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Application of an Iterative Fragment Selection (IFS) Method to Estimate Entropies of Fusion and Melting Points of Organic Chemicals
Author(s) -
Brown Trevor N.,
Armitage James M.,
Arnot Jon A.
Publication year - 2019
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201800160
Subject(s) - selection (genetic algorithm) , mean squared error , computer science , biological system , mathematics , artificial intelligence , biology , statistics
Abstract The main objective of this study is to develop and evaluate novel Quantitative Structure‐Property Relationships (QSPRs) for predicting entropy of fusion (Δ S M ) and melting point ( T M ) of organic chemicals from chemical structure. The QSPRs are developed using the Iterative Fragment Selection (IFS) method that requires only 2D structural information from the user (SMILES codes) for property prediction. The QSPRs also provide information on the applicability domain for each calculation and uncertainty estimates for the predictions. The root mean square error (RMSE) for the external validation sets are 11.8 J mol −1 K −1 and 46.9 K for the Δ S M and T M QSPRs, respectively. The performance of the new QSPRs is comparable to other predictive methods but has advantages with respect to availability and ease of use as well as the guidance on applicability domain for each prediction. Limitations of the new QSPRs are discussed. The QSPRs are coded as a user‐friendly, freely available tool.