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9XLU

Crystal structure of Staphylococcus aureus cystathionine gamma-lyase V129G

Summary for 9XLU
Entry DOI10.2210/pdb9xlu/pdb
DescriptorCystathionine gamma-synthase homolog (2 entities in total)
Functional Keywordscystathionine gamma-lyase, plp-dependent enzyme, transsulfuration, staphylococcus aureus, lyase
Biological sourceStaphylococcus aureus subsp. aureus Mu50
Total number of polymer chains1
Total formula weight43294.82
Authors
Lee, U.,Ha, N.C. (deposition date: 2025-11-08, release date: 2026-04-15, Last modification date: 2026-06-24)
Primary citationLee, U.,Park, M.,Song, B.,Ha, N.C.
Family-Specialized Transformer for L-cystathionine gamma-lyase Engineering and Its Structural Interpretation.
Comput Struct Biotechnol J, 35:0073-0073, 2026
Cited by
PubMed Abstract: The diversity of protein structures and reaction mechanisms complicates general-purpose artificial intelligence models for enzyme engineering, motivating family-specialized models. In this study, we developed EnzFormer, a specialized artificial intelligence pipeline for engineering L-cystathionine gamma-lyase (SaMccB). To overcome the scarcity of experimental labels, we used GPT-4o to generate putative activity labels for cystathionine gamma-lyase homologs, leveraging species-level ecological and evolutionary metadata as a proxy for functional selection. Using these labels, we trained a Transformer classifier on embeddings from the ESM Cambrian protein language model. From an exhaustive single-mutant library, in silico prioritization nominated 4 variants for testing and identified SaMccB V129G with a ~2-fold increase in catalytic turnover relative to the wild type. Val129 is distal to the active site; crystallographic and biochemical analyses suggest that V129G weakens local packing, thereby increasing the conformational flexibility of the active site loop, consistent with faster conformational steps in the catalytic cycle. Together, these results suggest that combining large language model-derived evolutionary priors with a family-specialized predictive model can identify distal mutations that modulate enzyme dynamics.
PubMed: 42256461
DOI: 10.34133/csbj.0073
PDB entries with the same primary citation
Experimental method
X-RAY DIFFRACTION (2.33 Å)
Structure validation

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PDB entries from 2026-08-12

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