Computer Assisted Simulation of 13C Nuclear Magnetic Spectra of Monosaccharides

Mathematical models are developed that relate the structures of monosaccharides to their 13 C nuclear magnetic resonance spectra. The data set of monosaccharides consists of 55 monosaccharides in the six-membered ring configuration and 56 monosaccharides in the five-membered ring configuration. The structural environment of each carbon atom in the data set is encoded using numerical atom-based descriptors which are then used to develop linear regression models relating the 13 C chemical shift to the structural features. The atom-based descriptors used in this study encode topological, geometric, and electronic information about the carbon atoms in monosaccharides. Multiple linear regression analysis is used to develop an 11-descriptor model to predict the chemical shifts of pyranoses and pyranosides and an eight-descriptor model to predict the chemical shifts of furanoses and furanosides. The models are then submitted to computational neural networks, giving improved results with final training set rms errors of 1.03 ppm for pyranoses and pyranosides and 1.58 ppm for furanoses and furanosides.