Computational mapping of proteins for the binding of ligands

描述(由申请者提供)：该提案要求续期“用于配体结合的蛋白质计算图谱”的资助。全球作图使用分子探针--小分子或功能基团--对目标蛋白质的表面进行采样，以确定潜在的有利结合位置。该方法基于X射线和核磁共振筛选研究，表明蛋白质的结合部位也结合了大量碎片大小的分子。我们开发了基于快速傅立叶变换(FFT)相关方法的多阶段映射算法FTMAP(可在http://ftmap.bu.edu/)作为服务器使用)，绘制了大量蛋白质的图谱，并建立了可药性标准。这次更新的总体目标是将该方法扩展到预测特定功能组的偏好，并进一步提高预测的稳健性。第一个目标将通过开发包括许多不同探针中的每个重要官能团的大型探针库、识别在相同位置处结合的探针中出现的重叠官能团的特殊(功能)聚类算法以及迭代映射来实现 一种算法，增强了包含上一轮确定的官能团的探针中的探针集。一旦找到官能团，将使用随机路线图模拟来验证他们对特定地点的偏好，以确保他们减少了逃离地点的倾向。该方法将在基于FFT的映射算法中直接考虑配体和蛋白质的灵活性。这将进一步提高具有挑战性的问题中位点预测的可靠性，允许使用更复杂的探针，并使我们能够考虑目前假定为刚性蛋白质的地图服务器的灵活性。作为该提案的重要组成部分，我们将整合计算和X射线晶体映射方法，通过计算映射预先选择用于X射线筛选的化合物。该方法将通过绘制模型系统和当前药物感兴趣的系统来验证。预测和观察到的相互作用的比较将有助于我们更好地理解支配片段大小的分子与蛋白质功能位点结合的原理，并进一步改进图谱。我们还将研究一些有趣的分子识别问题，包括识别蛋白质-蛋白质界面上的可用药部位，识别变构部位，将图谱延伸到膜蛋白质，以及确定大环化合物的重要官能团。

DESCRIPTION (provided by applicant): The proposal requests the renewal of the grant "Computational Mapping of Proteins for the Binding of Ligands". Mapping globally samples the surface of target proteins using molecular probes - small molecules or functional groups - to identify potentially favorable binding positions. The method is based on X-ray and NMR screening studies showing that the binding sites of proteins also bind a large variety of fragment-sized molecules. We have developed the multi-stage mapping algorithm FTMAP (available as a server at http://ftmap.bu.edu/) based on the fast Fourier transform (FFT) correlation approach, mapped a large number of proteins, and established criteria for druggability. The general goals of this renewal are extending the method toward predicting preferences for specific functional groups and further improving the robustness of the predictions. The first goal will be achieved by developing large probe libraries that include each important functional group in many different probes, a special ("functional") clustering algorithm to identify the overlapping functional groups that occur in probes binding at the same location, and an iterative mapping algorithm which enhances the probe set in probes containing the functional groups identified in the previous round. Once functional groups are found, their preference for the particular site will be validated using stochastic roadmap simulations to assure that they have reduced tendency to escape from the site. The method will account for ligand and protein flexibility directly within the FFT-based mapping algorithm. This will further improve the reliability of site prediction in challenging problems, will allow for the use of more complex probes, and will enable us to consider flexibility in our mapping server which at present assumes a rigid protein. As an important part of the proposal, we will integrate computational and X-ray crystallographic mapping methods by pre-selecting the compounds for the X-ray based screening by computational mapping. The approach will be validated by mapping model systems and systems of current pharmaceutical interests. The comparison of predicted and observed interactions will help us to better understand the principles that govern the binding of fragment-sized molecules to functional sites of proteins, and to further improve the mapping. We will also study a number of interesting molecular recognition problems, including the identification of druggable sites in protein-protein interfaces, the identification of allosteric sites; extension of mapping to membrane proteins; and determining the important functional groups of macrocyclic compounds.