QSPR Modeling of the Refractive Index for Diverse Polymers Using 2D Descriptors.

ABSTRACT: In the present work, predictive quantitative structure-property relationship models have been developed to predict refractive indices (RIs) of a set of 221 diverse organic polymers using theoretical two-dimensional descriptors generated on the basis of the structures of polymers' monomer units. Four models have been developed by applying partial least squares (PLS) regression with a different combination of six descriptors obtained via double cross-validation approaches. The predictive ability and robustness of the proposed models were checked using multiple validation strategies. Subsequently, the validated models were used for the generation of "intelligent" consensus models (http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/) to improve the quality of predictions for the external data set. The

SUBMITTER: Khan PM 

PROVIDER: S-EPMC6645227 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature