MONA 2: A Light Cheminformatics Platform for Interactive Compound Library Processing

Because of the availability of large compound collections on the Web, elementary cheminformatics tasks such as chemical library browsing, analyzing, filtering, or unifying have become widespread in the life science community. Furthermore, the high performance of desktop hardware allows an interactive, problem-driven approach to these tasks, avoiding rigid processing scripts and workflows. Here, we present MONA 2, which is the second major release of our cheminformatics desktop application addressing this need. Using MONA requires neither complex database setups nor expert knowledge of cheminformatics. A new molecular set concept purely based on structural entities rather than individual compounds has allowed the development of an intuitive user interface. Based on a chemically precise, high-performance software library, typical tasks on chemical libraries with up to one million compounds can be performed mostly interactively. This paper describes the functionality of MONA, its fundamental concepts, and a collection of application scenarios ranging from file conversion, compound library curation, and management to the post-processing of large-scale experiments

Discriminative Chemical Patterns: Automatic and Interactive Design

The classification of molecules with respect to their inhibiting, activating, or toxicological potential constitutes a central aspect in the field of cheminformatics. Often, a discriminative feature is needed to distinguish two different molecule sets. Besides physicochemical properties, substructures and chemical patterns belong to the descriptors most frequently applied for this purpose. As a commonly used example of this descriptor class, SMARTS strings represent a powerful concept for the representation and processing of abstract chemical patterns. While their usage facilitates a convenient way to apply previously derived classification rules on new molecule sets, the manual generation of useful SMARTS patterns remains a complex and time-consuming process. Here, we introduce SMARTSminer, a new algorithm for the automatic derivation of discriminative SMARTS patterns from preclassified molecule sets. Based on a specially adapted subgraph mining algorithm, SMARTSminer identifies structural features that are frequent in only one of the given molecule classes. In comparison to elemental substructures, it also supports the consideration of general and specific SMARTS features. Furthermore, SMARTSminer is integrated into an interactive pattern editor named SMARTSeditor. This allows for an intuitive visualization on the basis of the SMARTSviewer concept as well as interactive adaption and further improvement of the generated patterns. Additionally, a new molecular matching feature provides an immediate feedback on a pattern’s matching behavior across the molecule sets. We demonstrate the utility of the SMARTSminer functionality and its integration into the SMARTSeditor software in several different classification scenarios

Index-Based Searching of Interaction Patterns in Large Collections of Protein–Ligand Interfaces

Comparison of three-dimensional interaction patterns in large collections of protein–ligand interfaces is a key element for understanding protein–ligand interactions and supports various steps in the structure-based drug design process. Different methods exist that provide query systems to search for geometrical patterns in protein–ligand complexes. However, these tools do not meet all of the requirements, which are high query variability, an adjustable search set, and high retrieval speed. Here we present a new tool named PELIKAN that is able to search for a variety of geometrical queries in large protein structure collections in a reasonably short time. The data are stored in an SQLite database that can easily be constructed from any set of protein–ligand complexes. We present different test queries demonstrating the performance of the PELIKAN approach. Furthermore, two application scenarios show the usefulness of PELIKAN in structure-based design endeavors