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Application of regression learning for gas chromatographic analysis and prediction of toxicity of organic molecules

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Russian Chemical Bulletin Aims and scope

Abstract

An important task of physical chemistry is to predict the properties of chemical compounds from their structure. Prediction of the chromatographic retention allows one to reject false candidates in gas chromatography/mass spectrometry analysis and to elucidate structures of unknown compounds. Immediately after establishing the structure of an unknown analyte, the next task is to predict its properties, in particular, toxicity. In this work, the problem of prediction of gas chromatographic retention is considered in detail. A new method for predicting the retention indices on different stationary phases using regression learning is demonstrated in relation to flavors and fragrances. The achieved accuracy is higher than the accuracy of previously published methods. The median absolute error does not exceed 14 units. In addition, prediction of acute toxicity from the molecular structure is considered. The efficiency of various regression learning methods for predicting retention indices and acute toxicity (median lethal dose) of chemical compounds is compared.

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Authors and Affiliations

  1. A. N. Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences, Build. 4, 31 Leninsky prosp., 119071, Moscow, Russian Federation

    D. D. Matyushin & A. K. Buryak

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  1. D. D. Matyushin
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  2. A. K. Buryak
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Correspondence to D. D. Matyushin.

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Aleksei Konstantinovich Buryak, born in 1960, Director of the A. N. Frumkin Institute of Physical Chemistry and Electrochemistry of RAS, Corresponding Member of the Russian Academy of Sciences, Doctor of Chemical Sciences, Professor; he was awarded the medal “For the creative contribution to the design of ground space infrastructure facilities” and the rank Honorary Worker of Science and High Technology of the Russian Federation. A. K. Buryak specializes in the physical chemistry and technology of surface phenomena and inorganic materials; he is the author of 342 scientific publications and 30 patents. The key scientific results of A. K. Buryak include the development of a set of physicochemical methods and conduction of a series of studies of the surfaces of inorganic materials for predicting their reactivity. This made it possible to develop, patent, and practically implement processes for purification, modification, and corrosion protection of the construction materials used in ecology, petrochemistry, and rocket engineering. A. K. Buryak supervised eleven PhD Theses. He is Deputy Editor-in-Chief of the journals Fizicheskaya Khimiya (Russian Journal of Physical Chemistry) and Sorbtsionnye i Khromatograficheskie Protsessy (Sorption and Chromatographic Processes), Chairman of the Dissertation Council in Physical Chemistry, Deputy Chairman of the Academic Council of A. N. Frumkin Institute of Physical Chemistry and Electrochemistry of RAS, Co-chairman of the series of conferences “Kinetics and Dynamics of Exchange Processes” (2012–2019).

Published in Russian in Izvestiya Akademii Nauk. Seriya Khimicheskaya, Vol. 72, No. 2, pp. 482–492, February, 2023.

No human or animal subjects were used in this research.

The authors declare no competing interests.

This study was financially supported by the Ministry of Higher Education and Science of the Russian Federation.

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Matyushin, D.D., Buryak, A.K. Application of regression learning for gas chromatographic analysis and prediction of toxicity of organic molecules. Russ Chem Bull 72, 482–492 (2023). https://doi.org/10.1007/s11172-023-3811-2

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