Fayos, Jose; Infantes, Lourdes; Cano, F. H. published the artcile< Neural Network Prediction of Secondary Structure in Crystals: Hydrogen-Bond Systems in Pyrazole Derivatives>, Synthetic Route of 13808-65-6, the main research area is neural network prediction secondary structure crystal hydrogen bond pyrazole.
With the purpose of predicting by neural networks some structural properties of crystals, in particular, the types of secondary structure built by H bonds, 46 mols., containing the pyrazole ring, were codified in vectors of equal dimension. Looking for an unbiased codification, the authors selected the components of these vectors from the 1-dimensional Fourier transform of the corresponding three-dimensional mol. charge distribution. Matrixes of similarity and similarity maps of Kohonen’s trained networks have allowed classification of the mols., as a previous step before prediction of their H-bond system. Thus, the authors have worked under the hypothesis that this mol. codification contains information relevant to the structural level in crystals. The classes obtained show correlation with the previously known secondary structure of the corresponding crystals. Then, the authors have achieved, by training a neural network with some mol. vectors supervised by their coded secondary structure, a significant prediction of the type of secondary structure for the rest of the mols. This mol. codification seems also to account for other noncovalent mol. interactions involved in the packing.
Crystal Growth & Design published new progress about Hydrogen bond. 13808-65-6 belongs to class pyrazoles-derivatives, and the molecular formula is C9H7BrN2, Synthetic Route of 13808-65-6.
Referemce:
Pyrazole – Wikipedia,
Pyrazoles – an overview | ScienceDirect Topics