Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases

Rahil Taujale, Aarya Venkat, Liang-Chin Huang, Zhongliang Zhou, Wayland Yeung, Khaled M Rasheed, Sheng Li, Arthur S Edison, Kelley W Moremen, Natarajan Kannan
2020 eLife  
Glycosyltransferases (GTs) are prevalent across the tree of life and regulate nearly all aspects of cellular functions. The evolutionary basis for their complex and diverse modes of catalytic functions remain enigmatic. Here, based on deep mining of over half million GT-A fold sequences, we define a minimal core component shared among functionally diverse enzymes. We find that variations in the common core and emergence of hypervariable loops extending from the core contributed to GT-A
more » ... . We provide a phylogenetic framework relating diverse GT-A fold families for the first time and show that inverting and retaining mechanisms emerged multiple times independently during evolution. Using evolutionary information encoded in primary sequences, we trained a machine learning classifier to predict donor specificity with nearly 90% accuracy and deployed it for the annotation of understudied GTs. Our studies provide an evolutionary framework for investigating complex relationships connecting GT-A fold sequence, structure, function and regulation.
doi:10.7554/elife.54532 pmid:32234211 pmcid:PMC7185993 fatcat:fhrnw7put5bdzbm7a666l6fxoy