Insights into Laccase Engineering from Molecular Simulations: Toward a Binding-Focused Strategy

Monza, Emanuele; Lucas, Fátima; Camarero, Susana; Alejaldre, Lorea; Martínez, Ángel T.; Guallar, Vı́ctor

doi:10.1021/acs.jpclett.5b00225

Cited by 58 publications

(74 citation statements)

References 63 publications

(114 reference statements)

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“…Protein-substrate binding modes. To determine the different binding modes of substrates in the T1 copper site, PELE 9a, 38 simulations were performed following the protocol, described in detail in Monza et al 8 . Since the ligand's binding site in laccases is well known, each substrate was manually placed close to the entrance of the copper site and was then free to move in a region 20 Å within the T1 copper atom.…”

Section: Methodsmentioning

confidence: 99%

Computer-Aided Laccase Engineering: Toward Biological Oxidation of Arylamines

et al. 2016

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ABSTRACT:Oxidation of arylamines, such as aniline, is of high industrial interest and laccases have been proposed as biocatalysts to replace harsh chemical oxidants. However, the reaction is hampered by the redox potential of the substrate at acid pH and enzyme engineering is required to improve the oxidation. In this work, instead of trying to improve the redox potential of the enzyme, we aim towards the (transient) substrate's one and propose this as a more reliable strategy. We have successfully combined a computational approach with experimental validation to rationally design an improved biocatalyst. The in silico protocol combines classical and quantum mechanics to deliver atomic and electronic level detail on the two main processes involved: substrate binding and electron transfer. After mutant expression and comparison to the parent type, kinetic results show that the protocol accurately predicts aniline's improved oxidation (2-fold k cat increase) in the engineered variant for biocatalyzed polyaniline production.

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Section: Methodsmentioning

confidence: 99%

Computer-Aided Laccase Engineering: Toward Biological Oxidation of Arylamines

et al. 2016

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“…Although accurate QM/MM methodologies have been developed to study electron transfer rate in proteins [192,193], their use in enzyme design is limited by their computational cost. To overcome this barrier, we have recently developed a new methodology to approximately evaluate ET rates, which combines fast conformational sampling [163] and quick QM/MM spin density calculations and has been used to evaluate the activity of laccases variants [194,154]. While PELE provides a thorough and quick mapping of enzyme's and substrate's dynamics, substrate's spin density permits to promptly score the relative changes in driving force upon mutation (the higher the spin density, in principle, the higher the driving force).…”

Section: Catalytic Rate Constant Enhancementmentioning

confidence: 99%

“…Due to their very high cost (hours to days), future work will have to center in designing cheaper methods [200][201][202] and/or property evaluations. For example, in our current efforts in oxidoreductases's engineering the driving force is approximated with the amount of spin density, calculated after five steps of QM/MM geometry optimization, localized on the substrate (with respect to the wild type) [194].…”

Section: Fig 3 Proposed Computer-aided Directed Evolution Workflowmentioning

confidence: 99%

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Monza

Acebes

Lucas

et al. 2017

Directed Enzyme Evolution: Advances and Applications

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Directed evolution creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-50413-1_10/fulltext.html of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of art of molecular modeling, discussing their strengths, limitations and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques, and a synergic effort between simulations and experimental validation. IntroductionBiotechnology needs catalysts that can work under harsh conditions, catalyze a broad range of substrates, generate maximum amount of product, and tolerate changes in the environment. Enzymes, which are biodegradable and reusable catalysts [1], in addition to remarkable reaction rates, can work in environmentally friendly pH and temperature ranges, and display control over stereochemistry and regioselectivity which makes them ideal for many applications [2,3]. When thinking about enzymes, people normally associate them to expressions such as "perfect catalysts" or "outstanding reaction rate". In fact, there are examples of enzymes that catalyze reactions at extremely high rates such as triose phosphate isomerase, superoxide dismutase or carbonic anhydrase [4]. These are often limited only by the rate of ligand diffusion into the active site (diffusion-controlled rate). Nevertheless, an extensive analysis by Bar-Even et al., of nearly 2000 enzymes, showed that the median maximal turnover rate value over all measured enzymes is about 10 s −1 nowhere close to the values of 10 5 or 10 6 normally associated with catalysts [5,6].So, it would appear that natural enzymes are "just good enough" for the function they must perform in a given organism [7]. One might conclude that if they had evolved to their optimum performance then trying to improve them (from a kinetic point of view) would be attempting the impossible. On the contrary, as seen by the distribution of reaction rates, k cat , most enzymes function at a lower rate than the diffusion-limit and thus, there is space to further increase their kinetic properties to meet industrial needs. Additionally, we need enzymes capable of catalyzing reactions for which no known enzymes exist, to work with different substrates and for particular conditions that are industrially...

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“…1, [4][5][6] Such a broad range of applications has led to numerous engineering efforts, 7 including computer-aided strategies, 8,9 aiming at enhancing their activity and/or stability for industrial application. As for specificity, laccases are very promiscuous enzymes, most likely as a consequence of a superficial, shallow binding site which cannot guarantee the optimal positioning for ET for all the putative substrates.…”

Section: Introductionmentioning

confidence: 99%

“…Computational techniques are very promising as they provide an atomistic mapping of both substrate binding and oxidation. [8][9][10] In this work, a computational evolution protocol is applied to render the oxidation of 2,4-diamino-benzenesulfonic acid (2,4-dabsa) by POXA1b, a fungal (Pleurotus ostreatus) laccase with an unusually high stability at alkaline pH, 11 possible. The substrate of interest, 2,4-dabsa, is a dye precursor just like its constitutional isomer, 2,5-dabsa (Scheme 1).…”

Section: Introductionmentioning

confidence: 99%

Repurposing designed mutants: a valuable strategy for computer-aided laccase engineering – the case of POXA1b

Giacobelli

Monza

Lucas

et al. 2017

Catal. Sci. Technol.

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The Q3broad specificity of laccases, a direct consequence of their shallow binding site, makes this class of enzymes a suitable template to build specificity toward putative substrates.Please check this proof carefully. Our staff will not read it in detail after you have returned it.Translation errors between word-processor files and typesetting systems can occur so the whole proof needs to be read. Please pay particular attention to: tabulated material; equations; numerical data; figures and graphics; and references. If you have not already indicated the corresponding author(s) please mark their name(s) with an asterisk. Please e-mail a list of corrections or the PDF with electronic notes attached -do not change the text within the PDF file or send a revised manuscript. Corrections at this stage should be minor and not involve extensive changes. All corrections must be sent at the same time.Please bear in mind that minor layout improvements, e.g. in line breaking, table widths and graphic placement, are routinely applied to the final version.Please note that, in the typefaces we use, an italic vee looks like this: n, and a Greek nu looks like this: ν.We will publish articles on the web as soon as possible after receiving your corrections; no late corrections will be made.Please return your final corrections, where possible within 48 hours of receipt, by e-mail to: catalysis@rsc.org Queries for the attention of the authors The broad specificity of laccases, a direct consequence of their shallow binding site, makes this class of enzymes a suitable template to build specificity toward putative substrates. In this work, a computational methodology that accumulates beneficial interactions between the enzyme and the substrate in productive conformations is applied to oxidize 2,4-diamino-benzenesulfonic acid with POXA1b laccase. Although the experimental validation of two designed variants yielded negative results, most likely due to the hard oxidizability of the target substrate, molecular simulations suggest that a novel polar binding scaffold was designed to anchor negatively charged groups. Consequently, the oxidation of three such molecules, selected as representative of different classes of substances with different industrial applications, significantly improved. According to molecular simulations, the reason behind such an improvement lies in the more productive enzyme-substrate binding achieved thanks to the designed polar scaffold. In the future, mutant repurposing toward other substrates could be first carried out computationally, as done here, testing molecules that share some similarity with the initial target. In this way, repurposing would not be a mere safety net (as it is in the laboratory and as it was here) but rather a powerful approach to transform laccases into more efficient multitasking enzymes.

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Insights into Laccase Engineering from Molecular Simulations: Toward a Binding-Focused Strategy

Cited by 58 publications

References 63 publications

Computer-Aided Laccase Engineering: Toward Biological Oxidation of Arylamines

Computer-Aided Laccase Engineering: Toward Biological Oxidation of Arylamines

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Repurposing designed mutants: a valuable strategy for computer-aided laccase engineering – the case of POXA1b

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