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Fragmental descriptors in (Q)SAR: prediction of the assignment of organic compounds to pharmacological groups using the support vector machine approach

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Abstract

The structure—activity classification models for prediction of the assignment of organic compounds to 40 pharmacological groups were constructed in the framework of the fragmental approach using the support vector machine technique, the Platt—Wu probabilistic model, and resampling procedure. The models constructed allow one to predict possible types of the side pharmacological effects of drugs.

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Authors and Affiliations

  1. Department of Chemistry, M. V. Lomonosov Moscow State University, 1/3 Leninskie Gory, 119991, Moscow, Russian Federation

    E. P. Kondratovich, N. I. Zhokhova, I. I. Baskin, V. A. Palyulin & N. S. Zefirov

Authors
  1. E. P. Kondratovich
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  2. N. I. Zhokhova
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  3. I. I. Baskin
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  4. V. A. Palyulin
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  5. N. S. Zefirov
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Corresponding author

Correspondence to N. I. Zhokhova.

Additional information

Published in Russian in Izvestiya Akademii Nauk. Seriya Khimicheskaya, No. 4, pp. 641–647, April, 2009.

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Kondratovich, E.P., Zhokhova, N.I., Baskin, I.I. et al. Fragmental descriptors in (Q)SAR: prediction of the assignment of organic compounds to pharmacological groups using the support vector machine approach. Russ Chem Bull 58, 657–662 (2009). https://doi.org/10.1007/s11172-009-0076-5

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  • DOI: https://doi.org/10.1007/s11172-009-0076-5

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