The dynamic ensemble: exploring accessible conformational space

点击翻译按钮获取中文摘要

The functioning of the cells in our bodies is dependent upon the proper assembly, in time and location, of (often complicated) molecular complexes, that nearly always contain proteins. To understand the functioning of these so-called molecular machines, it is imperative that we know how they 'look', i.e. we need to know the arrangement of all the atoms that comprise the protein molecule in three-dimensional (3D) space. Moreover, these arrangements are not static; the protein molecules vibrate, deform and adapt their shape in response to their environment over time. It has become clear that these dynamic adaptations are key to the functional roles of these proteins and hence this has generated a profound interest in ways to study such dynamical properties.Structural biology is a field of biological science that studies 3D biomolecular structures, their dynamics and their interactions. Knowledge of these structures is essential in many areas of science and helps us understand the molecular basis of life and disease processes, design better drugs, improve the efficiency of enzymes used in the food, paper or agriculture industry, etc.X-ray crystallography and Nuclear Magnetic Resonance (NMR) spectroscopy are the two techniques that produce the overwhelming majority of biomolecular structures. Of the more than 100000 entries in the Protein Data Bank (PDB), a global repository for biomolecular structures, about 86% were determined using X-ray crystallography, while 13% come from NMR. X-ray structures are typically determined at a low temperature (-173 degree C) in a crystalline state and the technique does not naturally reveal information regarding dynamic properties. In contrast, the NMR data are acquired at room temperature in solution and are inherently affected by dynamic averaging processes occurring on a large range of time scales. This presents both a nuisance and an opportunity.This proposal aims to develop technology to extract knowledge about protein dynamics from easily available NMR data. We postulate that this information is inherently sufficient to derive a dynamically-representative structural ensemble that better accounts for both the experimental data and the actual protein conformation. Specifically, we plan to:1. Design and test a software pipeline for extraction of this dynamical information about proteins from readily available NMR data and convert it into an easily visualized form.2. Conduct a large-scale re-computation using the pipeline of the NMR-derived protein structures contained in the PDB.3. Test and explore the effect of small molecule docking using dynamically-representative structural ensembles.4. Setup a generally accessible server for the NMR community to execute the pipeline on their own projects.The structural information is deposited in the PDB by academic and industrial researchers from all over the world. We think that the better representation of dynamical information will increase the value of this data, yielding higher quality and more relevant result for usage by other scientists to advance our knowledge and understanding of human health, drug discovery, agriculture, etc.The project will be conducted in Leicester under the supervision of Prof. Vuister, a well-known expert in the field. Leicester's integrated structural biology research environment provides for a great scientific infrastructure and support. In addition, numerous other experts are connected to and support the project as well, thus extending its impact.