Exploring Molecular Context: Regioselectivity Prediction

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Year 1: General skills training and lab rotationsYears 2-4: The project aims to develop and implement a general workflow, based on the concept of a molecular context, for reaction prediction. As an initial case study, we will select aromatic chlorination reactions, where the structure of the starting material plays the major role on defining regioselectivity. Current models for aromatic substitution are developed from bromination and their range of applicability is not widely explored, although it is of paramount importance. This case study will start with data collection and data cleaning; thus, we will choose a reaction well understood and with various experimental results available. The next step will be the analysis of current models and group situations where different prediction models fail to give an accurate result. We expect the analysis of the limitations of models to guide the study of hidden missing features for the molecular context. A second case study will be evaluated on the reactivity of indazoles, where reactivity and reaction conditions play important roles. This additional study will complement a generalisation of reaction prediction because it must comprehend information beyond reactant structure. Finally, an in-depth study of molecular parametrisation - using computational chemistry and statistics - will be conducted to have a general approach towards reaction prediction. Therefore, we plan to develop a general workflow for reaction prediction reactions that can highlight the most important molecular and experimental features for the transformation and improve the development of machine learning models in chemistry using the concept of a molecular context of the system.