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SUMMARY:Can Lattice Theory Help Find a Cure for Paralysis? - Nicola Richmo
 nd\, GSK
DTSTART:20170131T160000Z
DTEND:20170131T170000Z
UID:TALK69579@talks.cam.ac.uk
CONTACT:CCA
DESCRIPTION:With the advent of the Human Genome Project came the industria
 lisation of the drug discovery process and a belief that combinatorial che
 mistry and high throughput screening would deliver molecules with increase
 d potency\, against a single target of interest. Yet the attrition rate is
  still at the 90% mark and there remain many human diseases for which no e
 ffective treatment exists. As Swinney et al have shown [1]\, there is comp
 elling evidence that first-in-class drugs are more likely to be found by a
 ssays that measure a clinically meaningful phenotype in a physiologically 
 relevant system rather than a single target based screening approach in an
  artificial setting.\n\nOne perceived issue with phenotypic screening is t
 he lack of mechanistic knowledge. Whilst understanding mechanism of action
  (MOA) is not a prerequisite for FDA approval\, it can guide a medicinal c
 hemistry effort\, predict potential toxicities and help define patient pop
 ulations for clinical trials and ultimately the market place. There are a 
 number of in vitro approaches to target deconvolution. However\, these ten
 d to be of lower throughput and better placed later in a screening cascade
 . So there is a real need for in silico based approaches that can be deplo
 yed early on in a drug discovery programme to identify potential MOAs.\n\n
 Using publicly available data on the Published Kinase Inhibitor Set (PKIS)
  [2\,3]\, we describe the application of Formal Concept Analysis (FCA)\, a
 n association mining technique with roots in set theory\, to the problem o
 f deconvoluting a phenotypic screen. We describe each compound in the PKIS
  by the set of kinases it inhibits. We then construct a Galois Lattice\, w
 hose nodes correspond to a set of compounds inhibiting a common set of kin
 ases and where two nodes are connected if the compound set of the child no
 de is a subset of the compound set of the parent node. Lattice nodes enric
 hed with compounds that promote neurite outgrowth in rat inform on which k
 inases should be targeted when seeking small molecules that encourage CNS 
 axon repair following injury. The targets we identify using this unsupervi
 sed and interpretable approach\, are in line with those identified in [3] 
 where here the authors use a combination of support vector machines\, cons
 idered a black box method\, and mutual information\, then confirm in siRNA
  studies.\n\n# Swinney DC\, Anthony J. How were new medicines discovered? 
 Nat Rev Drug Discov. 2011\;10:507–19.\n# Drewry DH\, Willson TM\, Zuerch
 er WJ. Seeding collaborations to advance kinase science with the GSK Publi
 shed Kinase Inhibitor Set (PKIS). Curr Top Med Chem 2014\;14:340–2.\n# A
 l-Ali H\, Lee DH\, Danzi MC\, Nassif H\, Gautam P\, Wennerberg K\, Zuerche
 r WJ\, Drewry DH\, Lee JK\, Lemmon VP\, Bixby JL. Rational polypharmacolog
 y: systematically identifying and engaging multiple drug targets to promot
 e axon growth. ACS Chem Biol 2015\;10:1939–51.
LOCATION:MR14
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