With the continuous growth of the real and virtual chemical space, efficient computer-assisted methods are required to discover new substances with desired properties and/or predict properties of interest for untested molecules. These methods rely on the principle that the physicochemical and biological properties of compounds are the effects of their structural characteristics. Therefore, the starting point of any chemo- and bioinformatics application is the conversion of a symbolic representation of the molecular structure into numerical information through the calculation of molecular descriptors. Molecular descriptors encode a wide variety of specific molecular features with a different effect on experimental properties and impact on the perceived chemical similarity between molecules. The choice of molecular descriptors is crucial in determining the chemical space representation and computational modeling outcomes. After introducing the fundamental concepts of molecular descriptors in the current epistemological framework, this chapter reviews some of the well-known classical molecular descriptors and fingerprints.

Consonni, V., Ballabio, D., Todeschini, R. (2023). Chemical space and Molecular Descriptors for QSAR studies. In R. Kunal (a cura di), Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development (pp. 303-327). Elsevier [10.1016/B978-0-443-18638-7.00022-0].

Chemical space and Molecular Descriptors for QSAR studies

Viviana Consonni
;
Davide Ballabio;Roberto Todeschini
2023

Abstract

With the continuous growth of the real and virtual chemical space, efficient computer-assisted methods are required to discover new substances with desired properties and/or predict properties of interest for untested molecules. These methods rely on the principle that the physicochemical and biological properties of compounds are the effects of their structural characteristics. Therefore, the starting point of any chemo- and bioinformatics application is the conversion of a symbolic representation of the molecular structure into numerical information through the calculation of molecular descriptors. Molecular descriptors encode a wide variety of specific molecular features with a different effect on experimental properties and impact on the perceived chemical similarity between molecules. The choice of molecular descriptors is crucial in determining the chemical space representation and computational modeling outcomes. After introducing the fundamental concepts of molecular descriptors in the current epistemological framework, this chapter reviews some of the well-known classical molecular descriptors and fingerprints.
Capitolo o saggio
Chemical space; Cheminformatics; In silico modeling; Mathematical chemistry; Molecular descriptors; Molecular similarity; QSAR;
English
Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development
Kunal, R
5-giu-2023
2023
9780443186387
Elsevier
303
327
Consonni, V., Ballabio, D., Todeschini, R. (2023). Chemical space and Molecular Descriptors for QSAR studies. In R. Kunal (a cura di), Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development (pp. 303-327). Elsevier [10.1016/B978-0-443-18638-7.00022-0].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/418058
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