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Optimization of biaryl piperidine and 4-amino-2-biarylurea MCH1 receptor antagonists using QSAR modeling, classification techniques and virtual screening

Journal of Computer-Aided Molecular Design volume 21, pages 251–267 (2007)Cite this article

Abstract

This paper presents the results of an optimization study on biaryl piperidine and 4-amino-2-biarylurea MCH1 receptor antagonists, which was accomplished by using quantitative-structure activity relationships (QSARs), classification and virtual screening techniques. First, a linear QSAR model was developed using Multiple Linear Regression (MLR) Analysis, while the Elimination Selection-Stepwise Regression (ES-SWR) method was adopted for selecting the most suitable input variables. The predictive activity of the model was evaluated using an external validation set and the Y-randomization technique. Based on the selected descriptors, the Support Vector Machines (SVM) classification technique was utilized to classify data into two categories: “actives” or “non-actives”. Several attempts were made to optimize the scaffold of most potent compounds by inducing various structural modifications. Potential derivatives with improved activities were identified, as they were classified “actives” by the SVM classifier. Their activities were estimated using the produced MLR model. A detailed analysis on the model applicability domain defined the compounds, whose estimations can be accepted with confidence.

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Acknowledgments

G.M. thanks the Greek State Scholarship Foundation for a doctoral assistantship. A.A. wishes to thank Cyprus Research Promotion Foundation (Grant No. PENEK/ENISX/0603/05) and the Committee of Research of the National Technical University of Athens, Greece for a doctoral assistantship.

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Authors and Affiliations

  1. School of Chemical Engineering, National Technical University of Athens, Athens, Greece

    Georgia Melagraki, Antreas Afantitis, Haralambos Sarimveis & Olga Igglessi-Markopoulou

  2. Department of ChemoInformatics, NovaMechanics Ltd, Larnaca, Cyprus

    Antreas Afantitis

  3. Department of Chemistry, University of Cyprus, P.O. Box 20537, 1678 , Nicosia, Cyprus

    Panayiotis A. Koutentis

  4. Department of Chemistry, University of Athens, Athens, Greece

    John Markopoulos

Authors
  1. Georgia Melagraki
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  2. Antreas Afantitis
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  3. Haralambos Sarimveis
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  6. Olga Igglessi-Markopoulou
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Correspondence to Haralambos Sarimveis.

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Melagraki, G., Afantitis, A., Sarimveis, H. et al. Optimization of biaryl piperidine and 4-amino-2-biarylurea MCH1 receptor antagonists using QSAR modeling, classification techniques and virtual screening. J Comput Aided Mol Des 21, 251–267 (2007). https://doi.org/10.1007/s10822-007-9112-4

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  • DOI: https://doi.org/10.1007/s10822-007-9112-4

Keywords

  • MCH1R
  • QSAR
  • Classification
  • SVM
  • Virtual screening