Influence of Template Size, Canonicalization, and Exclusivity for Retrosynthesis and Reaction Prediction Applications.

ABSTRACT: Heuristic and machine learning models for rank-ordering reaction templates comprise an important basis for computer-aided organic synthesis regarding both product prediction and retrosynthetic pathway planning. Their viability relies heavily on the quality and characteristics of the underlying template database. With the advent of automated reaction and template extraction software and consequently the creation of template databases too large for manual curation, a data-driven approach to assess and improve the quality of template sets is needed. We therefore systematically studied the influence of template generality, canonicalization, and exclusivity on the performance of different template ranking models. We find that duplicate and nonexclusive templates, i.e., templates which describe

SUBMITTER: Heid E 

PROVIDER: S-EPMC8757433 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature