Klebe G, Mietzner T
BASF AG, Main Laboratory, Ludwigshafen, Germany.
J Comput Aided Mol Des. 1994 Oct;8(5):583-606. doi: 10.1007/BF00123667.
Mutual binding between a ligand of low molecular weight and its macromolecular receptor demands structural complementarity of both species at the recognition site. To predict binding properties of new molecules before synthesis, information about possible conformations of drug molecules at the active site is required, especially if the 3D structure of the receptor is not known. The statistical analysis of small-molecule crystal data allows one to elucidate conformational preferences of molecular fragments and accordingly to compile libraries of putative ligand conformations. A comparison of geometries adopted by corresponding fragments in ligands bound to proteins shows similar distributions in conformations space. We have developed an automatic procedure that generates different conformers of a given ligand. The entire molecule is decomposed into its individual ring and open-chain torsional fragments, each used in a variety of favorable conformations. The latter ones are produced according to the library information about conformational preferences. During this building process, an extensive energy ranking is applied. Conformers ranked as energetically favorable are subjected to an optimization in torsion angle space. During minimization, unfavorable van der Waals interactions are removed while keeping the open-chain torsion angles as close as possible to the experimentally most frequently observed values. In order to assess how well the generated conformers map conformation space, a comparison with experimental data has been performed. This comparison gives some confidence in the efficiency and completeness of this approach. For some ligands that had been structurally characterized by protein crystallography the program was used to generate sets of some 10 to 100 conformers. Among these, geometries are found that fall convincingly close to the conformations actually adopted by these ligands at the binding site.
低分子量配体与其大分子受体之间的相互结合要求两种物质在识别位点具有结构互补性。为了在合成前预测新分子的结合特性，需要有关药物分子在活性位点可能构象的信息，特别是在受体的三维结构未知的情况下。小分子晶体数据的统计分析使人们能够阐明分子片段的构象偏好，并据此编制假定配体构象库。与结合到蛋白质上的配体中相应片段所采用的几何形状的比较显示，构象空间中的分布相似。我们开发了一种自动程序，可生成给定配体的不同构象异构体。整个分子被分解为其各个环状和开链扭转片段，每个片段都以各种有利构象使用。后者是根据有关构象偏好的库信息生成的。在这个构建过程中，应用了广泛的能量排序。被评为能量有利的构象异构体在扭转角空间中进行优化。在最小化过程中，消除不利的范德华相互作用，同时使开链扭转角尽可能接近实验中最常观察到的值。为了评估生成的构象异构体对构象空间的映射程度，已与实验数据进行了比较。这种比较使人们对该方法的效率和完整性有了一定的信心。对于一些已通过蛋白质晶体学进行结构表征的配体，该程序用于生成约10至100个构象异构体的集合。在这些构象异构体中，发现了一些几何形状与这些配体在结合位点实际采用的构象非常接近。
