Modeling the Alkaline Hydrolysis of Diaryl Sulfate Diesters: A Mechanistic Study.

Phosphate and sulfate esters have important roles in regulating cellular processes. However, while there has been substantial experimental and computational investigation of the mechanisms and the transition states involved in phosphate ester hydrolysis, there is far less work on sulfate ester hydrolysis. Here, we report a detailed computational study of the alkaline hydrolysis of diaryl sulfate diesters, using different DFT functionals as well as mixed implicit/explicit solvation with varying numbers of explicit water molecules. We consider the impact of the computational model on computed linear free-energy relationships (LFER) and the nature of the transition states (TS) involved. We obtain good qualitative agreement with experimental LFER data when using a pure implicit solvent model and excellent agreement with experimental kinetic isotope effects for all models used. Our calculations suggest that sulfate diester hydrolysis proceeds through loose transition states, with minimal bond formation to the nucleophile and bond cleavage to the leaving group already initiated. Comparison to prior work indicates that these TS are similar in nature to those for the alkaline hydrolysis of neutral arylsulfonate monoesters or charged phosphate diesters and fluorophosphates. Obtaining more detailed insights into the transition states involved assists in understanding the selectivity of enzymes that hydrolyze these reactions.

Enzyme Evolution: An Epistatic Ratchet versus a Smooth Reversible Transition.

Evolutionary trajectories are deemed largely irreversible. In a newly diverged protein, reversion of mutations that led to the functional switch typically results in loss of both the new and the ancestral functions. Nonetheless, evolutionary transitions where reversions are viable have also been described. The structural and mechanistic causes of reversion compatibility versus incompatibility therefore remain unclear. We examined two laboratory evolution trajectories of mammalian paraoxonase-1, a lactonase with promiscuous organophosphate hydrolase (OPH) activity. Both trajectories began with the same active-site mutant, His115Trp, which lost the native lactonase activity and acquired higher OPH activity. A neo-functionalization trajectory amplified the promiscuous OPH activity, whereas the re-functionalization trajectory restored the native activity, thus generating a new lactonase that lacks His115. The His115 revertants of these trajectories indicated opposite trends. Revertants of the neo-functionalization trajectory lost both the evolved OPH and the original lactonase activity. Revertants of the trajectory that restored the original lactonase function were, however, fully active. Crystal structures and molecular simulations show that in the newly diverged OPH, the reverted His115 and other catalytic residues are displaced, thus causing loss of both the original and the new activity. In contrast, in the re-functionalization trajectory, reversion compatibility of the original lactonase activity derives from mechanistic versatility whereby multiple residues can fulfill the same task. This versatility enables unique sequence-reversible compositions that are inaccessible when the active site was repurposed toward a new function.

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.

Active Site Hydrophobicity and the Convergent Evolution of Paraoxonase Activity in Structurally Divergent Enzymes: The Case of Serum Paraoxonase 1.

Serum paraoxonase 1 (PON1) is a native lactonase capable of promiscuously hydrolyzing a broad range of substrates, including organophosphates, esters, and carbonates. Structurally, PON1 is a six-bladed ß-propeller with a flexible loop (residues 70-81) covering the active site. This loop contains a functionally critical Tyr at position 71. We have performed detailed experimental and computational analyses of the role of selected Y71 variants in the active site stability and catalytic activity in order to probe the role of Y71 in PON1's lactonase and organophosphatase activities. We demonstrate that the impact of Y71 substitutions on PON1's lactonase activity is minimal, whereas the kcat for the paraoxonase activity is negatively perturbed by up to 100-fold, suggesting greater mutational robustness of the native activity. Additionally, while these substitutions modulate PON1's active site shape, volume, and loop flexibility, their largest effect is in altering the solvent accessibility of the active site by expanding the active site volume, allowing additional water molecules to enter. This effect is markedly more pronounced in the organophosphatase activity than the lactonase activity. Finally, a detailed comparison of PON1 to other organophosphatases demonstrates that either a similar "gating loop" or a highly buried solvent-excluding active site is a common feature of these enzymes. We therefore posit that modulating the active site hydrophobicity is a key element in facilitating the evolution of organophosphatase activity. This provides a concrete feature that can be utilized in the rational design of next-generation organophosphate hydrolases that are capable of selecting a specific reaction from a pool of viable substrates.

Linking coupled motions and entropic effects to the catalytic activity of 2-deoxyribose-5-phosphate aldolase (DERA).

DERA, 2-deoxyribose-5-phosphate aldolase, catalyzes the retro-aldol cleavage of 2-deoxy-ribose-5-phosphate (dR5P) into glyceraldehyde-3-phosphate (G3P) and acetaldehyde in a branch of the pentose phosphate pathway. In addition to the physiological reaction, DERA also catalyzes the reverse addition reaction and, hence, is an interesting candidate for bio-catalysis of carbo-ligation reactions, which are central to synthetic chemistry. An obstacle to overcome for this enzyme to become a truly useful biocatalyst, however, is to relax the very strict dependency of this enzyme on phosphorylated substrates. We have studied herein the role of the non-canonical phosphate-binding site of this enzyme, consisting of Ser238 and Ser239, by site-directed and site-saturation mutagenesis, coupled to kinetic analysis of mutants. In addition, we have performed molecular dynamics simulations on the wild-type and four mutant enzymes, to analyse how mutations at this phosphate-binding site may affect the protein structure and dynamics. Further examination of the S239P mutant revealed that this variant increases the enthalpy change at the transition state, relative to the wild-type enzyme, but concomitant loss in entropy causes an overall relative loss in the TS free energy change. This entropy loss, as measured by the temperature dependence of catalysed rates, was mirrored in both a drastic loss in dynamics of the enzyme, which contributes to phosphate binding, as well as an overall loss in anti-correlated motions distributed over the entire protein. Our combined data suggests that the degree of anticorrelated motions within the DERA structure is coupled to catalytic efficiency in the DERA-catalyzed retro-aldol cleavage reaction, and can be manipulated for engineering purposes.

Modeling the mechanisms of biological GTP hydrolysis.

Enzymes that hydrolyze GTP are currently in the spotlight, due to their molecular switch mechanism that controls many cellular processes. One of the best-known classes of these enzymes are small GTPases such as members of the Ras superfamily, which catalyze the hydrolysis of the γ-phosphate bond in GTP. In addition, the availability of an increasing number of crystal structures of translational GTPases such as EF-Tu and EF-G have made it possible to probe the molecular details of GTP hydrolysis on the ribosome. However, despite a wealth of biochemical, structural and computational data, the way in which GTP hydrolysis is activated and regulated is still a controversial topic and well-designed simulations can play an important role in resolving and rationalizing the experimental data. In this review, we discuss the contributions of computational biology to our understanding of GTP hydrolysis on the ribosome and in small GTPases.

Catalytic stimulation by restrained active-site floppiness--the case of high density lipoprotein-bound serum paraoxonase-1.

Despite the abundance of membrane-associated enzymes, the mechanism by which membrane binding stabilizes these enzymes and stimulates their catalysis remains largely unknown. Serum paraoxonase-1 (PON1) is a lipophilic lactonase whose stability and enzymatic activity are dramatically stimulated when associated with high-density lipoprotein (HDL) particles. Our mutational and structural analyses, combined with empirical valence bond simulations, reveal a network of hydrogen bonds that connect HDL binding residues with Asn168--a key catalytic residue residing >15Å from the HDL contacting interface. This network ensures precise alignment of N168, which, in turn, ligates PON1's catalytic calcium and aligns the lactone substrate for catalysis. HDL binding restrains the overall motion of the active site and particularly of N168, thus reducing the catalytic activation energy barrier. We demonstrate herein that disturbance of this network, even at its most far-reaching periphery, undermines PON1's activity. Membrane binding thus immobilizes long-range interactions via second- and third-shell residues that reduce the active site's floppiness and pre-organize the catalytic residues. Although this network is critical for efficient catalysis, as demonstrated here, unraveling these long-rage interaction networks is challenging, let alone their implementation in artificial enzyme design.