PropertyValue
?:abstract
  • We introduce a family of positive definite kernels specifically optimized for the manipulation of 3D structures of molecules with kernel methods. The kernels are based on the comparison of the three-point pharmacophores present in the 3D structures of molecules, a set of molecular features known to be particularly relevant for virtual screening applications. We present a computationally demanding exact implementation of these kernels, as well as fast approximations related to the classical fingerprint-based approaches. Experimental results suggest that this new approach is competitive with state-of-the-art algorithms based on the 2D structure of molecules for the detection of inhibitors of several drug targets. ()
?:appearsInJournal
?:citationCount
  • 64 ()
is ?:cites of
?:cites
?:created
  • 2016-06-24 ()
?:creator
?:doi
  • 10.1021/ci060138m ()
?:endingPage
  • 2014 ()
?:estimatedCitationCount
  • 102 ()
is ?:hasCitedEntity of
?:hasDiscipline
?:hasURL
?:issueIdentifier
  • 5 ()
?:language
  • en ()
?:publicationDate
  • 2006-09-01 ()
?:publisher
  • American Chemical Society ()
?:rank
  • 19774 ()
?:referenceCount
  • 43 ()
?:startingPage
  • 2003 ()
?:title
  • The Pharmacophore Kernel for Virtual Screening with Support Vector Machines ()
?:type
?:volume
  • 46 ()

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