Quantitative Structure-Activity Relationship Modeling and Bayesian Networks: Optimality of Naive Bayes Model

Oleg Kupervasser

A chapter in Bayesian Networks - Advances and Novel Applications from IntechOpen

Abstract: Previously, computational drag design was usually based on simplified laws of molecular physics, used for calculation of ligand's interaction with an active site of a protein-enzyme. However, currently, this interaction is widely estimated using some statistical properties of known ligand-protein complex properties. Such statistical properties are described by quantitative structure-activity relationships (QSAR). Bayesian networks can help us to evaluate stability of a ligand-protein complex using found statistics. Moreover, we are possible to prove optimality of Naive Bayes model that makes these evaluations simple and easy for practical realization. We prove here optimality of Naive Bayes model using as an illustration ligand-protein interaction.

Keywords: quantitative structure-activity relationship; Naive Bayes model; optimality; Bayes classifier; Bayesian networks; protein-ligand complex; computational drag design; molecular recognition and binding; ligand-active site of protein; likelihood; probability (search for similar items in EconPapers)
JEL-codes: C60 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:164906

DOI: 10.5772/intechopen.85976

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