A Priori Estimation of Organic Reaction Yields.

A thermodynamically guided calculation of free energies of substrate and product molecules allows for the estimation of the yields of organic reactions. The non-ideality of the system and the solvent effects are taken into account through the activity coefficients calculated at the molecular level by perturbed-chain statistical associating fluid theory (PC-SAFT). The model is iteratively trained using a diverse set of reactions with yields that have been reported previously. This trained model can then estimate a priori the yields of reactions not included in the training set with an accuracy of ca. ±15 %. This ability has the potential to translate into significant economic savings through the selection and then execution of only those reactions that can proceed in good yields.

Organic chemistry as a language and the implications of chemical linguistics for structural and retrosynthetic analyses.

Methods of computational linguistics are used to demonstrate that a natural language such as English and organic chemistry have the same structure in terms of the frequency of, respectively, text fragments and molecular fragments. This quantitative correspondence suggests that it is possible to extend the methods of computational corpus linguistics to the analysis of organic molecules. It is shown that within organic molecules bonds that have highest information content are the ones that 1) define repeat/symmetry subunits and 2) in asymmetric molecules, define the loci of potential retrosynthetic disconnections. Linguistics-based analysis appears well-suited to the analysis of complex structural and reactivity patterns within organic molecules.