title: DOGS: reaction-driven de novo design of bioactive compounds.
abstract: We present a computational method for the reaction-based de novo design of drug-like molecules. The software DOGS (Design of Genuine Structures) features a ligand-based strategy for automated 'in silico' assembly of potentially novel bioactive compounds. The quality of the designed compounds is assessed by a graph kernel method measuring their similarity to known bioactive reference ligands in terms of structural and pharmacophoric features. We implemented a deterministic compound construction procedure that explicitly considers compound synthesizability, based on a compilation of 25'144 readily available synthetic building blocks and 58 established reaction principles. This enables the software to suggest a synthesis route for each designed compound. Two prospective case studies are presented together with details on the algorithm and its implementation. De novo designed ligand candidates for the human histamine H₄ receptor and γ-secretase were synthesized as suggested by the software. The computational approach proved to be suitable for scaffold-hopping from known ligands to novel chemotypes, and for generating bioactive molecules with drug-like properties.
authors.affiliation: Swiss Federal Institute of Technology (ETH), Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, Zürich, Switzerland.
authors.forename: Markus
authors.initials: M
authors.lastname: Hartenfeller
authors.forename: Heiko
authors.initials: H
authors.lastname: Zettl
authors.forename: Miriam
authors.initials: M
authors.lastname: Walter
authors.forename: Matthias
authors.initials: M
authors.lastname: Rupp
authors.forename: Felix
authors.initials: F
authors.lastname: Reisen
authors.forename: Ewgenij
authors.initials: E
authors.lastname: Proschak
authors.forename: Sascha
authors.initials: S
authors.lastname: Weggen
authors.forename: Holger
authors.initials: H
authors.lastname: Stark
authors.forename: Gisbert
authors.initials: G
authors.lastname: Schneider
mesh_terms: D000465:Algorithms; D053829:Amyloid Precursor Protein Secretases / Q000378:metabolism; D001331:Automation; D019295:Computational Biology / Q000379:methods*; D003201:Computers; D015195:Drug Design; D006801:Humans; D008024:Ligands; D008956:Models, Chemical; D015233:Models, Statistical; D015394:Molecular Structure; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry; D011968:Receptors, Histamine / Q000737:chemistry; D000074040:Receptors, Histamine H4; D012984:Software; D013678:Technology, Pharmaceutical
chemical_list: C418607:HRH4 protein, human; D008024:Ligands; D043562:Receptors, G-Protein-Coupled; D011968:Receptors, Histamine; D000074040:Receptors, Histamine H4; D053829:Amyloid Precursor Protein Secretases