Loop-Centric Engineering of Terminal Deoxynucleotidyl Transferase for Enhanced Catalysis of 3'-Modified Nucleotides.

Abstract

Efficient enzymatic DNA synthesis requires terminal deoxynucleotidyl transferases (TdTs) that can accept reversibly blocked nucleotides, but improving wild-type enzymes has traditionally depended on labor-intensive screening. Here, we combine deep learning-based structure prediction with molecular dynamics simulations to guide loop-centric engineering of a TdT from Crocodylus porosus. The resulting variant M3 (V253E/L256M/N338R) showed a 26-fold increase in specific activity toward 3'-ONH2-dCTP while maintaining expression and thermostability. Simulations indicated that the mutations reorganized Loop1 dynamics and reproducibly biased the incoming nucleotide toward a more favorable in-line attack orientation. The key N338R change also improved a second TdT scaffold, supporting N338 as a potentially transferable engineering hotspot. These results provide a practical computational strategy for improving terminal deoxynucleotidyl transferases for incorporation of 3'-modified nucleotides, reducing reliance on large-scale screening.