Editorial: Chemical Reactions Mining

Abstract

Tremendous progress of deep learning methods makes possible to generate potent chemical entities which stability and synthetic feasibility need to be estimated. In turn, this requires to answer such questions as (a) how given compounds can be synthesized, (b) under which conditions a given reaction should be carried out, (c) what is estimated rate/yield/selectivity of a given reaction under given conditions, (d) how one can design molecules with controlled synthetic accessibility, (e) what is the reactivity/stability of particular molecule in particular environment or organism?Here, we introduce special issue of Molecular Informatics devoted to chemical reactions mining. It covers a wide variety of topics, from condition prediction to de novo design and tends to answer the above question using chemoinformatics approaches.P. Ertl et al. [1] reviewed some original approaches for the assessment of molecular reactivity and possible molecular transformations in ex vivo and in vivo settings. The article by Gimadiev et al. [2] described reaction data curation and cleaning protocol using open-sourced tools. Lin et al. [3] benchmarked popular atom-to-atom mapping algorithms and proposed an elegant strategy of erroneous mapping correction. Special attention in the issue was paid to the modeling of reaction properties. Thus, Sato et al. [4] reported a deep learning-based descriptor-free model for yield prediction in important for medicinal chemistry Buchwald-Hartwig reaction. Genheden et al. [5] proposed an interesting approach for predicting Buchwald-Hartwig reaction conditions, such as ligand, base, solvent, and (pre-)catalyst. In order to identify the most promising reactants for the Claisen reaction, Okada et al. [6] applied a genetic algorithmbased approach coupled with quantum chemical reaction barrier estimation. Focusing on de novo design of synthetically available molecules, Ghiandoni et al. [7] proposed reaction-based tool RENATE for reaction-based structure generation that can fragment and assemble molecules following a chemical logic.We hope that this special issue wil be of interest of the readers of Molecular Informatics.