The proﬁtability of next-generation bioreﬁneries is acutely contingent on the discovery and utilization of biocatalysts that can valorize lignin. To this end, the metabolic catalogues of diverse microbiota have been mined previously using functional metagenomics in order to identify biocatalysts that can selectively degrade lignin into monoaromatic compounds. Herein, we have further improved the valorization factor of bioreﬁning by deploying functional metagenomics toward the identiﬁcation of a novel transaminase that can selectively functionalize lignin-derived monoaromatics to produce value-added feedstocks for pharmaceutical synthesis. We implemented a high-throughput colorimetric assay using o-xylylenediamine as the amino donor and successfully identiﬁed a transaminase that utilizes the canonical cofactor, pyridoxal 50-phosphate, to aminate as many as 14 monoaromatic aldehydes and ketones. We subsequently identiﬁed the optimal conditions for enzyme activity towards the most favoured amino acceptor, benzaldehyde, including temperature, pH and choice of co-solvent. We also evaluated the speciﬁcity of the enzyme towards a variety of amino donors, as well as the optimal concentration of the most favoured amino donor. Signiﬁcantly, the novel enzyme is markedly smaller than typical transaminases, and it is stably expressed in E. coli without any modiﬁcations to its amino acid sequence. Finally, we developed and implemented a computational methodology to assess the activity of the novel transaminase. The methodology is generalizable for assessing any transaminase and facilitates in silico screening of enzyme–substrate combinations in order to develop eﬃcient biocatalytic routes to value-added amines. The computational pipeline is an ideal complement to metagenomics and opens new possibilities for biocatalyst discovery.