title: [In Silico Drug Design Using an Evolutionary Algorithm and Compound Database].
abstract: Computational drug design plays an important role in the discovery of new drugs. Recently, we proposed an algorithm for designing new drug-like molecules utilizing the structure of a known active molecule. To design molecules, three types of fragments (ring, linker, and side-chain fragments) were defined as building blocks, and a fragment library was prepared from molecules listed in G protein-coupled receptor (GPCR)-SARfari database. An evolutionary algorithm which executes evolutionary operations, such as crossover, mutation, and selection, was implemented to evolve the molecules. As a case study, some GPCRs were selected for computational experiments in which we tried to design ligands from simple seed fragments using the Tanimoto coefficient as a fitness function. The results showed that the algorithm could be used successfully to design new molecules with structural similarity, scaffold variety, and chemical validity. In addition, a docking study revealed that these designed molecules also exhibited shape complementarity with the binding site of the target protein. Therefore, this is expected to become a powerful tool for designing new drug-like molecules in drug discovery projects.
authors.affiliation: Drug Research Center, Kaken Pharmaceutical Co. Ltd.
authors.forename: Kentaro
authors.initials: K
authors.lastname: Kawai
authors.forename: Yoshimasa
authors.initials: Y
authors.lastname: Takahashi
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D062126:Databases, Chemical; D015195:Drug Design; D008024:Ligands; D015394:Molecular Structure
chemical_list: D008024:Ligands