Computational biotechnology: Prediction of competitive substrate inhibition of enzymes by buffer compounds with protein–ligand docking

Biodegradation of patulin in fresh pear juice by an aldo-keto reductase from Meyerozyma guilliermondii

Bio-enzymes have shown broad application prospects in controlling mycotoxins due to their strong specificity, fast reaction rate and mild reaction conditions. However, the number of enzymes isolated, purified and characterized to degrade patulin (PAT) is limited. We expressed an aldo-keto reductase (MgAKR) from Meyerozyma guilliermondii in Escherichia coli. The results demonstrated that the purified MgAKR could convert PAT into ascladiol in vitro with NADPH serving as a coenzyme. Adding 300 μg/mL MgAKR resulted in an 88 % reduction of PAT in fresh pear juice without affecting its quality in the biodegradation process. The site-directed mutagenesis suggested that the interaction between MgAKR and PAT occurred through the active sites of Lys242 and Leu240. This study serves as a valuable theoretical reference for the development of enzymes aimed at detoxifying PAT in fruit and their derivatives.

Assay Development for Metal-Dependent Enzymes-Influence of Reaction Buffers on Activities and Kinetic Characteristics

Buffers are often thought of as innocuous components of a reaction, with the sole task of maintaining the pH of a system. However, studies had shown that this is not always the case. Common buffers used in biochemical research, such as Tris (hydroxymethyl) aminomethane hydrochloride (Tris-HCl), can chelate metal ions and may thus affect the activity of metalloenzymes, which are enzymes that require metal ions for enhanced catalysis. To determine whether enzyme activity is influenced by buffer identity, the activity of three enzymes (BLC23O, Ro1,2-CTD, and trypsin) was comparatively characterized in N-2- hydroxyethylpiperazine-N'-2-ethanesulfonic acid (HEPES), Tris-HCl, and sodium phosphate buffer. The pH and temperature optima of BLC23O, a Mn2+-dependent dioxygenase, were first identified, and then the metal ion dissociation constant (Kd) was determined in the three buffer systems. It was observed that BLC23O exhibited different Kd values depending on the buffer, with the lowest (1.49 ± 0.05 μM) recorded in HEPES under the optimal set of conditions (pH 7.6 and 32.5 °C). Likewise, the kinetic parameters obtained varied depending on the buffer, with HEPES (pH 7.6) yielding overall the greatest catalytic efficiency and turnover number (kcat = 0.45 ± 0.01 s-1; kcat/Km = 0.84 ± 0.02 mM-1 s-1). To corroborate findings, the characterization of Fe3+-dependent Ro1,2-CTD was performed, resulting in different kinetic constants depending on the buffer (Km (HEPES, Tris-HCl, and Na-phosphate) = 1.80, 6.93, and 3.64 μM; kcat(HEPES, Tris-HCl, and Na-phosphate) = 0.64, 1.14, and 1.01 s-1; kcat/Km(HEPES, Tris-HCl, and Na-phosphate)= 0.36, 0.17, and 0.28 μM-1 s-1). In order to determine whether buffer identity influenced the enzymatic activity of nonmetalloenzymes alike, the characterization of trypsin was also carried out. Contrary to the previous results, trypsin yielded comparable kinetic parameters independent of the buffer (Km (HEPES, Tris-HCl, and Na-Phosphate) = 3.14, 3.07, and 2.91 mM; kcat(HEPES, Tris-HCl, and Na-phosphate) = 1.51, 1.47, and 1.53 s-1; kcat/Km (HEPES, Tris-HCl, and Na-phosphate) = 0.48, 0.48, and 0.52 mM-1 s-1). These results showed that the activity of tested metalloenzymes was impacted by different buffers. While selected buffers did not influence the tested nonmetalloenzyme activity, other research had shown impacts of buffers on other enzyme activities. As a result, we suggest that buffer selection be optimized for any new enzymes such that the results from one lab to another can be accurately compared.

Effects of oxygen fertilization on damage reduction in flooded snap bean (Phaseolus vulgaris L.)

Flooding is one of the major abiotic stresses for vegetable production in Florida. Hydroponic and pot trials were conducted with snap bean to evaluate the effects of oxygen fertilization on the biochemical and physiological status of flooded snap bean plants. There were three treatments in the hydroponic trials were: (1) flooded (control), (2) bubble aeration with ambient air, and (3) hydrogen peroxide (H₂O₂) applied at the beginning of the trial. Plant health was evaluated by determining nitrogen (N) and phosphorus (P) uptake rates. The greenhouse pot trials were used to quantify the effects of three different application rates of solid oxygen fertilizers as calcium peroxide (CaO₂) and magnesium peroxide (MgO₂). The results showed that plant N and P uptake rates were significantly greater (p < 0.05) with H₂O₂ than without H₂O₂. The N uptake rates with H₂O₂ were like that of those with bubbling. The uptake rate of NH₄⁺ was significantly greater than that of NO₃^- with the bubbling and H₂O₂ conditions_, but the uptake rate of NO₃^- was significantly greater than that of NH₄⁺ in the flooding condition. The plant height, leaf greenness, shoot biomass, and yield were all significantly greater with CaO₂ or MgO₂ than without either solid oxygen fertilizer. The minimum damage of flooded snap bean was found with 2 g CaO₂ or 4 g MgO₂ per pot. These results indicated that oxygen fertilization may potentially improve yield of flooded snap bean plants.

Substrate-imprinted docking of Agrobacterium tumefaciens uronate dehydrogenase for increased substrate selectivity

Agrobacterium tumefaciens uronate dehydrogenase (AtuUdh) belongs to the short-chain dehydrogenase superfamily, specifically those acting on the CH-OH group of donor with NAD⁺ or NADP⁺ as acceptor. It is apparently required for the production of D-glucaric acid. AtuUdh-catalyzed reaction is reversible with dual substrate-specific activity (D-galacturonic acid and D-glucuronic acid) in nature. In our study, 34 mutants were pre-screened from 155 mutants generated from AtuUdh (wild-type) and selected 10 structurally stable mutants with increased substrate selectivity. The specificity, efficiency, and selectivity of these mutants for different substrates and cofactors were predicted from 121 docked models using a substrate-imprinted docking approach. Q14F, S36L, and S75T mutants have shown a high binding affinity to D-glucuronic acid and its substrate intermediates such as D-glucaro-1,4-lactone and D-glucaro-1,5-lactone. These mutants exhibited a low binding affinity to the substrate and cofactor required for D-galactaric acid. D34S, N112E and S165E mutants found to show a high selectivity of D-galacturonic acid and its substrate intermediates for D-galactaric acid production. Ser75, Ser165, and Arg174 are active residues playing an imperative role in the substrate selectivity and also contributed in the conjecture the mechanism of transition state stabilization catalyzed by AtuUdh mutants. The present approach was used to reveal the substrate binding mechanism of AtuUdh mutants for a better understanding of the structural basis for selectivity and function.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Computational evaluation of factors governing catalytic 2-keto acid decarboxylation

Recent advances in computational approaches for creating pathways for novel biochemical reactions has motivated the development of approaches for identifying enzyme-substrate pairs that are attractive candidates for effecting catalysis. We present an improved structural-based strategy to probe and study enzyme-substrate binding based on binding geometry, energy, and molecule characteristics, which allows for in silico screening of structural features that imbue higher catalytic potential with specific substrates. The strategy is demonstrated using 2-keto acid decarboxylation with various pairs of 2-keto acids and enzymes. We show that this approach fitted experimental values for a wide range of 2-keto acid decarboxylases for different 2-keto acid substrates. In addition, we show that the structure-based methods can be used to select specific enzymes that may be promising candidates to catalyze decarboxylation of certain 2-keto acids. The key features and principles of the candidate enzymes evaluated by the strategy can be used to design novel biosynthesis pathways, to guide enzymatic mutation or to guide biomimetic catalyst design.