title: Rational Polypharmacology: Systematically Identifying and Engaging Multiple Drug Targets To Promote Axon Growth.
abstract: Mammalian central nervous system (CNS) neurons regrow their axons poorly following injury, resulting in irreversible functional losses. Identifying therapeutics that encourage CNS axon repair has been difficult, in part because multiple etiologies underlie this regenerative failure. This suggests a particular need for drugs that engage multiple molecular targets. Although multitarget drugs are generally more effective than highly selective alternatives, we lack systematic methods for discovering such drugs. Target-based screening is an efficient technique for identifying potent modulators of individual targets. In contrast, phenotypic screening can identify drugs with multiple targets; however, these targets remain unknown. To address this gap, we combined the two drug discovery approaches using machine learning and information theory. We screened compounds in a phenotypic assay with primary CNS neurons and also in a panel of kinase enzyme assays. We used learning algorithms to relate the compounds' kinase inhibition profiles to their influence on neurite outgrowth. This allowed us to identify kinases that may serve as targets for promoting neurite outgrowth as well as others whose targeting should be avoided. We found that compounds that inhibit multiple targets (polypharmacology) promote robust neurite outgrowth in vitro. One compound with exemplary polypharmacology was found to promote axon growth in a rodent spinal cord injury model. A more general applicability of our approach is suggested by its ability to deconvolve known targets for a breast cancer cell line as well as targets recently shown to mediate drug resistance.
authors.forename: Hassan
authors.initials: H
authors.lastname: Al-Ali
authors.forename: Do-Hun
authors.initials: DH
authors.lastname: Lee
authors.forename: Matt C
authors.initials: MC
authors.lastname: Danzi
authors.affiliation: ⊥Core Machine Learning Science Team, Amazon, Seattle, Washington 98109, United States.
authors.forename: Houssam
authors.initials: H
authors.lastname: Nassif
authors.affiliation: #Institute for Molecular Medicine Finland, University of Helsinki, Helsinki FI-00014, Finland.
authors.forename: Prson
authors.initials: P
authors.lastname: Gautam
authors.affiliation: #Institute for Molecular Medicine Finland, University of Helsinki, Helsinki FI-00014, Finland.
authors.forename: Krister
authors.initials: K
authors.lastname: Wennerberg
authors.affiliation: ○Department of Chemical Biology, GlaxoSmithKline, Research Triangle Park, North Carolina 27709, United States.
authors.forename: Bill
authors.initials: B
authors.lastname: Zuercher
authors.affiliation: ○Department of Chemical Biology, GlaxoSmithKline, Research Triangle Park, North Carolina 27709, United States.
authors.forename: David H
authors.initials: DH
authors.lastname: Drewry
authors.forename: Jae K
authors.initials: JK
authors.lastname: Lee
authors.forename: Vance P
authors.initials: VP
authors.lastname: Lemmon
authors.forename: John L
authors.initials: JL
authors.lastname: Bixby
mesh_terms: D000818:Animals; D002478:Cells, Cultured; D002490:Central Nervous System / Q000166:cytology / Q000187:drug effects / Q000502:physiology; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D000069550:Machine Learning; D009416:Nerve Regeneration / Q000187:drug effects*; D016501:Neurites / Q000187:drug effects* / Q000502:physiology; D009474:Neurons / Q000187:drug effects* / Q000502:physiology; D064798:Polypharmacology; D047428:Protein Kinase Inhibitors / Q000494:pharmacology*; D011494:Protein Kinases / Q000235:genetics / Q000378:metabolism; D034741:RNA, Small Interfering / Q000235:genetics; D051381:Rats
chemical_list: D047428:Protein Kinase Inhibitors; D034741:RNA, Small Interfering; D011494:Protein Kinases