Mapping enzyme catalysis with metabolomic biosensing
Xu, L.; Chang, K.-C.; Payne, E. M.; Modavi, C.; Liu, L.; Palmer, C.; Tao, N.; Alper, H. S.; Kennedy, R. T.; Cornett, D. S.; Abate, A. R.
Show abstract
Enzymes are represented across a vast space of protein sequences and structural forms and have activities that far exceed the best chemical catalysts; however, engineering them to have novel or enhanced activity is limited by technologies for sensing product formation. Here, we describe a general and scalable approach for characterizing enzyme activity that uses the metabolism of the host cell as a biosensor by which to infer product formation. Since different products consume different molecules in their synthesis, they perturb host metabolism in unique ways that can be measured by mass spectrometry. This provides a general way by which to sense product formation, to discover unexpected products and map the effects of mutagenesis.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- pChem: a modification-centric assessment tool for the performance of chemoproteomic probes 93%
- Multiplexed, bioorthogonal labeling of multicomponent, biomolecular complexes using genomically encoded, non-canonical amino acids 93%
- In vitro prototyping and rapid optimization of biosynthetic enzymes for cellular design 92%
Similar papers in this journal
Similar papers in this journal
- Selection of a Promiscuous Minimalist cAMP Phosphodiesterase from a Library of De Novo Designed Proteins 92%
- Activity-based directed evolution of a membrane editor in mammalian cells 91%
- Global analysis of biosynthetic gene clusters reveals conserved and unique natural products in entomopathogenic nematode-symbiotic bacteria 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.