformational ensembles of disordered peptides and disordered regions in proteins. This concept is elaborated for and applied to a dodecapeptide, whose spectroscopic fingerprint is measured and theoretically predicted by means of enhanced-sampling molecular dynamics coupled with quantum mechanical calculations. Following this approach, we demonstrate that peptides lacking a clear propensity for ordered secondary-structure motifs are not randomly, but only conditionally disordered. This means that their conformational landscape, or phase-space, can be well represented by a basis-set of conformers including about 10 to 100 structures. The implications of this finding have profound consequences both for the interpretation of experimental electronic and vibrational spectral features of peptides in solution and for the theoretical prediction of these features using accurate and computationally expensive techniques. The here-derived methods and conclusions are expected to fundamentally impact the rationalization of so-far elusive structure-spectra relationships for disordered peptides and proteins, towards improved and versatile structure prediction methods.
最先进的结构预测方法在探索无序肽和蛋白质的构象集合时无能为力，因此“蛋白质折叠问题”仍然未得到解决。我们提出了一种新颖的方法，能够准确预测光谱指纹（圆二色性、红外、拉曼和拉曼光学活性），从而可以“整理”无序肽和蛋白质中无序区域的构象集合。针对一种十二肽阐述并应用了这一概念，通过增强采样分子动力学结合量子力学计算对其光谱指纹进行了测量和理论预测。按照这种方法，我们证明缺乏明显有序二级结构基序倾向的肽并非随机无序，而是有条件地无序。这意味着它们的构象景观或相空间可以由一组包含约10到100个结构的构象体很好地表示。这一发现对于解释溶液中肽的实验电子和振动光谱特征以及使用精确且计算成本高昂的技术对这些特征进行理论预测都具有深远影响。本文得出的方法和结论有望从根本上影响对迄今为止难以捉摸的无序肽和蛋白质结构 - 光谱关系的合理化，朝着改进和通用的结构预测方法发展。
