Soluble Methane Monooxygenase Component Interactions Monitored by ¹⁹F NMR

Abstract

Soluble methane monooxygenase (sMMO) is a multicomponent metalloenzyme capable of catalyzing the fissure of the C−H bond of methane and the insertion of one atom of oxygen from O 2 to yield methanol. Efficient multiple-turnover catalysis occurs only in the presence of all three sMMO protein components: hydroxylase (MMOH), reductase (MMOR), and regulatory protein (MMOB). The complex series of sMMO protein component interactions that regulate the formation and decay of sMMO reaction cycle intermediates is not fully understood. Here, the two tryptophan residues in MMOB and the single tryptophan residue in MMOR are converted to 5-fluorotryptophan (5FW) by expression in defined media containing 5-fluoroindole. In addition, the mechanistically significant N-terminal region of MMOB is 19 F-labeled by reaction of the K15C variant with 3-bromo-1,1,1trifluoroacetone (BTFA). The 5FW and BTFA modifications cause minimal structural perturbation, allowing detailed studies of the interactions with sMMOH using 19 F NMR. Resonances from the 275 kDa complexes of sMMOH with 5FW-MMOB and BTFA-K15C-5FW-MMOB are readily detected at 5 μM labeled protein concentration. This approach shows directly that MMOR and MMOB competitively bind to sMMOH with similar K D values, independent of the oxidation state of the sMMOH diiron cluster. These findings suggest a new model for regulation in which the dynamic equilibration of MMOR and MMOB with sMMOH allows a transient formation of key reactive complexes that irreversibly pull the reaction cycle forward. The slow kinetics of exchange of the sMMOH:MMOB complex is proposed to prevent MMOR-mediated reductive quenching of the high-valent reaction cycle intermediate Q before it can react with methane.

X-ray Crystal Structures of Methane Monooxygenase Hydroxylase Complexes with Variants of Its Regulatory Component: Correlations with Altered Reaction Cycle Dynamics

“…Indeed, recent studies suggest that O 2 binding, activation, and the reaction of the activated species with hydrocarbons occurs in the sMMOH:MMOB complex after dissociation of MMOR. 27 The kinetic, regiospecific, and structural changes in sMMOH and sMMOH catalysis caused by MMOB binding have been investigated by several approaches, but none has been more informative than the application of targeted MMOB variants. 21,[27][28][29][32][33][34]37,44,45 The crystal structures of the MMOB variants in complex with sMMOH shown in this report reveal discrete and distinct perturbations within sMMOH.…”

“…27 The kinetic, regiospecific, and structural changes in sMMOH and sMMOH catalysis caused by MMOB binding have been investigated by several approaches, but none has been more informative than the application of targeted MMOB variants. 21,[27][28][29][32][33][34]37,44,45 The crystal structures of the MMOB variants in complex with sMMOH shown in this report reveal discrete and distinct perturbations within sMMOH. Some of these changes can now be correlated with the effects on catalysis and regulation seen during sMMO turnover, and these aspects are discussed here.…”

“…25,26 The final and perhaps most elegant aspect of MMOB regulation is described by a recently proposed dynamic equilibrium model that explains how sMMO avoids reductive quenching of Q by MMOR. 27 MMOB and MMOR were shown to bind with similar affinities to sMMOH and to compete for the same binding site near the buried diiron cluster. The distinct roles of MMOR and MMOB, diiron cluster reduction versus O 2 binding, respectively, are manifested only when the correct pair of sMMO components forms a complex.…”

Rational Design of Pepsin for Enhanced Thermostability via Exploiting the Guide of Structural Weakness on Stability

“…ΔΔG < 0 indicates that the mutant is more stable than the wild-type. The thermostability of multiple proteins has been improved using the PoPMuSiC algorithm [9,28,29]. HoTMuSiC is a computational tool that uses an artificial neural network to predict the change in melting temperature ΔT m , upon the introduction of single-point mutations, based on the imperfect correlation of thermodynamics and thermal stabilities [30].…”

“…However, owing to their unpredictability and long-range effects, mutants with improved thermostability are not readily obtained [5,6]. With the development of structural and computational biology, protein structures can be obtained efficiently through experimental determination and computational prediction [7][8][9][10]. In recent years, based on protein structure and energy function, the prediction of mutations stabilizing the folded protein structure has improved considerably.…”