title: Concepts and applications of "natural computing" techniques in de novo drug and peptide design.
abstract: Evolutionary algorithms, particle swarm optimization, and ant colony optimization have emerged as robust optimization methods for molecular modeling and peptide design. Such algorithms mimic combinatorial molecule assembly by using molecular fragments as building-blocks for compound construction, and relying on adaptation and emergence of desired pharmacological properties in a population of virtual molecules. Nature-inspired algorithms might be particularly suited for bioisosteric replacement or scaffold-hopping from complex natural products to synthetically more easily accessible compounds that are amenable to optimization by medicinal chemistry. The theory and applications of selected nature-inspired algorithms for drug design are reviewed, together with practical applications and a discussion of their advantages and limitations.
authors.affiliation: Goethe-University, Department of Biochemistry, Chemistry, and Pharmacy, Frankfurt am Main, Germany.
authors.forename: Jan A
authors.initials: JA
authors.lastname: Hiss
authors.forename: Markus
authors.initials: M
authors.lastname: Hartenfeller
authors.forename: Gisbert
authors.initials: G
authors.lastname: Schneider
mesh_terms: D000465:Algorithms; D001688:Biological Products / Q000737:chemistry*; D020650:Combinatorial Chemistry Techniques / Q000379:methods; D019020:Directed Molecular Evolution / Q000379:methods; D015195:Drug Design; D010455:Peptides / Q000737:chemistry*; D004364:Pharmaceutical Preparations / Q000737:chemistry; D010946:Plants, Medicinal / Q000737:chemistry
chemical_list: D001688:Biological Products; D010455:Peptides; D004364:Pharmaceutical Preparations