Prediction of Optimal Conditions of Hydrogenation Reaction Using the Likelihood Ranking Approach.

ABSTRACT: The selection of experimental conditions leading to a reasonable yield is an important and essential element for the automated development of a synthesis plan and the subsequent synthesis of the target compound. The classical QSPR approach, requiring one-to-one correspondence between chemical structure and a target property, can be used for optimal reaction conditions prediction only on a limited scale when only one condition component (e.g., catalyst or solvent) is considered. However, a particular reaction can proceed under several different conditions. In this paper, we describe the Likelihood Ranking Model representing an artificial neural network that outputs a list of different conditions ranked according to their suitability to a given chemical transformation. Benchmarking calculati

SUBMITTER: Afonina VA 

PROVIDER: S-EPMC8745269 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature