Bioisosteric Similarity of Molecules Based on Structural Alignment and Observed Chemical Replacements in Drugs

The algorithmic concept used to assess the evolutionary relationship between protein sequences was adopted to the comparison of drug-like compounds. For this purpose, we have developed a method that uses the SMILES representation of the molecules to perform the corresponding pairwise alignment. The necessary exchange matrix was generated in an automated procedure that reflects the frequencies of chemical replacements in pharmaceutical substances. From the resulting alignment, the relationship between two molecules is computed as so-called bioisosteric similarity. This measure was used to perform virtual screening in several publicly available substance databases. We observed that databases containing drug-like compounds throughout showed higher bioisosteric similarities to the query compound than our reference set of confirmed nondrugs. Likewise, most actual drugs within a class show a higher bioisosteric similarity than the large background of other substances. The compounds obtained as highest ranking hits from the lead-like subset of the ZINC library showed distinct differences in comparison with corresponding results from a fingerprint-based similarity search, as well as the FTrees method. In particular the kind of chemical replacements as well as the conservation of substructures strongly reflect the underlying bioisosteric exchanges. Moreover, the bioisosteric similarity was used to assess the chemical diversity of the utilized drug classes and to compute the “average” molecule within the respective class.

本研究将用于评估蛋白质序列进化关系的算法概念，适配至类药化合物（drug-like compounds）的比对任务中。为此，我们开发了一种基于分子简化分子线性输入规范（SMILES）表示法的成对比对方法。我们通过自动化流程生成了所需的化学替换矩阵，该矩阵可反映药物类物质中化学替换的发生频率。基于所得的比对结果，可计算得到两个分子间的关联度，即所谓的生物电子等排相似性（bioisosteric similarity）。该相似性度量被应用于多个公开可用的物质数据库，以开展虚拟筛选（virtual screening）。我们观察到，整体而言包含类药化合物的数据库，相较于我们所构建的确认非药物参考集，与查询化合物的生物电子等排相似性更高。同样，同一类别中的多数实际药物，相较于其他物质构成的庞大背景集，其生物电子等排相似性也更高。从ZINC数据库的先导样分子子集（lead-like subset）中筛选得到的最高排名命中化合物，与基于指纹的相似性搜索（fingerprint-based similarity search）以及FTrees方法所得的对应结果相比，存在显著差异。具体而言，化学替换的类型以及子结构的保守性，可强烈反映出背后的生物电子等排替换关系。此外，生物电子等排相似性还被用于评估所选用药物类别的化学多样性，并计算对应类别内的"平均"分子。