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An Algorithm to Identify Target-Selective Ligands – A Case Study of 5-HT7/5-HT1A Receptor Selectivity

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  • Rafał Kurczab
  • Vittorio Canale
  • Paweł Zajdel
  • Andrzej J Bojarski

Abstract

A computational procedure to search for selective ligands for structurally related protein targets was developed and verified for serotonergic 5-HT7/5-HT1A receptor ligands. Starting from a set of compounds with annotated activity at both targets (grouped into four classes according to their activity: selective toward each target, not-selective and not-selective but active) and with an additional set of decoys (prepared using DUD methodology), the SVM (Support Vector Machines) models were constructed using a selective subset as positive examples and four remaining classes as negative training examples. Based on these four component models, the consensus classifier was then constructed using a data fusion approach. The combination of two approaches of data representation (molecular fingerprints vs. structural interaction fingerprints), different training set sizes and selection of the best SVM component models for consensus model generation, were evaluated to determine the optimal settings for the developed algorithm. The results showed that consensus models with molecular fingerprints, a larger training set and the selection of component models based on MCC maximization provided the best predictive performance.

Suggested Citation

  • Rafał Kurczab & Vittorio Canale & Paweł Zajdel & Andrzej J Bojarski, 2016. "An Algorithm to Identify Target-Selective Ligands – A Case Study of 5-HT7/5-HT1A Receptor Selectivity," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-18, June.
  • Handle: RePEc:plo:pone00:0156986
    DOI: 10.1371/journal.pone.0156986
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    References listed on IDEAS

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    1. Dawid Warszycki & Stefan Mordalski & Kurt Kristiansen & Rafał Kafel & Ingebrigt Sylte & Zdzisław Chilmonczyk & Andrzej J Bojarski, 2013. "A Linear Combination of Pharmacophore Hypotheses as a New Tool in Search of New Active Compounds – An Application for 5-HT1A Receptor Ligands," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    2. Brent R. Stockwell, 2004. "Exploring biology with small organic molecules," Nature, Nature, vol. 432(7019), pages 846-854, December.
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