Fig. 2

Machine learning-assisted directed evolution: The first step in ML-assisted DE is the same as for traditional DE (see Fig. 1). A library of variants is created via mutagenesis. Existing data, \(\mathcal {S}=\{s_k,y\}_{i=1:n}\) are used to train a classifier or regression model, \(f(s_k)\rightarrow y\), which is then used to rank variants via an in silico screen. The top variants are then synthesized/cloned and screened using in vitro or in vivo assays. The data from the ith round is added to \(\mathcal {S}\) and used in subsequent DE rounds