The Chemistry Development Kit (CDK) is a freely available open-source Java library for Structural Chemo-and Bioinformatics. Its architecture and capabilities as well as the development as an open-source project by a team of international collaborators from academic and industrial institutions is described. The CDK provides methods for many common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc. Application scenarios as well as access information for interested users and potential contributors are given.

The Chemistry Development Kit (CDK) is a freely available open-source Java library for Structural Chemoand Bioinformatics. Its architecture and capabilities as well as the development as an open-source project by a team of international collaborators from academic and industrial institutions is described. The CDK provides methods for many common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc. Application scenarios as well as access information for interested users and potential contributors are given.

An evolutionary algorithm (EA) using a graph-based data structure to explore the molecular constitution space is presented. The EA implementation proves to be a promising alternative to deterministic approaches to the problem of computer-assisted structure elucidation (CASE). While not relying on any external database, the EA-guided CASE program SENECA is able to find correct solutions within calculation times comparable to that of other CASE expert systems. The implementation presented here significantly expands the size limit of constitutional optimization problems treatable with evolutionary algorithms by introducing novel efficient graph-based genetic operators. The new EA-based search strategy is discussed including the underlying data structures, component design, parameter optimization, and evolution process control. Typical structure elucidation examples are given to demonstrate the algorithm's performance.

Computers in chemistryComputers in chemistry V 0380 Evolutionary-Algorithm-Based Strategy for Computer-Assisted Structure Elucidation. -(HAN, Y.; STEINBECK*, C.; J. Chem. Inf. Comput. Sci. 44 (2004) 2, 489-498; MPI Chem. Oekol., D-07745 Jena, Germany; Eng.) -Lindner 25-224

The analysis of biochemical pathways has recently gained much interest as these are the processes that keep us alive. A deeper understanding of biochemical reactions must analyze them at atomic resolution. In order to achieve that we have developed a reaction database with the information on the well known Biochemical Pathways wall chart. Based on that, 3D models of the substrates and intermediates of biochemical reactions can be built. It is shown how this information can be used for searching for inhibitors of enzyme catalyzed reactions by superimposition of 3D structures with a genetic algorithm. Physicochemical properties of the bonds directly involved in the reaction event allow a classification of these enzyme catalyzed reactions by self-organizing neural networks. This classification is compared with the enzyme code (EC) classification.