Combined Theoretical and Experimental Study to Unravel the Differences in Promiscuous Amidase Activity of Two Nonhomologous Enzymes

Engineering Glucosamine-6-Phosphate Synthase to Achieve Efficient One-Step Biosynthesis of Glucosamine

As an important functional monosaccharide, glucosamine (GlcN) is widely used in fields such as medicine, food nutrition, and health care. Here, we report a distinct GlcN biosynthesis method that utilizes engineered Bacillus subtilis glucosamine-6-phosphate synthase (BsGlmS) to convert D-fructose to directly generate GlcN. The best variant obtained by using a combinatorial active-site saturation test/iterative saturation mutagenesis (CAST/ISM) strategy was a quadruple mutant S596D/V597G/S347H/G299Q (BsGlmS-BK19), which has a catalytic activity 1736-fold that of the wild type toward D-fructose. Upon using mutant BK19 as a whole-cell catalyst, D-fructose was converted into GlcN with 65.32% conversion in 6 h, whereas the wild type only attained a conversion rate of 0.31% under the same conditions. Molecular docking and molecular dynamics simulations were implemented to provide insights into the mechanism underlying the enhanced activity of BK19. Importantly, the BsGlmS-BK19 variant specifically catalyzes D-fructose without the need for phosphorylated substrates, representing a significant advancement in GlcN biosynthesis.

Computational study of the mechanism of a polyurethane esterase A (PueA) from Pseudomonas chlororaphis

The effective management of plastic waste has become a global imperative, given our reliance on a linear model in which plastics are manufactured, used once, and then discarded. This has led to the pervasive accumulation of plastic debris in landfills and environmental contamination. Recognizing this issue, numerous initiatives are underway to address the environmental repercussions associated with plastic disposal. In this study, we investigate the possible molecular mechanism of polyurethane esterase A (PueA), which has been previously identified as responsible for the degradation of a polyester polyurethane (PU) sample in Pseudomonas chlororaphis, as an effort to develop enzymatic biodegradation solutions. After generating the unsolved 3D structure of the protein by AlphaFold2 from its known genome, the enzymatic hydrolysis of the same model PU compound previously used in experiments has been explored employing QM/MM molecular dynamics simulations. This required a preliminary analysis of the 3D structure of the apo-enzyme, identifying the putative active site, and the search for the optimal protein-substrate binding site. Finally, the resulting free energy landscape indicates that wild-type PueA can degrade PU chains, although with low-level activity. The reaction takes place by a characteristic four-step path of the serine hydrolases, involving an acylation followed by a diacylation step. Energetics and structural analysis of the evolution of the active site along the reaction suggests that PueA can be considered a promising protein scaffold for further development to achieve efficient biodegradation of PU.

Electrostatics as a Guiding Principle in Understanding and Designing Enzymes

Enzyme design faces challenges related to the implementation of the basic principles that govern the catalytic activity in natural enzymes. In this work, we revisit basic electrostatic concepts that have been shown to explain the origin of enzymatic efficiency like preorganization and reorganization. Using magnitudes such as the electrostatic potential and the electric field generated by the protein, we explain how these concepts work in different enzymes and how they can be used to rationalize the consequences of point mutations. We also discuss examples of protein design in which electrostatic effects have been implemented. For the near future, molecular simulations, coupled with the use of machine learning methods, can be used to implement electrostatics as a guiding principle for enzyme designs.

Free Energy Profile Decomposition Analysis for QM/MM Simulations of Enzymatic Reactions

In enzyme mechanistic studies and mutant design, it is highly desirable to know the individual residue contributions to the reaction free energy and barrier. In this work, we show that such free energy contributions from each residue can be readily obtained by postprocessing ab initio quantum mechanical molecular mechanical (ai-QM/MM) free energy simulation trajectories. Specifically, through a mean force integration along the minimum free energy pathway, one can obtain the electrostatic, polarization, and van der Waals contributions from each residue to the free energy barrier. Separately, a similar analysis procedure allows us to assess the contribution from different collective variables along the reaction coordinate. The chorismate mutase reaction is used to demonstrate the utilization of these two trajectory analysis tools.

Artificial Intelligence Aided Lipase Production and Engineering for Enzymatic Performance Improvement

With the development of artificial intelligence (AI), tailoring methods for enzyme engineering have been widely expanded. Additional protocols based on optimized network models have been used to predict and optimize lipase production as well as properties, namely, catalytic activity, stability, and substrate specificity. Here, different network models and algorithms for the prediction and reforming of lipase, focusing on its modification methods and cases based on AI, are reviewed in terms of both their advantages and disadvantages. Different neural networks coupled with various algorithms are usually applied to predict the maximum yield of lipase by optimizing the external cultivations for lipase production, while one part is used to predict the molecule variations affecting the properties of lipase. However, few studies have directly utilized AI to engineer lipase by affecting the structure of the enzyme, and a set of research gaps needs to be explored. Additionally, future perspectives of AI application in enzymes, including lipase engineering, are deduced to help the redesign of enzymes and the reform of new functional biocatalysts. This review provides a new horizon for developing effective and innovative AI tools for lipase production and engineering and facilitating lipase applications in the food industry and biomass conversion.

Mechanistic studies of a lipase unveil effect of pH on hydrolysis products of small PET modules

Biocatalysis is a key technology enabling plastic recycling. However, despite advances done in the development of plastic-degrading enzymes, the molecular mechanisms that govern their catalytic performance are poorly understood, hampering the engineering of more efficient enzyme-based technologies. In this work, we study the hydrolysis of PET-derived diesters and PET trimers catalyzed by the highly promiscuous lipase B from Candida antarctica (CALB) through QM/MM molecular dynamics simulations supported by experimental Michaelis-Menten kinetics. The computational studies reveal the role of the pH on the CALB regioselectivity toward the hydrolysis of bis-(hydroxyethyl) terephthalate (BHET). We exploit this insight to perform a pH-controlled biotransformation that selectively hydrolyzes BHET to either its corresponding diacid or monoesters using both soluble and immobilized CALB. The discoveries presented here can be exploited for the valorization of BHET resulting from the organocatalytic depolymerization of PET.

Computational design of an amidase by combining the best electrostatic features of two promiscuous hydrolases

While there has been emerging interest in designing new enzymes to solve practical challenges, computer-based options to redesign catalytically active proteins are rather limited. Here, a rational QM/MM molecular dynamics strategy based on combining the best electrostatic properties of enzymes with activity in a common reaction is presented. The computational protocol has been applied to the re-design of the protein scaffold of an existing promiscuous esterase from Bacillus subtilis Bs2 to enhance its secondary amidase activity. After the alignment of Bs2 with a non-homologous amidase Candida antarctica lipase B (CALB) within rotation quaternions, a relevant spatial aspartate residue of the latter was transferred to the former as a means to favor the electrostatics of transition state formation, where a clear separation of charges takes place. Deep computational insights, however, revealed a significant conformational change caused by the amino acid replacement, provoking a shift in the pK a of the inserted aspartate and counteracting the anticipated catalytic effect. This prediction was experimentally confirmed with a 1.3-fold increase in activity. The good agreement between theoretical and experimental results, as well as the linear correlation between the electrostatic properties and the activation energy barriers, suggest that the presented computational-based investigation can transform in an enzyme engineering approach.