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Deletion and Randomization of Structurally Variable Regions in B. subtilis Lipase A (BSLA) Alter Its Stability and Hydrolytic Performance Against Long Chain Fatty Acid Esters.
Martínez, R, Bernal, C, Álvarez, R, Concha, C, Araya, F, Cabrera, R, Dhoke, GV, Davari, MD
International journal of molecular sciences. 2020;(6)
Abstract
The continuous search for novel enzyme backbones and the engineering of already well studied enzymes for biotechnological applications has become an increasing challenge, especially by the increasing potential diversity space provided by directed enzyme evolution approaches and the demands of experimental data generated by rational design of enzymes. In this work, we propose a semi-rational mutational strategy focused on introducing diversity in structurally variable regions in enzymes. The identified sequences are subjected to a progressive deletion of two amino acids and the joining residues are subjected to saturation mutagenesis using NNK degenerate codons. This strategy offers a novel library diversity approach while simultaneously decreasing enzyme size in the variable regions. In this way, we intend to identify and reduce variable regions found in enzymes, probably resulting from neutral drift evolution, and simultaneously studying the functional effect of said regions. This strategy was applied to Bacillus. subtilis lipase A (BSLA), by selecting and deleting six variable enzyme regions (named regions 1 to 6) by the deletion of two amino acids and additionally randomizing the joining amino acid residues. After screening, no active variants were found in libraries 1% and 4%, 15% active variants were found in libraries 2% and 3%, and 25% for libraries 5 and 6 (n = 3000 per library, activity detected using tributyrin agar plates). Active variants were assessed for activity in microtiter plate assay (pNP-butyrate), thermal stability, substrate preference (pNP-butyrate, -palmitate), and compared to wildtype BSLA. From these analyses, variant P5F3 (F41L-ΔW42-ΔD43-K44P), from library 3 was identified, showing increased activity towards longer chain p-nitrophenyl fatty acid esters, when compared to BSLA. This study allowed to propose the targeted region 3 (positions 40-46) as a potential modulator for substrate specificity (fatty acid chain length) in BSLA, which can be further studied to increase its substrate spectrum and selectivity. Additionally, this variant showed a decreased thermal resistance but interestingly, higher isopropanol and Triton X-100 resistance. This deletion-randomization strategy could help to expand and explore sequence diversity, even in already well studied and characterized enzyme backbones such as BSLA. In addition, this strategy can contribute to investigate and identify important non-conserved regions in classic and novel enzymes, as well as generating novel biocatalysts with increased performance in specific processes, such as enzyme immobilization.
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2.
Increasing the chemical space of proteins in living cells via genetic code expansion.
Krauskopf, K, Lang, K
Current opinion in chemical biology. 2020;:112-120
Abstract
In recent years it has become possible to genetically encode an expanded set of designer amino acids with tailored chemical and physical properties (dubbed unnatural amino acids, UAAs) into proteins in living cells by expanding the genetic code. Together with developments in chemistries that are amenable to and selective within physiological settings, these strategies have started to have a big impact on biological studies, as they enable exciting in cellulo applications. Here we highlight recent advances to covalently stabilize transient protein-protein interactions and capture enzyme substrate-complexes in living cells using proximity-triggered and residue-selective photo-induced crosslinking approaches. Furthermore, we describe recent efforts in controlling enzyme activity with photocaged UAAs and in extending their application to a variety of enzymatic scaffolds. In addition, we discuss the site-specific incorporation of UAAs mimicking post-translational modifications (PTMs) and approaches to generate natively-linked ubiquitin-protein conjugates to probe the role of PTMs in modulating complex cellular networks.
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3.
Reprogramming extracellular vesicles with engineered proteins.
Shi, X, Cheng, Q, Zhang, Y
Methods (San Diego, Calif.). 2020;:95-102
Abstract
Extracellular vesicles (EVs) have been emerging as a new class of cell-free therapy for the treatment of a variety of diseases, including cancer, tissue injuries, and inflammatory diseases. Reprograming native EVs by genetic engineering and other approaches offers an attractive prospect of extending therapeutic capabilities of EVs beyond their natural functions and properties. In this review article, we survey the state-of-the-art methods of EVs engineering and summarize major therapeutic applications of the reprogrammed EVs.
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4.
Creating Flavin Reductase Variants with Thermostable and Solvent-Tolerant Properties by Rational-Design Engineering.
Maenpuen, S, Pongsupasa, V, Pensook, W, Anuwan, P, Kraivisitkul, N, Pinthong, C, Phonbuppha, J, Luanloet, T, Wijma, HJ, Fraaije, MW, et al
Chembiochem : a European journal of chemical biology. 2020;(10):1481-1491
Abstract
We have employed computational approaches-FireProt and FRESCO-to predict thermostable variants of the reductase component (C1 ) of (4-hydroxyphenyl)acetate 3-hydroxylase. With the additional aid of experimental results, two C1 variants, A166L and A58P, were identified as thermotolerant enzymes, with thermostability improvements of 2.6-5.6 °C and increased catalytic efficiency of 2- to 3.5-fold. After heat treatment at 45 °C, both of the thermostable C1 variants remain active and generate reduced flavin mononucleotide (FMNH- ) for reactions catalyzed by bacterial luciferase and by the monooxygenase C2 more efficiently than the wild type (WT). In addition to thermotolerance, the A166L and A58P variants also exhibited solvent tolerance. Molecular dynamics (MD) simulations (6 ns) at 300-500 K indicated that mutation of A166 to L and of A58 to P resulted in structural changes with increased stabilization of hydrophobic interactions, and thus in improved thermostability. Our findings demonstrated that improvements in the thermostability of C1 enzyme can lead to broad-spectrum uses of C1 as a redox biocatalyst for future industrial applications.
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5.
Escherichia coli Extract-Based Cell-Free Expression System as an Alternative for Difficult-to-Obtain Protein Biosynthesis.
Smolskaya, S, Logashina, YA, Andreev, YA
International journal of molecular sciences. 2020;(3)
Abstract
Before utilization in biomedical diagnosis, therapeutic treatment, and biotechnology, the diverse variety of peptides and proteins must be preliminarily purified and thoroughly characterized. The recombinant DNA technology and heterologous protein expression have helped simplify the isolation of targeted polypeptides at high purity and their structure-function examinations. Recombinant protein expression in Escherichia coli, the most-established heterologous host organism, has been widely used to produce proteins of commercial and fundamental research interests. Nonetheless, many peptides/proteins are still difficult to express due to their ability to slow down cell growth or disrupt cellular metabolism. Besides, special modifications are often required for proper folding and activity of targeted proteins. The cell-free (CF) or in vitro recombinant protein synthesis system enables the production of such difficult-to-obtain molecules since it is possible to adjust reaction medium and there is no need to support cellular metabolism and viability. Here, we describe E. coli-based CF systems, the optimization steps done toward the development of highly productive and cost-effective CF methodology, and the modification of an in vitro approach required for difficult-to-obtain protein production.
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6.
Structure-based enzyme engineering improves donor-substrate recognition of Arabidopsis thaliana glycosyltransferases.
Akere, A, Chen, SH, Liu, X, Chen, Y, Dantu, SC, Pandini, A, Bhowmik, D, Haider, S
The Biochemical journal. 2020;(15):2791-2805
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Abstract
Glycosylation of secondary metabolites involves plant UDP-dependent glycosyltransferases (UGTs). UGTs have shown promise as catalysts in the synthesis of glycosides for medical treatment. However, limited understanding at the molecular level due to insufficient biochemical and structural information has hindered potential applications of most of these UGTs. In the absence of experimental crystal structures, we employed advanced molecular modeling and simulations in conjunction with biochemical characterization to design a workflow to study five Group H Arabidopsis thaliana (76E1, 76E2, 76E4, 76E5, 76D1) UGTs. Based on our rational structural manipulation and analysis, we identified key amino acids (P129 in 76D1; D374 in 76E2; K275 in 76E4), which when mutated improved donor substrate recognition than wildtype UGTs. Molecular dynamics simulations and deep learning analysis identified structural differences, which drive substrate preferences. The design of these UGTs with broader substrate specificity may play important role in biotechnological and industrial applications. These findings can also serve as basis to study other plant UGTs and thereby advancing UGT enzyme engineering.
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7.
Adaptive landscape flattening allows the design of both enzyme: Substrate binding and catalytic power.
Opuu, V, Nigro, G, Gaillard, T, Schmitt, E, Mechulam, Y, Simonson, T
PLoS computational biology. 2020;(1):e1007600
Abstract
Designed enzymes are of fundamental and technological interest. Experimental directed evolution still has significant limitations, and computational approaches are a complementary route. A designed enzyme should satisfy multiple criteria: stability, substrate binding, transition state binding. Such multi-objective design is computationally challenging. Two recent studies used adaptive importance sampling Monte Carlo to redesign proteins for ligand binding. By first flattening the energy landscape of the apo protein, they obtained positive design for the bound state and negative design for the unbound. We have now extended the method to design an enzyme for specific transition state binding, i.e., for its catalytic power. We considered methionyl-tRNA synthetase (MetRS), which attaches methionine (Met) to its cognate tRNA, establishing codon identity. Previously, MetRS and other synthetases have been redesigned by experimental directed evolution to accept noncanonical amino acids as substrates, leading to genetic code expansion. Here, we have redesigned MetRS computationally to bind several ligands: the Met analog azidonorleucine, methionyl-adenylate (MetAMP), and the activated ligands that form the transition state for MetAMP production. Enzyme mutants known to have azidonorleucine activity were recovered by the design calculations, and 17 mutants predicted to bind MetAMP were characterized experimentally and all found to be active. Mutants predicted to have low activation free energies for MetAMP production were found to be active and the predicted reaction rates agreed well with the experimental values. We suggest the present method should become the paradigm for computational enzyme design.
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8.
Modular repeat protein sculpting using rigid helical junctions.
Brunette, TJ, Bick, MJ, Hansen, JM, Chow, CM, Kollman, JM, Baker, D
Proceedings of the National Academy of Sciences of the United States of America. 2020;(16):8870-8875
Abstract
The ability to precisely design large proteins with diverse shapes would enable applications ranging from the design of protein binders that wrap around their target to the positioning of multiple functional sites in specified orientations. We describe a protein backbone design method for generating a wide range of rigid fusions between helix-containing proteins and use it to design 75,000 structurally unique junctions between monomeric and homo-oligomeric de novo designed and ankyrin repeat proteins (RPs). Of the junction designs that were experimentally characterized, 82% have circular dichroism and solution small-angle X-ray scattering profiles consistent with the design models and are stable at 95 °C. Crystal structures of four designed junctions were in close agreement with the design models with rmsds ranging from 0.9 to 1.6 Å. Electron microscopic images of extended tetrameric structures and ∼10-nm-diameter "L" and "V" shapes generated using the junctions are close to the design models, demonstrating the control the rigid junctions provide for protein shape sculpting over multiple nanometer length scales.
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9.
Practically useful protein-design methods combining phylogenetic and atomistic calculations.
Weinstein, J, Khersonsky, O, Fleishman, SJ
Current opinion in structural biology. 2020;:58-64
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Abstract
Our ability to design new or improved biomolecular activities depends on understanding the sequence-function relationships in proteins. The large size and fold complexity of most proteins, however, obscure these relationships, and protein-optimization methods continue to rely on laborious experimental iterations. Recently, a deeper understanding of the roles of stability-threshold effects and biomolecular epistasis in proteins has led to the development of hybrid methods that combine phylogenetic analysis with atomistic design calculations. These methods enable reliable and even single-step optimization of protein stability, expressibility, and activity in proteins that were considered outside the scope of computational design. Furthermore, ancestral-sequence reconstruction produces insights on missing links in the evolution of enzymes and binders that may be used in protein design. Through the combination of phylogenetic and atomistic calculations, the long-standing goal of general computational methods that can be universally applied to study and optimize proteins finally seems within reach.
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Engineering Plant Cytochrome P450s for Enhanced Synthesis of Natural Products: Past Achievements and Future Perspectives.
Shang, Y, Huang, S
Plant communications. 2020;(1):100012
Abstract
Cytochrome P450s (P450s) are the most versatile catalysts and are widely used by plants to synthesize a vast array of structurally diverse specialized metabolites that not only play essential ecological roles but also constitute a valuable resource for the development of new drugs. To accelerate the metabolic engineering of these high-value metabolites, it is imperative to identify and characterize pathway P450s, and to further improve their activities through protein engineering. In this review, we focus on P450 engineering and summarize the major strategies for enhancing the stability and activity of P450s and successful cases of P450 engineering. Studies in which the functions of P450s were altered to create de novo metabolic pathways or novel compounds are discussed as well. We also overview emerging tools, specifically DNA synthesis, machine learning, and de novo protein design, as well as the evolutionary patterns of P450s unveiled from a massive number of DNA sequences that could be integrated to accelerate the engineering of these enzymes. These approaches would greatly aid in the exploitation of plant-specialized metabolites or derivatives for various uses including medical applications.