QSPR modelling of dielectric constants of π-conjugated organic compounds by means of the CORAL software

Abstract

Simplified molecular input line entry system (SMILES) notations of 116 π-conjugated organic compounds have been used in three random splits to develop single optimal descriptor based quantitative structure–property relationships (QSPR) models for the prediction of dielectric constants by CORAL (CORrelation And Logic). Four kinds of optimal descriptors were obtained based on SMILES, hydrogen suppressed graph (HSG), graph of atomic orbitals (GAO) and hybrid descriptors. The Monte Carlo optimization was carried out for each random split by three different methods: (i) classic scheme; (ii) balance of correlations; and (iii) balance of correlations with ideal slopes. The QSPR models gave reliable and accurate values of dielectric constant for all the π-conjugated organic compounds. SMILES and the hybrid-based QSPR model provided the best accuracy for the prediction of dielectric constants. Statistical characteristics of the QSPR model-1 based on classic scheme method are n = 110, r² = 0.860, Q² = 0.860, s = 1.84, MAE = 1.30 and F = 696 (training set), n = 6, r² = 0.947, Q² = 0.876, s = 0.955, MAE = 0.647 and F = 71 (test set). These QSPR models are further validated by an external validation set of 25 molecules and the robustness is checked by parameters like k, kk, r_m², r^*_m², average r_m², ∆r_m²and randomization technique ().

Keywords:

• SMILES
• QSPR models
• dielectric constants
• CORAL
• optimal descriptors

Acknowledgements

The author expresses his gratitude to the Honourable Vice-Chancellor, Dean, Director and Associate Dean of Institute of Technical Education and Research (ITER), Siksha ‘O’ Anusandhan University, Bhubaneswar, India, for extending the facility at the Centre of Excellence in Theoretical and Mathematical Sciences. Also, I am extending thanks to the research scholars of the Department of Chemistry for preparing the dataset for the Monte Carlo optimization.