Measuring the efficiency of synthetic routes and transformations using vectors derived from similarity and complexity.

With the aim of providing new tools for the design and assessment of synthetic routes, we describe an approach that mimics human interpretation whilst being highly amenable to machine implementation. The representation of molecular structures as 2D-coordinates derived from molecular similarity and complexity allows individual transformations to be viewed as vectors (reactant to product) where the magnitude and direction of travel can be used to assess and quantify efficiency. Using a dataset comprising 640k literature syntheses and 2.4m reactions taken from six journals between 2000 and 2020, we show that vectors derived in this way follow logical patterns when grouped by reaction type. Similarly, complete synthetic routes can be visualised as sequences of head-to-tail vectors traversing the range between starting material and target, allowing the efficiency with which this range is covered to be quantified. Three applications of the methodology are demonstrated: a comparison of CASP performance between two versions of AiZynthFinder for generating synthetic routes to 100k ChEMBL targets, analysis of predicted routes to a specific target molecule and, finally, a perspective on how the efficiency of published synthetic routes has changed over the last two decades.