Non-active Site Residue in Loop L4 Alters Substrate Capture and Product Release in d-Arginine Dehydrogenase.
Daniel OuedraogoMichael SouffrantXin-Qiu YaoDonald HamelbergGiovanni GaddaPublished in: Biochemistry (2023)
Numerous studies demonstrate that enzymes undergo multiple conformational changes during catalysis. The malleability of enzymes forms the basis for allosteric regulation: residues located far from the active site can exert long-range dynamical effects on the active site residues to modulate catalysis. The structure of Pseudomonas aeruginosa d-arginine dehydrogenase ( Pa DADH) shows four loops (L1, L2, L3, and L4) that span the substrate and the FAD-binding domains. Loop L4 comprises residues 329-336, spanning over the flavin cofactor. The I335 residue on loop L4 is ∼10 Å away from the active site and ∼3.8 Å from N(1)-C(2)═O atoms of the flavin. In this study, we used molecular dynamics and biochemical techniques to investigate the effect of the mutation of I335 to histidine on the catalytic function of Pa DADH. Molecular dynamics showed that the conformational dynamics of Pa DADH are shifted to a more closed conformation in the I335H variant. In agreement with an enzyme that samples more in a closed conformation, the kinetic data of the I335H variant showed a 40-fold decrease in the rate constant of substrate association ( k 1 ), a 340-fold reduction in the rate constant of substrate dissociation from the enzyme-substrate complex ( k 2 ), and a 24-fold decrease in the rate constant of product release ( k 5 ), compared to that of the wild-type. Surprisingly, the kinetic data are consistent with the mutation having a negligible effect on the reactivity of the flavin. Altogether, the data indicate that the residue at position 335 has a long-range dynamical effect on the catalytic function in Pa DADH.
Keyphrases
- molecular dynamics
- density functional theory
- amino acid
- pseudomonas aeruginosa
- electronic health record
- wild type
- big data
- nitric oxide
- transcription factor
- molecular dynamics simulations
- crystal structure
- structural basis
- cystic fibrosis
- small molecule
- machine learning
- escherichia coli
- single molecule
- dna binding
- biofilm formation