title: Evolving molecules using multi-objective optimization: applying to ADME/Tox.
abstract: Modern drug discovery involves the simultaneous optimization of many physicochemical and biological properties that transcends the historical focus on bioactivity alone. The process of resolving many requirements is termed 'multi-objective optimization', and here we discuss how this can be used for drug discovery, focusing on evolutionary molecule design to incorporate optimal predicted absorption, distribution, metabolism, excretion and toxicity properties. We provide several examples of how Pareto optimization implemented in Pareto Ligand Designer can be used to make trade-offs between these different predicted or real molecular properties to result in better predicted compounds.
authors.affiliation: Collaborations in Chemistry, 601 Runnymede Avenue, Jenkintown, PA 19046, USA. ekinssean@yahoo.com
authors.forename: Sean
authors.initials: S
authors.lastname: Ekins
authors.forename: J Dana
authors.initials: JD
authors.lastname: Honeycutt
authors.forename: James T
authors.initials: JT
authors.lastname: Metz
mesh_terms: D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D008024:Ligands; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D010599:Pharmacokinetics
chemical_list: D008024:Ligands; D004364:Pharmaceutical Preparations