Probing the mechanisms for the selectivity and promiscuity of methyl parathion hydrolase

Catalytic Redundancies and Conformational Plasticity Drives Selectivity and Promiscuity in Quorum Quenching Lactonases

Several enzymes from the metallo-β-lactamase-like family of lactonases (MLLs) degrade N- acyl-L-homoserine lactones (AHLs). In doing so, they play a role in a microbial communication system, quorum sensing, which contributes to pathogenicity and biofilm formation. There is currently great interest in designing quorum quenching ( QQ ) enzymes that can interfere with this communication and be used in a range of industrial and biomedical applications. However, tailoring these enzymes for specific targets requires a thorough understanding of their mechanisms and the physicochemical properties that determine their substrate specificities. We present here a detailed biochemical, computational, and structural study of the MLL GcL, which is highly proficient, thermostable, and has broad substrate specificity. Strikingly, we show that GcL does not only accept a broad range of substrates but is also capable of utilizing different reaction mechanisms that are differentially used in function of the substrate structure or the remodeling of the active site via mutations. Comparison of GcL to other lactonases such as AiiA and AaL demonstrates similar mechanistic promiscuity, suggesting this is a shared feature across lactonases in this enzyme family. Mechanistic promiscuity has previously been observed in the lactonase/paraoxonase PON1, as well as with protein tyrosine phosphatases that operate via a dual general-acid mechanism. The apparent prevalence of this phenomenon is significant from both a biochemical and an engineering perspective: in addition to optimizing for specific substrates, it is possible to optimize for specific mechanisms, opening new doors not just for the design of novel quorum quenching enzymes, but also of other mechanistically promiscuous enzymes.

Molecular binding of different classes of organophosphates to methyl parathion hydrolase from Ochrobactrum species

Methyl parathion hydrolase (MPH) is an enzyme of the metallo-β-lactamase superfamily, which hydrolyses a wide range of organophosphates (OPs). Recently, MPH has attracted attention as a promising enzymatic bioremediator. The crystal structure of MPH enzyme shows a dimeric form, with each subunit containing a binuclear metal ion center. MPH also demonstrates metal ion-dependent selectivity patterns. The origins of these patterns remain unclear but are linked to open questions about the more general role of metal ions in functional evolution and divergence within enzyme superfamilies. We aimed to investigate and compare the binding of different OP pesticides to MPH with cobalt(II) metal ions. In this study, MPH was modeled from Ochrobactrum sp. with different OP pesticides bound, including methyl paraoxon and dichlorvos and profenofos. The docked structures for each substrate optimized by DFT calculation were selected and subjected to atomistic molecular dynamics simulations for 500 ns. It was found that alpha metal ions did not coordinate with all the pesticides. Rather, the pesticides coordinated with less buried beta metal ions. It was also observed that the coordination of beta metal ions was perturbed to accommodate the pesticides. The binding free energy calculations and structure-based pharmacophore model revealed that all the three substrates could bind well at the active site. However, profenofos exhibit a stronger binding affinity to MPH in comparison to the other two substrates. Therefore, our findings provide molecular insight on the binding of different OP pesticides which could help us design the enzyme for OP pesticides degradation.

Improving Catalytic Activity and Thermal Stability of Methyl-Parathion Hydrolase for Degrading the Pesticide of Methyl-Parathion

Pesticides are indispensable in today’s agriculture. Methyl-parathion hydrolase (MPH, E.C.3.1.8.1) could hydrolyze organophosphorus pesticides, including methyl-parathion. MPH could rehabilitate soil and water resources contaminated by organophosphorus pesticides. However, natural MPHs generally exhibited a low tolerance to high temperatures and low catalytic efficiency. In this study, we improved the catalytic efficiency toward methyl-parathion and the thermal stability of the MPH from Pseudomonas sp. WBC-3 through saturation mutagenesis and fusion with self-assembling amphipathic peptides (SAP). The experimental characterization showed that compared to the wild-type enzyme, the kcat/Km of the mutant T271S yielded by saturation mutagenesis was increased by 224.3% compared to the wild-type MPH. T50 and Tm of SAP3-MPH with an SAP fused at the N-terminus were increased by 6.2°C and 6.0°C, respectively. Compared to the wild-type enzyme, T271S fused with SAP3 at the N-terminus (SAP3-T271S) exhibited a 2.1-fold increase in kcat/Km without significantly affecting the thermal stability. The simultaneous improvement of the catalytic efficiency and thermal stability of MPH would be beneficial for its application in the degradation and detection of organophosphorus pesticides. Furthermore, our study provides a potential combination strategy for the design of the other enzyme preparations of pollutant degradation.

Why Monoamine Oxidase B Preferably Metabolizes N-Methylhistamine over Histamine: Evidence from the Multiscale Simulation of the Rate-Limiting Step

Histamine levels in the human brain are controlled by rather peculiar metabolic pathways. In the first step, histamine is enzymatically methylated at its imidazole N^τ atom, and the produced N-methylhistamine undergoes an oxidative deamination catalyzed by monoamine oxidase B (MAO-B), as is common with other monoaminergic neurotransmitters and neuromodulators of the central nervous system. The fact that histamine requires such a conversion prior to oxidative deamination is intriguing since MAO-B is known to be relatively promiscuous towards monoaminergic substrates; its in-vitro oxidation of N-methylhistamine is about 10 times faster than that for histamine, yet this rather subtle difference appears to be governing the decomposition pathway. This work clarifies the MAO-B selectivity toward histamine and N-methylhistamine by multiscale simulations of the rate-limiting hydride abstraction step for both compounds in the gas phase, in aqueous solution, and in the enzyme, using the established empirical valence bond methodology, assisted by gas-phase density functional theory (DFT) calculations. The computed barriers are in very good agreement with experimental kinetic data, especially for relative trends among systems, thereby reproducing the observed MAO-B selectivity. Simulations clearly demonstrate that solvation effects govern the reactivity, both in aqueous solution as well as in the enzyme although with an opposing effect on the free energy barrier. In the aqueous solution, the transition-state structure involving histamine is better solvated than its methylated analog, leading to a lower barrier for histamine oxidation. In the enzyme, the higher hydrophobicity of N-methylhistamine results in a decreased number of water molecules at the active side, leading to decreased dielectric shielding of the preorganized catalytic electrostatic environment provided by the enzyme. This renders the catalytic environment more efficient for N-methylhistamine, giving rise to a lower barrier relative to histamine. In addition, the transition state involving N-methylhistamine appears to be stabilized by the surrounding nonpolar residues to a larger extent than with unsubstituted histamine, contributing to a lower barrier with the former.

The adaptive landscape of a metallo-enzyme is shaped by environment-dependent epistasis

Enzymes can evolve new catalytic activity when environmental changes present them with novel substrates. Despite this seemingly straightforward relationship, factors other than the direct catalytic target can also impact adaptation. Here, we characterize the catalytic activity of a recently evolved bacterial methyl-parathion hydrolase for all possible combinations of the five functionally relevant mutations under eight different laboratory conditions (in which an alternative divalent metal is supplemented). The resultant adaptive landscapes across this historical evolutionary transition vary in terms of both the number of “fitness peaks” as well as the genotype(s) at which they are found as a result of genotype-by-environment interactions and environment-dependent epistasis. This suggests that adaptive landscapes may be fluid and molecular adaptation is highly contingent not only on obvious factors (such as catalytic targets), but also on less obvious secondary environmental factors that can direct it towards distinct outcomes.

The metaphor of an adaptive landscape is presented quantitatively by looking at molecular adaptations and their catalytic consequences in a recently evolved bacterial enzyme. The study identifies both genotype-by-environment interactions and environment-dependent epistasis as factors that can alter the fitness of functional mutations.

Structure and evolutionary trace-assisted screening of a residue swapping the substrate ambiguity and chiral specificity in an esterase

Our understanding of enzymes with high substrate ambiguity remains limited because their large active sites allow substrate docking freedom to an extent that seems incompatible with stereospecificity. One possibility is that some of these enzymes evolved a set of evolutionarily fitted sequence positions that stringently allow switching substrate ambiguity and chiral specificity. To explore this hypothesis, we targeted for mutation a serine ester hydrolase (EH3) that exhibits an impressive 71-substrate repertoire but is not stereospecific (e.e. 50%). We used structural actions and the computational evolutionary trace method to explore specificity-swapping sequence positions and hypothesized that position I244 was critical. Driven by evolutionary action analysis, this position was substituted to leucine, which together with isoleucine appears to be the amino acid most commonly present in the closest homologous sequences (max. identity, ca. 67.1%), and to phenylalanine, which appears in distant homologues. While the I244L mutation did not have any functional consequences, the I244F mutation allowed the esterase to maintain a remarkable 53-substrate range while gaining stereospecificity properties (e.e. 99.99%). These data support the possibility that some enzymes evolve sequence positions that control the substrate scope and stereospecificity. Such residues, which can be evolutionarily screened, may serve as starting points for further designing substrate-ambiguous, yet chiral-specific, enzymes that are greatly appreciated in biotechnology and synthetic chemistry.

Novel mutation in Cul7 gene in a family diagnosed with 3M syndrome

This study evaluates a family with two siblings having severe growth retardation and facial dysmorphism, born to consanguineous normal healthy parents. Affymetrix CytoScan 750K microarray showed a 34-Mb pericentric homozygous region on chromosome 6 for both siblings. CUL7 was one of the 141 genes present in this region. Sanger sequencing of CUL7 gene detected a 2-bp novel deletion in the 15th exon (c.2943_2944delCT of the cDNA). This deletion leads to a frameshift and a premature termination signal much upstream of the wild-type termination signal, leading to a nonsense mediated decay of the mRNA. CUL7 protein plays an important role in formation of 3M complex, ubiquitination, microtubule dynamics and cell cycle regulation. Mutations in CUL7 gene is known to cause a rare 3M syndrome. Information about the novel mutation has been accepted in the ClinVar database with rs1064792895.

Challenges and advances in the computational modeling of biological phosphate hydrolysis

Phosphate ester hydrolysis is fundamental to many life processes, and has been the topic of substantial experimental and computational research effort. However, even the simplest of phosphate esters can be hydrolyzed through multiple possible pathways that can be difficult to distinguish between, either experimentally, or computationally. Therefore, the mechanisms of both the enzymatic and non-enzymatic reactions have been historically controversial. In the present contribution, we highlight a number of technical issues involved in reliably modeling these computationally challenging reactions, as well as proposing potential solutions. We also showcase examples of our own work in this area, discussing both the non-enzymatic reaction in aqueous solution, as well as insights obtained from the computational modeling of organophosphate hydrolysis and catalytic promiscuity amongst enzymes that catalyze phosphoryl transfer.

Similar Active Sites and Mechanisms Do Not Lead to Cross-Promiscuity in Organophosphate Hydrolysis: Implications for Biotherapeutic Engineering

Organophosphate hydrolases are proficient catalysts of the breakdown of neurotoxic organophosphates and have great potential as both biotherapeutics for treating acute organophosphate toxicity and as bioremediation agents. However, proficient organophosphatases such as serum paraoxonase 1 (PON1) and the organophosphate-hydrolyzing lactonase SsoPox are unable to hydrolyze bulkyorganophosphates with challenging leaving groups such as diisopropyl fluorophosphate (DFP) or venomous agent X, creating a major challenge for enzyme design. Curiously, despite their mutually exclusive substrate specificities, PON1 and diisopropyl fluorophosphatase (DFPase) have essentially identical active sites and tertiary structures. In the present work, we use empirical valence bond simulations to probe the catalytic mechanism of DFPase as well as temperature, pH, and mutational effects, demonstrating that DFPase and PON1 also likely utilize identical catalytic mechanisms to hydrolyze their respective substrates. However, detailed examination of both static structures and dynamical simulations demonstrates subtle but significant differences in the electrostatic properties and solvent penetration of the two active sites and, most critically, the role of residues that make no direct contact with either substrate in acting as "specificity switches" between the two enzymes. Specifically, we demonstrate that key residues that are structurally and functionally critical for the paraoxonase activity of PON1 prevent it from being able to hydrolyze DFP with its fluoride leaving group. These insights expand our understanding of the drivers of the evolution of divergent substrate specificity in enzymes with identical active sites and guide the future design of organophosphate hydrolases that hydrolyze compounds with challenging leaving groups.

Extending the Nonbonded Cationic Dummy Model to Account for Ion-Induced Dipole Interactions

Modeling metalloproteins often requires classical molecular dynamics (MD) simulations in order to capture their relevant motions, which in turn necessitates reliable descriptions of the metal centers involved. One of the most successful approaches to date is provided by the "cationic dummy model", where the positive charge of the metal ion is transferred toward dummy particles that are bonded to the central metal ion in a predefined coordination geometry. While this approach allows for ligand exchange, and captures the correct electrostatics as demonstrated for different divalent metal ions, current dummy models neglect ion-induced dipole interactions. In the present work, we resolve this weakness by taking advantage of the recently introduced 12-6-4 type Lennard-Jones potential to include ion-induced dipole interactions. We revise our previous dummy model for Mg²⁺ and demonstrate that the resulting model can simultaneously reproduce the experimental solvation free energy and metal-ligand distances without the need for artificial restraints or bonds. As ion-induced dipole interactions become particularly important for highly charged metal ions, we develop dummy models for the biologically relevant ions Al³⁺, Fe³⁺, and Cr³⁺. Finally, the effectiveness of our new models is demonstrated in MD simulations of several diverse (and highly challenging to simulate) metalloproteins.