SMARTS.plus - A Toolbox for Chemical Pattern Design.

The number of publications concerning Pan-Assay Interference Compounds and related problematic structural motifs in screening libraries is constantly growing. In consequence, filter collections are merged, extended but also critically discussed. Due to the complexity of the chemical pattern language SMARTS, an easy-to-use toolbox enabling every chemist to understand, design and modify chemical patterns is urgently needed.

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.

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.

Exploring Structure-Activity Relationships with Three-Dimensional Matched Molecular Pairs-A Review.

A matched molecular pair (MMP) consists of two small molecules that differ by a few atoms only. The minor structural difference between the molecules allows a detailed analysis of changes in properties. Three-dimensional (3D) MMPs extend the concept of chemical similarity by spatial similarity.

Matched Molecular Series: Measuring SAR Similarity.

Suggesting novel compounds to be made on the basis of similarity to a previously seen structure-activity relationship (SAR) requires a measure for SAR similarity. While SAR similarity has intuitively been used by medicinal chemists for decades, no systematic comparison of candidate similarity metrics has been published to date. With this publication, we attempt to close that gap by providing a statistical framework that allows comparison of SAR similarity metrics by their ability to rank series that provide the best activity prediction of novel substituents.

Kinetic barriers in the isomerization of substituted ureas: implications for computer-aided drug design.

Urea derivatives are ubiquitously found in many chemical disciplines. N,N'-substituted ureas may show different conformational preferences depending on their substitution pattern. The high energetic barrier for isomerization of the cis and trans state poses additional challenges on computational simulation techniques aiming at a reproduction of the biological properties of urea derivatives.