Receptor ligand binding: complex structure prediction and affinity evaluation

受体配体结合：复杂结构预测和亲和力评估

• 批准号: 46076684
• 负责人: Professor Dr. Rainer Böckmann
• 金额: --
• 依托单位: Professur Computational Biology
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2007
• 资助国家: 德国
• 起止时间: 2006-12-31 至 2010-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/46076684?language=en
• 关键词: Receptor; ligand; binding; complex; structure

The reliable and fast computation of binding free energies of small molecules to the active sites of proteins is crucial for structure-based drug design and for the understanding of protein-ligand interactions. Rigorous treatments involve computationally expensive methods like free energy perturbation approaches, which are, however, incompatible with the need for fast methods in e.g. drug screening or lead discovery. In turn, commonly used fast methods involve empirically derived scoring functions and usually do not include receptor and/or ligand flexibility. Hence, such methods are inherently limited in accuracy. The proposed project aims at the development of a fast conformational search for possible proteinligand conformations based on available structural data combined with a physical effective energy function for the computation of free energy differences. The first step involves the efficient prediction of protein-ligand conformations based on geometric considerations, aimed at efficiently sampling the available configurational space of ligand-receptor conformations. Subsequently, entropy estimates are used for weighting of the sampled conformations, in order to generate canonical ensembles. These ensembles allow an accurate determination of binding energies by (ensemble) averaging an energy function which is based on physical chemistry (force field) and an efficient continuum electrostatic approach to evaluate solvation free energy. Together, these two steps — the generation of alternative conformations and the computation of free energies using canonical ensemble averaging—are anticipated to allow an accurate and efficient estimation of relative binding affinities. In subsequent steps the method may be extended towards novel lead discovery or docking strategies, fully taking into account protein and ligand flexibilities.

小分子与蛋白质活性位点的结合自由能的可靠和快速计算对于基于结构的药物设计和蛋白质-配体相互作用的理解至关重要。严格的治疗涉及计算上昂贵的方法，如自由能微扰方法，然而，这与快速方法的需求不相容，例如药物筛选或先导发现。反过来，常用的快速方法涉及经验得出的评分函数，通常不包括受体和/或配体的灵活性。因此，这样的方法固有地在准确性方面受到限制。拟议的项目旨在开发一个快速的构象搜索可能的proteinligand构象的基础上，结合现有的结构数据与物理有效能量函数的自由能差的计算。第一步涉及基于几何考虑的蛋白质-配体构象的有效预测，旨在有效地采样配体-受体构象的可用构型空间。随后，熵估计用于加权的采样构象，以产生典型的系综。这些合奏允许一个准确的结合能的测定（合奏）平均的能量函数，这是基于物理化学（力场）和一个有效的连续静电的方法来评估溶剂化自由能。总之，这两个步骤-替代构象的生成和使用典型的系综平均的自由能的计算-预计允许相对结合亲和力的准确和有效的估计。在随后的步骤中，该方法可以扩展到新的铅发现或对接策略，充分考虑蛋白质和配体的灵活性。

项目成果

Dynamical characterization of two differentially disease associated MHC class I proteins in complex with viral and self-peptides.

两种与疾病相关的 MHC I 类蛋白与病毒和自身肽复合物的动态特征

• DOI: 10.1016/j.jmb.2011.11.021
• 发表时间: 2012
• 期刊: Journal of molecular biology
• 影响因子: 5.6
• 作者: Daniele Narzi;Caroline M. Becker;Maria Teresa Fiorillo;Barbara Uchanskao Ziegler;Andreas Ziegler;Rainer A. Böckmann
• 通讯作者: Rainer A. Böckmann