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Comprehensive Analysis of Applicability Domains of QSPR Models for Chemical Reactions

Authors
  • Rakhimbekova, Assima1
  • Madzhidov, Timur I.1
  • Nugmanov, Ramil I.1
  • Gimadiev, Timur R.
  • Baskin, Igor I.1, 2, 3
  • Varnek, Alexandre3
  • 1 (I.I.B.)
  • 2 Faculty of Physics, Moscow State University, 119234 Moscow, Russia
  • 3 Laboratory of Chemoinformatics, UMR 7140 CNRS, University of Strasbourg, 67000 Strasbourg, France
Type
Published Article
Journal
International Journal of Molecular Sciences
Publisher
MDPI AG
Publication Date
Aug 03, 2020
Volume
21
Issue
15
Identifiers
DOI: 10.3390/ijms21155542
PMID: 32756326
PMCID: PMC7432167
Source
PubMed Central
Keywords
License
Green

Abstract

Nowadays, the problem of the model’s applicability domain (AD) definition is an active research topic in chemoinformatics. Although many various AD definitions for the models predicting properties of molecules (Quantitative Structure-Activity/Property Relationship (QSAR/QSPR) models) were described in the literature, no one for chemical reactions (Quantitative Reaction-Property Relationships (QRPR)) has been reported to date. The point is that a chemical reaction is a much more complex object than an individual molecule, and its yield, thermodynamic and kinetic characteristics depend not only on the structures of reactants and products but also on experimental conditions. The QRPR models’ performance largely depends on the way that chemical transformation is encoded. In this study, various AD definition methods extensively used in QSAR/QSPR studies of individual molecules, as well as several novel approaches suggested in this work for reactions, were benchmarked on several reaction datasets. The ability to exclude wrong reaction types, increase coverage, improve the model performance and detect Y-outliers were tested. As a result, several “best” AD definitions for the QRPR models predicting reaction characteristics have been revealed and tested on a previously published external dataset with a clear AD definition problem.

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