Computing the Role of Near Attack Conformations in an Enzyme-Catalyzed Nucleophilic Bimolecular Reaction

Substrate Turnover Dynamics Guide Ketol-Acid Reductoisomerase Redesign for Increased Specific Activity

The task of adapting enzymes for specific applications is often hampered by our incomplete ability to tune and tailor catalytic functions, particularly when seeking increased activity. Here, we develop and demonstrate a rational approach to address this challenge, applied to ketol-acid reductoisomerase (KARI), which has uses in industrial-scale isobutanol production. While traditional structure-based computational enzyme redesign strategies typically focus on the enzyme-bound ground state (GS) and transition state (TS), we postulated that additionally treating the underlying dynamics of complete turnover events that connect and pass through both states could further elucidate the structural properties affecting catalysis and help identify mutations that lead to increased catalytic activity. To examine the dynamics of substrate conversion with atomistic detail, we adapted and applied computational methods based on path sampling techniques to gather thousands of QM/MM simulations of attempted substrate turnover events by KARI: both productive (reactive) and unproductive (nonreactive) attempts. From these data, machine learning models were constructed and used to identify specific conformational features (interatomic distances, angles, and torsions) associated with successful, productive catalysis. Multistate protein redesign techniques were then used to select mutations that stabilized reactive-like structures over nonreactive-like ones while also meeting additional criteria consistent with enhanced specific activity. This procedure resulted in eight high-confidence enzyme mutants with a significant improvement in calculated specific activity relative to wild type (WT), with the fastest variant's increase in calculated k cat being (2 ± 1) × 104-fold. Collectively, these results suggest that introducing mutations designed to increase the population of reaction-promoting conformations of the enzyme-substrate complex before it reaches the barrier can provide an effective approach to engineering improved enzyme catalysts.

Reconstructing dynamics correlation network to simultaneously improve activity and stability of 2,3-butanediol dehydrogenase by design of distal interchain disulfide bonds

The complete enzyme catalytic cycle includes substrate binding, chemical reaction and product release, in which different dynamic conformations are adopted. Due to the complex relationship among enzyme activity, stability and dynamics, the directed evolution of enzymes for improved activity or stability commonly leads to a trade-off in stability or activity. It hence remains a challenge to engineer an enzyme to have both enhanced activity and stability. Here, we have attempted to reconstruct the dynamics correlation network involved with active center to improve both activity and stability of a 2,3-butanediol dehydrogenase (2,3-BDH) by introducing inter-chain disulfide bonds. A computational strategy was first applied to evaluate the effect of introducing inter-chain disulfide bond on activity and stability of three 2,3-BDHs, and the N258C mutation of 2,3-BDH from Corynebacterium glutamicum (CgBDH) was proved to be effective in improving both activity and stability. In the results, CgBDH-N258C showed a different unfolding curve from the wild type, with two melting temperatures (Tm) of 68.3 °C and 50.8 °C, 19.7 °C and 2 °C higher than 48.6 °C of the wild type. Its half-life was also improved by 14.8-fold compared to the wild type. Catalytic efficiency (kcat/Km) of the mutant was increased by 7.9-fold toward native substrate diacetyl and 8.8-fold toward non-native substrate 2,5-hexanedione compared to the wild type. Molecular dynamics simulations revealed that an interaction network formed by Cys258, Arg162, Ala144 and the catalytic residues was reconstructed in the mutant and the dynamics change caused by the disulfide bond could be propagated through the interactions network. This improved the enzyme stability and activity by decreasing the flexibility and locking more "reactive" pose, respectively. Further construction of mutations including A144G showing a 44-fold improvement in catalytic efficiency toward meso-2,3-BD confirmed the role of modifying dynamics correlation network in tunning enzyme activity and selectivity. This study provided important insights into the relationship among dynamics, enzyme catalysis and stability, and will be useful in the designing new enzymes with co-evolution of stability, activity and selectivity.

Pralidoxime-like reactivator with increased lipophilicity - Molecular modeling and in vitro study

Acetylcholinesterase (AChE, EC 3.1.1.7) reactivators (2-PAM, trimedoxime, obidoxime, asoxime) have become an integral part of antidotal treatment in cases of nerve agent and organophosphorus (OP) pesticide poisonings. They are often referred to as specific antidotes due to their ability to restore AChE function when it has been covalently inhibited by an OP compound. Currently available commercial reactivators exhibit limited ability to penetrate the blood-brain barrier, where reactivation of inhibited AChE is crucial. Consequently, there have been numerous efforts to discover more brain-penetrating AChE reactivators. In this study, we examined a derivative of 2-PAM designed to possess increased lipophilicity. This enhanced lipophilicity was achieved through the incorporation of a benzyl group into its molecular structure. Initially, a molecular modeling study was conducted, followed by a comparison of its reactivation efficacy with that of 2-PAM against 10 different AChE inhibitors in vitro. Unfortunately, this relatively significant structural modification of 2-PAM resulted in a decrease in its reactivation potency. Consequently, this derivative cannot be considered as a broad-spectrum AChE reactivator.

Characterization and structure-based protein engineering of a regiospecific saponin acetyltransferase from Astragalus membranaceus

Acetylation contributes to the bioactivity of numerous medicinally important natural products. However, little is known about the acetylation on sugar moieties. Here we report a saponin acetyltransferase from Astragalus membranaceus. AmAT7-3 is discovered through a stepwise gene mining approach and characterized as the xylose C3'/C4'-O-acetyltransferse of astragaloside IV (1). To elucidate its catalytic mechanism, complex crystal structures of AmAT7-3/1 and AmAT7-3A310G/1 are obtained, which reveal a large active pocket decided by a specific sequence AADAG. Combining with QM/MM computation, the regiospecificity of AmAT7-3 is determined by sugar positioning modulated by surrounding amino acids including #A310 and #L290. Furthermore, a small mutant library is built using semi-rational design, where variants A310G and A310W are found to catalyze specific C3'-O and C4'-O acetylation, respectively. AmAT7-3 and its variants are also employed to acetylate other bioactive saponins. This work expands the understanding of saponin acetyltransferases, and provide efficient catalytic tools for saponin acetylation.

Applications of the Near Attack Conformation (NAC) approach in the search for Acetylcholinesterase reactivators

The Near Attack Conformation (NAC) approach states that the efficiency of an enzyme-catalyzed reaction depends on the prior attainment of optimal conditions for substrate atom organization and positioning for bond formation. These conditions are prerequisites for the transition state (TS) in which the involved atoms are within the van der Waals range of contact and positioned at an angle similar to that achieved after bond formation. The successful application of this approach to investigate the reactivation mechanism of acetylcholinesterase inhibited by nerve agents has contributed to a better understanding of this mechanism and demonstrated consistent corroboration with experimental data. In this article, we summarize the accomplishments achieved thus far and outline future perspectives.

Efficient polyethylene terephthalate degradation at moderate temperature: a protein engineering study of LC-cutinase highlights the key role of residue 243

Enzymatic degradation of poly(ethylene terephthalate) (PET) is becoming a reality because of the identification of novel PET-hydrolysing enzymes (PHEs) and the engineering of evolved enzyme variants. Here, improved variants of leaf-branch compost cutinase (LCC), a thermostable enzyme isolated by a metagenomic approach, were generated by a semi-rational protein engineering approach. Starting from a deleted LCC form lacking the secretion signal (ΔLCC), single and double variants possessing a higher activity on PET were isolated. The single-point F243T ΔLCC variant partially (~ 67%) depolymerized amorphous PET film producing ~ 21.9 mm of products after 27 h of reaction at 72 °C. The S101N/F243T ΔLCC double variant reached a further increase in activity on PET. Notably, for both single and double variants the highest conversion yield was obtained at 55 °C. Kinetics studies and molecular dynamics simulations support that a slight decreased affinity for PET is responsible for the superior degradation performance of the S101N/F243T variant and that this stems from a slightly higher flexibility of the active site region close to position 243. Furthermore, our findings question the need for a high reaction temperature for PET degradation, at least for LCC: at ≥ 70 °C, the conversion of amorphous PET into a more crystalline polymer, resistant to enzymatic hydrolysis, is favoured. The evolved S101N/F243T ΔLCC variant is able to depolymerize fully 1.3 g of untreated postconsumer PET waste in ≤ 3 days at 55 °C (using 1.25 mg of enzyme only), this making PET enzymatic degradation by engineering LCC a more ecofriendly and sustainable process.

An Efficient Protein Evolution Workflow for the Improvement of Bacterial PET Hydrolyzing Enzymes

Enzymatic degradation is a promising green approach to bioremediation and recycling of the polymer poly(ethylene terephthalate) (PET). In the past few years, several PET-hydrolysing enzymes (PHEs) have been discovered, and new variants have been evolved by protein engineering. Here, we report on a straightforward workflow employing semi-rational protein engineering combined to a high-throughput screening of variant libraries for their activity on PET nanoparticles. Using this approach, starting from the double variant W159H/S238F of Ideonella sakaiensis 201-F6 PETase, the W159H/F238A-ΔIsPET variant, possessing a higher hydrolytic activity on PET, was identified. This variant was stabilized by introducing two additional known substitutions (S121E and D186H) generating the TS-ΔIsPET variant. By using 0.1 mg mL⁻¹ of TS-ΔIsPET, ~10.6 mM of degradation products were produced in 2 days from 9 mg mL⁻¹ PET microparticles (~26% depolymerization yield). Indeed, TS-ΔIsPET allowed a massive degradation of PET nanoparticles (>80% depolymerization yield) in 1.5 h using only 20 μg of enzyme mL⁻¹. The rationale underlying the effect on the catalytic parameters due to the F238A substitution was studied by enzymatic investigation and molecular dynamics/docking analysis. The present workflow is a well-suited protocol for the evolution of PHEs to help generate an efficient enzymatic toolbox for polyester degradation.

Exploring Dihydroflavonol-4-Reductase Reactivity and Selectivity by QM/MM-MD Simulations

Flavonoids are secondary metabolites ubiquitously found in plants. Their antioxidant properties make them highly interesting natural compounds for use in pharmacology. Therefore, unravelling the mechanisms of flavonoid biosynthesis is an important challenge. Among all the enzymes involved in this biosynthetic pathway, dihydroflavonol-4-reductase (DFR) plays a key role in the production of anthocyanins and proanthocyanidins. Here, we provide new information on the mechanism of action of this enzyme by using QM/MM-MD simulations applied to both dihydroquercetin (DHQ) and dihydrokaempferol (DHK) substrates. The consideration of these very similar compounds shed light on the major role played by the enzyme on the stabilization of the transition state but also on the activation of the substrate before the reaction through near-attack conformer effects.

Computational Prediction of ω-Transaminase Specificity by a Combination of Docking and Molecular Dynamics Simulations

ω-Transaminases (ω-TAs) catalyze the conversion of ketones to chiral amines, often with high enantioselectivity and specificity, which makes them attractive for industrial production of chiral amines. Tailoring ω-TAs to accept non-natural substrates is necessary because of their limited substrate range. We present a computational protocol for predicting the enantioselectivity and catalytic selectivity of an ω-TA from Vibrio fluvialis with different substrates and benchmark it against 62 compounds gathered from the literature. Rosetta-generated complexes containing an external aldimine intermediate of the transamination reaction are used as starting conformations for multiple short independent molecular dynamics (MD) simulations. The combination of molecular docking and MD simulations ensures sufficient and accurate sampling of the relevant conformational space. Based on the frequency of near-attack conformations observed during the MD trajectories, enantioselectivities can be quantitatively predicted. The predicted enantioselectivities are in agreement with a benchmark dataset of experimentally determined ee% values. The substrate-range predictions can be based on the docking score of the external aldimine intermediate. The low computational cost required to run the presented framework makes it feasible for use in enzyme design to screen thousands of enzyme variants.

The HIV-1 Nucleocapsid Regulates Its Own Condensation by Phase-Separated Activity-Enhancing Sequestration of the Viral Protease during Maturation

A growing number of studies indicate that mRNAs and long ncRNAs can affect protein populations by assembling dynamic ribonucleoprotein (RNP) granules. These phase-separated molecular ‘sponges’, stabilized by quinary (transient and weak) interactions, control proteins involved in numerous biological functions. Retroviruses such as HIV-1 form by self-assembly when their genomic RNA (gRNA) traps Gag and GagPol polyprotein precursors. Infectivity requires extracellular budding of the particle followed by maturation, an ordered processing of ∼2400 Gag and ∼120 GagPol by the viral protease (PR). This leads to a condensed gRNA-NCp7 nucleocapsid and a CAp24-self-assembled capsid surrounding the RNP. The choreography by which all of these components dynamically interact during virus maturation is one of the missing milestones to fully depict the HIV life cycle. Here, we describe how HIV-1 has evolved a dynamic RNP granule with successive weak–strong–moderate quinary NC-gRNA networks during the sequential processing of the GagNC domain. We also reveal two palindromic RNA-binding triads on NC, KxxFxxQ and QxxFxxK, that provide quinary NC-gRNA interactions. Consequently, the nucleocapsid complex appears properly aggregated for capsid reassembly and reverse transcription, mandatory processes for viral infectivity. We show that PR is sequestered within this RNP and drives its maturation/condensation within minutes, this process being most effective at the end of budding. We anticipate such findings will stimulate further investigations of quinary interactions and emergent mechanisms in crowded environments throughout the wide and growing array of RNP granules.

Multiscale Approach for Computing Gated Ligand Binding from Molecular Dynamics and Brownian Dynamics Simulations

We develop an approach to characterize the effects of gating by a multiconformation protein consisting of macrostate conformations that are either accessible or inaccessible to ligand binding. We first construct a Markov state model of the apo-protein from atomistic molecular dynamics simulations from which we identify macrostates and their conformations, compute their relative macrostate populations and interchange kinetics, and structurally characterize them in terms of ligand accessibility. We insert the calculated first-order rate constants for conformational transitions into a multistate gating theory from which we derive a gating factor γ that quantifies the degree of conformational gating. Applied to HIV-1 protease, our approach yields a kinetic network of three accessible (semi-open, open, and wide-open) and two inaccessible (closed and a newly identified, "parted") macrostate conformations. The parted conformation sterically partitions the active site, suggesting a possible role in product release. We find that the binding kinetics of drugs and drug-like inhibitors to HIV-1 protease falls in the slow gating regime. However, because γ = 0.75, conformational gating only modestly slows ligand binding. Brownian dynamics simulations of the diffusional association of eight inhibitors to the protease─having a wide range of experimental association constants (∼10⁴-10¹⁰ M^-1 s^-1)─yields gated rate constants in the range of ∼0.5-5.7 × 10⁸ M^-1 s^-1. This indicates that, whereas the association rate of some inhibitors could be described by the model, for many inhibitors either subsequent conformational transitions or alternate binding mechanisms may be rate-limiting. For systems known to be modulated by conformational gating, the approach could be scaled computationally efficiently to screen association kinetics for a large number of ligands.

Fine-Tuning of Sequence Specificity by Near Attack Conformations in Enzyme-Catalyzed Peptide Hydrolysis

The catalytic role of near attack conformations (NACs), molecular states that lie on the pathway between the ground state (GS) and transition state (TS) of a chemical reaction, is not understood completely. Using a computational approach that combines Bürgi–Dunitz theory with all-atom molecular dynamics simulations, the role of NACs in catalyzing the first stages of HIV-1 protease peptide hydrolysis was previously investigated using a substrate that represents the recognized SP1-NC cleavage site of the HIV-1 Gag polyprotein. NACs were found to confer no catalytic effect over the uncatalyzed reaction there ( Δ Δ G N ‡ ∼ 0 kcal/mol). Here, using the same approach, the role of NACs across multiple substrates that each represent a further recognized cleavage site is investigated. Overall rate enhancement varies by | Δ Δ G ‡ | ∼ 12–15 kcal/mol across this set, and although NACs contribute a small and approximately constant barrier to the uncatalyzed reaction (< Δ G N ‡ u > = 4.3 ± 0.3 kcal/mol), they are found to contribute little significant catalytic effect ( | Δ Δ G N ‡ | ∼ 0–2 kcal/mol). Furthermore, no correlation is exhibited between NAC contributions and the overall energy barrier ( R 2 = 0.01). However, these small differences in catalyzed NAC contributions enable rates to match those required for the kinetic order of processing. Therefore, NACs may offer an alternative and subtle mode compared to non-NAC contributions for fine-tuning reaction rates during complex evolutionary sequence selection processes—in this case across cleavable polyproteins whose constituents exhibit multiple functions during the virus life-cycle.

Visualizing Tetrahedral Oxyanion Bound in HIV-1 Protease Using Neutrons: Implications for the Catalytic Mechanism and Drug Design

HIV-1 protease is indispensable for virus propagation and an important therapeutic target for antiviral inhibitors to treat AIDS. As such inhibitors are transition-state mimics, a detailed understanding of the enzyme mechanism is crucial for the development of better anti-HIV drugs. Here, we used room-temperature joint X-ray/neutron crystallography to directly visualize hydrogen atoms and map hydrogen bonding interactions in a protease complex with peptidomimetic inhibitor KVS-1 containing a reactive nonhydrolyzable ketomethylene isostere, which, upon reacting with the catalytic water molecule, is converted into a tetrahedral intermediate state, KVS-1_TI. We unambiguously determined that the resulting tetrahedral intermediate is an oxyanion, rather than the gem-diol, and both catalytic aspartic acid residues are protonated. The oxyanion tetrahedral intermediate appears to be unstable, even though the negative charge on the oxyanion is delocalized through a strong n → π* hyperconjugative interaction into the nearby peptidic carbonyl group of the inhibitor. To better understand the influence of the ketomethylene isostere as a protease inhibitor, we have also examined the protease structure and binding affinity with keto-darunavir (keto-DRV), which similar to KVS-1 includes the ketomethylene isostere. We show that keto-DRV is a significantly less potent protease inhibitor than DRV. These findings shed light on the reaction mechanism of peptide hydrolysis catalyzed by HIV-1 protease and provide valuable insights into further improvements in the design of protease inhibitors.

Reactivation of VX-Inhibited Human Acetylcholinesterase by Deprotonated Pralidoxime. A Complementary Quantum Mechanical Study

In the present work, we performed a complementary quantum mechanical (QM) study to describe the mechanism by which deprotonated pralidoxime (2-PAM) could reactivate human (Homo sapiens sapiens) acetylcholinesterase (HssAChE) inhibited by the nerve agent VX. Such a reaction is proposed to occur in subsequent addition-elimination steps, starting with a nucleophile bimolecular substitution (S_N2) mechanism through the formation of a trigonal bipyramidal transition state (TS). A near attack conformation (NAC), obtained in a former study using molecular mechanics (MM) calculations, was taken as a starting point for this project, where we described the possible formation of the TS. Together, this combined QM/MM study on AChE reactivation shows the feasibility of the reactivation occurring via attack of the deprotonated form of 2-PAM against the Ser203-VX adduct of HssAChE.

Finding Reactive Configurations: A Machine Learning Approach for Estimating Energy Barriers Applied to Sirtuin 5

Sirtuin 5 is a class III histone deacetylase that, unlike its classification, mainly catalyzes desuccinylation and demanoylation reactions. It is an interesting drug target that we use here to test new ideas for calculating reaction pathways of large molecular systems such as enzymes. A major issue with most schemes (e.g., adiabatic mapping) is that the resulting activation barrier height heavily depends on the chosen educt conformation. This makes the selection of the initial structure decisive for the success of the characterization. Here, we apply machine learning to a large number of molecular dynamics frames and potential energy barriers obtained by quantum mechanics/molecular mechanics calculations in order to identify (1) suitable start-conformations for reaction path calculations and (2) structural features relevant for the first step of the desuccinylation reaction catalyzed by Sirtuin 5. The latter generally aids the understanding of reaction mechanisms and important interactions in active centers. Using our novel approach, we found eleven key features that govern the reactivity. We were able to estimate reaction barriers with a mean absolute error of 3.6 kcal/mol and identified reactive configurations.

Tuning molecular fluctuation to boost the conductance in DNA based molecular wires

Inherent molecular fluctuations are known to have a significant influence on the charge transport properties of biomolecules like DNA, PNA and proteins. In this work, we show ways to control these fluctuations and further demonstrate their use to enhance the conductance of two widely studied molecular wires, namely dsDNA (DNA) and G4 Quadruplex (G4-Quad). We quantify the molecular fluctuation in terms of the root mean square deviation (RMSD) of the molecule. In the case of DNA, we use temperature to control the fluctuations, while in the case of G4-Quad the fluctuations are tuned by the ions inside the pore. The electronic coupling between the bases of dsDNA and G4-Quad, which measures the conductance of these molecular wires, shows a non-monotonic behaviour with the increase in fluctuation. We find values of fluctuation which give rise to maximum electronic coupling and hence high conductivity for both the cases. In the case of DNA, these optimal fluctuations (∼2.5 Å) are achieved at a temperature of 210 K, which gives rise to an electronic coupling of 0.135 eV between the DNA bases. The optimal fluctuations in G4-Quad are achieved (∼7 Å) in a 4 base pair long system with 2 Na⁺ ions inside the pore, giving rise to an electronic coupling of 0.09 eV.

Modelling of substrate access and substrate binding to cephalosporin acylases

Semisynthetic cephalosporins are widely used antibiotics currently produced by different chemical steps under harsh conditions, which results in a considerable amount of toxic waste. Biocatalytic synthesis by the cephalosporin acylase from Pseudomonas sp. strain N176 is a promising alternative. Despite intensive engineering of the enzyme, the catalytic activity is still too low for a commercially viable process. To identify the bottlenecks which limit the success of protein engineering efforts, a series of MD simulations was performed to study for two acylase variants (WT, M6) the access of the substrate cephalosporin C from the bulk to the active site and the stability of the enzyme-substrate complex. In both variants, cephalosporin C was binding to a non-productive substrate binding site (E86α, S369β, S460β) at the entrance to the binding pocket, preventing substrate access. A second non-productive binding site (G372β, W376β, L457β) was identified within the binding pocket, which competes with the active site for substrate binding. Noteworthy, substrate binding to the protein surface followed a Langmuir model resulting in binding constants K = 7.4 and 9.2 mM for WT and M6, respectively, which were similar to the experimentally determined Michaelis constants KM = 11.0 and 8.1 mM, respectively.

Molecular modeling studies on the interactions of 7-methoxytacrine-4-pyridinealdoxime, 4-PA, 2-PAM, and obidoxime with VX-inhibited human acetylcholinesterase: a near attack conformation approach

7-methoxytacrine-4-pyridinealdoxime (7-MEOTA-4-PA, named hybrid 5C) is a compound formerly synthesized and evaluated in vitro, together with 4-pyridine aldoxime (4-PA) and commercial reactivators of acetylcholinesterase (AChE). This compound was designed with the purpose of being a prophylactic reactivator, capable of interacting with different subdomains of the active site of AChE. To investigate these interactions, theoretical results from docking were first compared with experimental data of hybrid 5C, 4-PA, and two commercial oximes, on the reactivation of human AChE (HssAChE) inhibited by VX. Then, further docking studies, molecular dynamics simulations, and molecular mechanics Poisson–Boltzmann surface area calculations, were carried out to investigate reactivation performances, considering the near attack conformation (NAC) approach, prior to the nucleophilic substitution mechanism. Our results helped to elucidate the interactions of such molecules with the different subdomains of the active site of HssAChE. Additionally, NAC poses of each oxime were suggested for further theoretical studies on the reactivation reaction.

Machine Learning Identifies Chemical Characteristics That Promote Enzyme Catalysis

Despite tremendous progress in understanding and engineering enzymes, knowledge of how enzyme structures and their dynamics induce observed catalytic properties is incomplete, and capabilities to engineer enzymes fall far short of industrial needs. Here, we investigate the structural and dynamic drivers of enzyme catalysis for the rate-limiting step of the industrially important enzyme ketol-acid reductoisomerase (KARI) and identify a region of the conformational space of the bound enzyme-substrate complex that, when populated, leads to large increases in reactivity. We apply computational statistical mechanical methods that implement transition interface sampling to simulate the kinetics of the reaction and combine this with machine learning techniques from artificial intelligence to select features relevant to reactivity and to build predictive models for reactive trajectories. We find that conformational descriptors alone, without the need for dynamic ones, are sufficient to predict reactivity with greater than 85% accuracy (90% AUC). Key descriptors distinguishing reactive from almost-reactive trajectories quantify substrate conformation, substrate bond polarization, and metal coordination geometry and suggest their role in promoting substrate reactivity. Moreover, trajectories constrained to visit a region of the reactant well, separated from the rest by a simple hyperplane defined by ten conformational parameters, show increases in computed reactivity by many orders of magnitude. This study provides evidence for the existence of reactivity promoting regions within the conformational space of the enzyme-substrate complex and develops methodology for identifying and validating these particularly reactive regions of phase space. We suggest that identification of reactivity promoting regions and re-engineering enzymes to preferentially populate them may lead to significant rate enhancements.

Catalytic mechanism of type C sialidase from Streptococcus pneumoniae: from covalent intermediate to final product

Streptococcus pneumoniae is a Gram-positive human pathogenic bacterium, which is the main cause of pneumonia and meningitis in children and the elderly. Three sialidases (or neuraminidases) encoded from Streptococcus pneumoniae could catalyze the cleavage of sialic acid linkages. This mechanism is directly connected with infection, apoptosis, and signaling, and usually considered to be one of the critical virulence factors. Type C neuraminidase (NanC) is unique because its primary product of Neu5Ac2en is considered to be an inhibitor to the other two sialidases. Experimentally, there are two different pathways for the formation mechanism of Neu5Ac2en catalyzed by NanC. In this work, a combined quantum mechanical and molecular mechanical approach was employed in all calculations. Starting from the covalent sialylated intermediate, we first examined the reaction to Neu5Ac2en and found the reaction prefers a direct proton abstraction mechanism rather than the water mediated proton abstraction mechanism. Free energy profiles can confirm that Neu5Ac2en is the major product of NanC. Functional roles of some important residues were also investigated, e.g., D315 acts as the proton acceptor during the formation of Neu5Ac2en, while the general base for the hydrolytic reaction to Neu5Ac. This study can facilitate the understanding of the catalytic mechanism of NanC and has the potential to aid in future inhibitor design studies.

Characterization and engineering of a plastic-degrading aromatic polyesterase

Synthetic polymers are ubiquitous in the modern world but pose a global environmental problem. While plastics such as poly(ethylene terephthalate) (PET) are highly versatile, their resistance to natural degradation presents a serious, growing risk to fauna and flora, particularly in marine environments. Here, we have characterized the 3D structure of a newly discovered enzyme that can digest highly crystalline PET, the primary material used in the manufacture of single-use plastic beverage bottles, in some clothing, and in carpets. We engineer this enzyme for improved PET degradation capacity and further demonstrate that it can also degrade an important PET replacement, polyethylene-2,5-furandicarboxylate, providing new opportunities for biobased plastics recycling.

Poly(ethylene terephthalate) (PET) is one of the most abundantly produced synthetic polymers and is accumulating in the environment at a staggering rate as discarded packaging and textiles. The properties that make PET so useful also endow it with an alarming resistance to biodegradation, likely lasting centuries in the environment. Our collective reliance on PET and other plastics means that this buildup will continue unless solutions are found. Recently, a newly discovered bacterium, Ideonella sakaiensis 201-F6, was shown to exhibit the rare ability to grow on PET as a major carbon and energy source. Central to its PET biodegradation capability is a secreted PETase (PET-digesting enzyme). Here, we present a 0.92 Å resolution X-ray crystal structure of PETase, which reveals features common to both cutinases and lipases. PETase retains the ancestral α/β-hydrolase fold but exhibits a more open active-site cleft than homologous cutinases. By narrowing the binding cleft via mutation of two active-site residues to conserved amino acids in cutinases, we surprisingly observe improved PET degradation, suggesting that PETase is not fully optimized for crystalline PET degradation, despite presumably evolving in a PET-rich environment. Additionally, we show that PETase degrades another semiaromatic polyester, polyethylene-2,5-furandicarboxylate (PEF), which is an emerging, bioderived PET replacement with improved barrier properties. In contrast, PETase does not degrade aliphatic polyesters, suggesting that it is generally an aromatic polyesterase. These findings suggest that additional protein engineering to increase PETase performance is realistic and highlight the need for further developments of structure/activity relationships for biodegradation of synthetic polyesters.

Phe71 in Type III Trypanosomal Protein Arginine Methyltransferase 7 (TbPRMT7) Restricts the Enzyme to Monomethylation

Protein arginine methyltransferase 7 (PRMT7) is unique within the PRMT family as it is the only isoform known to exclusively make monomethylarginine (MMA). Given its role in epigenetics, the mechanistic basis for the strict monomethylation activity is under investigation. It is thought that PRMT7 enzymes are unable to add a second methyl group because of steric hindrance in the active site that restricts them to monomethylation. To test this, we probed the active site of trypanosomal PRMT7 (TbPRMT7) using accelerated molecular dynamics, site-directed mutagenesis, kinetic, binding, and product analyses. Both the dynamics simulations and experimental results show that the mutation of Phe71 to Ile converts the enzyme from a type III methyltransferase into a mixed type I/II, that is, an enzyme that can now perform dimethylation. In contrast, the serine and alanine mutants of Phe71 preserve the type III behavior of the native enzyme. These results are inconsistent with a sterics-only model to explain product specificity. Instead, molecular dynamics simulations of these variants bound to peptides show hydrogen bonding between would-be substrates and Glu172 of TbPRMT7. Only in the case of the Phe71 to Ile mutation is this interaction between MMA and the enzyme maintained, and the geometry for optimal S_N2 methyl transfer is obtained. The results of these studies highlight the benefit of combined computational and experimental methods in providing a better understanding for how product specificity is dictated by PRMTs.

Impaired coordination of nucleophile and increased hydrophobicity in the +1 subsite shift levansucrase activity towards transfructosylation

Bacterial levansucrases produce β(2,6)-linked levan-type polysaccharides using sucrose or sucrose analogs as donor/acceptor substrates. However, the dominant reaction of Bacillus megaterium levansucrase (Bm-LS) is hydrolysis. Single domain levansucrases from Gram-positive bacteria display a wide substrate-binding pocket with open access to water, challenging engineering for transfructosylation-efficient enzymes. We pursued a shift in reaction specificity by either modifying the water distribution in the active site or the coordination of the catalytic acid/base (E352) and the nucleophile (D95), thus affecting the fructosyl-transfer rate and allowing acceptors other than water to occupy the active site. Two serine (173/422) and two water-binding tyrosine (421/439) residues located in the first shell of the catalytic pocket were modified. Library variants of S173, Y421 and S422, which coordinate the position of D95 and E352, show increased transfructosylation (30–200%) and modified product spectra. Substitutions at position 422 have a higher impact on sucrose affinity, while changes at position 173 and 421 have a strong effect on the overall catalytic rate. As most retaining glycoside hydrolases (GHs) Bm-LS catalyzes hydrolysis and transglycosylation via a double displacement reaction involving two-transition states (TS1 and TS2). Hydrogen bonds of D95 with the side chains of S173 and S422 contribute a total of 2.4 kcal mol⁻¹ to TS1 stabilization, while hydrogen bonds between invariant Y421, E352 and the glucosyl C-2 hydroxyl-group of sucrose contribute 2.15 kcal mol⁻¹ stabilization. Changes at Y439 render predominantly hydrolytic variants synthesizing shorter oligosaccharides.