Comparing Molecular Patterns Using the Example of SMARTS: Applications and Filter Collection Analysis.

In a recent work, an algorithm to compare chemical patterns, written for example in SMARTS, was presented. This algorithm, called SMARTScompare, is able to assess the identity, subset relation, and similarity of a pair of patterns. Here we used an implementation of SMARTScompare to analyze SMARTS filter sets that were published in the context of, for example, high-throughput screening. We found that the difference in intentions with which the filter sets were designed is mirrored in the similarity values we calculated. The analysis revealed which patterns from one filter set are covered by filters from another set. In one case it became obvious that a filter set is more or less completely covered by another. Furthermore, we analyzed pattern hierarchies for consistency, and we propose a method to remove redundant patterns. SMARTScompare together with SMARTScompareView equips users with powerful methods to visualize, compare, and focus their filter sets.

Comparing Molecular Patterns Using the Example of SMARTS: Theory and Algorithms.

Molecular patterns are widely used for compound filtering in molecular design endeavors. They describe structural properties that are connected with unwanted physical or chemical properties like reactivity or toxicity. With filter sets comprising hundreds of structural filters, an analytic approach to compare those patterns is needed. Here we present a novel approach to solve the generic pattern comparison problem. We introduce chemically inspired fingerprints for pattern nodes and edges to derive an easy-to-compare pattern representation. On two annotated pattern graphs we apply a maximum common subgraph algorithm enabling the calculation of pattern inclusion and similarity. The resulting algorithm can be used in many different ways. We can automatically derive pattern hierarchies or search in large pattern collections for more general or more specific patterns. To the best of our knowledge, the presented algorithm is the first of its kind enabling these types of chemical pattern analytics. Our new tool named SMARTScompare is an implementation of the approach for the SMARTS language, which is the quasi-standard for structural filters. We demonstrate the capabilities of SMARTScompare on a large collection of SMARTS patterns from real applications.