Journal of Proteomics & Bioinformatics
Open Access

Mohamed Sadiq

Publications

• Research Article
  Support Vector Machine Classifier for Predicting Drug Binding to P-glycoprotein
  Author(s): Karthikeyan Ramaswamy, Mohamed Sadiq, Sridhar V and Nagasuma Chandra Karthikeyan Ramaswamy, Mohamed Sadiq, Sridhar V and Nagasuma Chandra
  
  Unforeseen reduction in bio-availability of drugs contribute heavily to late phase failure in drug discovery processes. P-glycoprotein, an efflux pump, that evicts a wide range of drugs is a major cause for reduction in bioavailability. Classification of potential drugs into binders and non-binders of this protein will aid greatly in weeding out the failures early in the discovery processes. The need to tap the power of computational approaches for such prediction is increasingly becoming evident, given the speed and ease with which predictions can be integrated into the discovery programs. In this paper, we report development of a prediction method to identify substrates and nonsubstrates of Pglycoprotein, based on a support vector machine algorithm. The method uses a combination of descriptors, encoding substructure types and their relative positions in the drug mol.. View More»
  DOI: 10.4172/jpb.1000077

  Abstract PDF

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