Models of protein-ligand crystal structures: trust, but verify.
Models of protein-ligand crystal structures: trust, but verify.
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DOI：
10.1007/s10822-015-9833-8
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发表时间：
2015-09
影响因子：
3.5
通讯作者：
Rupp B
中科院分区：
文献类型：
--
作者：
Deller MC;Rupp B
X射线晶体学提供了最精确的蛋白质-配体结构模型。这些模型作为许多计算方法的基础，包括结构预测，分子建模和基于结构的药物设计。这些计算方法的成功最终取决于底层蛋白质-配体模型的质量。X射线晶体学提供了一个明确的数学形式与蛋白质配体模型的实验数据的无与伦比的优势。在X射线晶体学的情况下，主要的实验证据是形成晶体的分子的电子密度。生成准确和精确的晶体学模型的第一步是解释晶体的电子密度，通常通过构建原子模型来进行。然后，原子模型必须进行验证，以适应实验的电子密度，并与先前的预期的立体化学协议。严格验证的蛋白质配体模型已成为可能的结果，强制性沉积的主要衍射数据，许多计算工具，现在可以帮助验证过程。蛋白质-配体复合物的验证揭示了配体密度的非热情解释的一些实例。蛋白质配体质量验证的基本概念和指标进行了讨论，我们强调软件工具，以协助在这个过程中。最终用户选择高质量的蛋白质-配体模型用于其计算和生物学研究是至关重要的，我们提供了如何实现这一目标的概述。
X-ray crystallography provides the most accurate models of protein–ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein–ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein–ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein–ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein–ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein–ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein–ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.