LAUSR

We report new 3D fragment descriptors to model parameters and properties of stereoisomeric molecules and conformers. New 3D fragment descriptors have been applied to discriminate between stereoisomers in predictive QSPR modeling of the standard free energy (∆G°) for the 1:1 inclusion complexation of 76 chiral guests with β-cyclodextrin (β-CD) and 40 chiral guests with 6-amino-6-deoxy-β-cyclodextrin (am-β-CD) in water at 298 K. The in-house software, mfSpace (Molecular Fragments Space), was used for QSPR modeling, generation and coding of the 3D fragment descriptors. The program implements the Singular Value Decomposition for Multiple Linear Regression analysis as machine learning method. We used ensemble modeling techniques which include the generation of many individual models, the selection of the most relevant ones and followed by their joint application to test compounds, i.e., applying a consensus model for average predictions. The models based on 2D and 3D fragment descriptors provide the best predictions in external fivefold cross-validation: root mean squared error RMSE = 1.1 kJ/mol and determination coefficient $$R_{{det}}^{2}$$Rdet2 = 0.918 (β-CD), RMSE = 0.89 kJ/mol and $$R_{{det}}^{2}$$Rdet2 = 0.910 (am-β-CD).