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QSAR: What Else?

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Computational Toxicology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1800))

Abstract

QSAR (quantitative structure–activity relationship) is a method for predicting the physical and biological properties of small molecules; it is today in large use in companies and public services. However, as any scientific method, it is nowadays challenged by more and more requests, especially considering its possible role in assessing the safety of new chemicals. Posing the question whether QSAR is a way not only to exploit available knowledge but also to build new knowledge, we shortly review QSAR history, thus searching for a QSAR epistemology. We consider the three pillars on which QSAR stands: biological data, chemical knowledge, and modeling algorithms. Most of the time we assume that biological data is a true picture of the world (as they result from good experimental practice), that chemical knowledge is scientifically true; so if a QSAR is not working, blame modeling. This opens the way to look at the role of modeling in developing scientific theories, and in producing knowledge. QSAR is a mature technology; however, debate is still active in many topics, in particular about the acceptability of the models and how they are explained. After an excursus in inductive reasoning, we relate the QSAR methodology to open debates in the philosophy of science.

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Notes

  1. 1.

    Titus Lucretius Carus, Of The Nature of Things ,

    http://www.gutenberg.org/ebooks/785?msg=welcome_stranger

  2. 2.

    http://www.antares-life.eu/index.php?sec=modellist

  3. 3.

    https://plato.stanford.edu/entries/induction-problem/

  4. 4.

    https://plato.stanford.edu/entries/justep-intext/

  5. 5.

    <https://plato.stanford.edu/archives/fall2014/entries/justep-intext/>

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Authors and Affiliations

  1. DEIB, Politecnico di Milano, Milan, Italy

    Giuseppina Gini

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  1. Giuseppina Gini
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Correspondence to Giuseppina Gini .

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  1. Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, Italy

    Orazio Nicolotti

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Gini, G. (2018). QSAR: What Else?. In: Nicolotti, O. (eds) Computational Toxicology. Methods in Molecular Biology, vol 1800. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7899-1_3

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  • DOI: https://doi.org/10.1007/978-1-4939-7899-1_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7898-4

  • Online ISBN: 978-1-4939-7899-1

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