Protein engineering approaches for antibody fragments: directed evolution and rational design approaches

Background α-amylases catalyze the endo-hydrolysis of α-1,4-D-glycosidic bonds in starch into smaller moieties. While industrial processes are usually performed at harsh conditions, α-amylases from mainly the bacteria, fungi and yeasts are preferred for their stabilities (thermal, pH and oxidative) and specificities (substrate and product). Microbial α-amylases can be purified and characterized for industrial applications. While exploring novel enzymes with these properties in the nature is time-costly, the advancements in protein engineering techniques including rational design, directed evolution and others have privileged their modifications to exhibit industrially ideal traits. However, the commentary on the strategies and preferably mutated residues are lacking, hindering the design of new mutants especially for enhanced substrate specificity and oxidative stability. Thus, our review ensures wider accessibility of the previously reported experimental findings to facilitate the future engineering work. Survey methodology and objectives A traditional review approach was taken to focus on the engineering of microbial α-amylases to enhance industrially favoured characteristics. The action mechanisms of α- and β-amylases were compared to avoid any bias in the research background. This review aimed to discuss the advances in modifying microbial α-amylases via protein engineering to achieve longer half-life in high temperature, improved resistance (acidic, alkaline and oxidative) and enhanced specificities (substrate and product). Captivating results were discussed in depth, including the extended half-life at 100 °C, pH 3.5 and 10, 1.8 M hydrogen peroxide as well as enhanced substrate (65.3%) and product (42.4%) specificities. These shed light to the future microbial α-amylase engineering in achieving paramount biochemical traits ameliorations to apt in the industries. Conclusions Microbial α-amylases can be tailored for specific industrial applications through protein engineering (rational design and directed evolution). While the critical mutation points are dependent on respective enzymes, formation of disulfide bridge between cysteine residues after mutations is crucial for elevated thermostability. Amino acids conversion to basic residues was reported for enhanced acidic resistance while hydrophobic interaction resulted from mutated hydrophobic residues in carbohydrate-binding module or surface-binding sites is pivotal for improved substrate specificity. Substitution of oxidation-prone methionine residues with non-polar residues increases the enzyme oxidative stability. Hence, this review provides conceptual advances for the future microbial α-amylases designs to exhibit industrially significant characteristics. However, more attention is needed to enhance substrate specificity and oxidative stability since they are least reported.

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Rational Design Protein Engineering Through Crowdsourcing

Journal of Student Research ◽

10.47611/jsr.v6i2.377 ◽

2018 ◽

Vol 6 (2) ◽

pp. 31-38

Author(s):

Tylar Seiya Farmer ◽

Patrick Bohse ◽

Dianne Kerr

Keyword(s):

Genetic Engineering ◽

Protein Engineering ◽

Directed Evolution ◽

Rational Design ◽

Ethical Issues ◽

Living System ◽

Computational Power ◽

Induced Mutations ◽

Computer Based ◽

Protein Models

Two popular methods exist to engineer a protein: directed evolution and rational design. Directed evolution utilizes a controlled environment to create proteins through induced mutations and selection, while rational design makes desired changes to a protein by directly manipulating its amino acids. Directed evolution is currently more commonly used, since rational design relies on structural knowledge of the protein of interest, which is often unavailable. Utilizing crowdsourcing manpower and computational power to improve protein depictions allows rational design to be more easily used to perform the manipulation of proteins. Two free programs, “Folding@home and “Foldit”, allow anyone with a computer and internet access to contribute to protein engineering. Folding@home relies on one’s computational power, while Foldit relies on user intuition to improve protein models. Rational design has allowed protein engineers to create artificial proteins that can be applied to the treatment of illnesses, research of enzyme activity in a living system, genetic engineering, and biological warfare. Starting with an overview of protein engineering, this paper discusses the methods of rational design and directed evolutions and goes on to explain how computer based programs can help in the advancement of rational design as a protein engineering method. Furthermore, this paper discusses the application of computer based programs in medicine and genetic engineering and presents some ethical issues that may arise from using such technology. The paper concludes with an analysis of whether or not computer based programs for protein engineering is worth the investment.

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Evolutionary context-integrated deep sequence modeling for protein engineering

10.1101/2020.01.16.908509 ◽

2020 ◽

Cited By ~ 3

Author(s):

Yunan Luo ◽

Lam Vo ◽

Hantian Ding ◽

Yufeng Su ◽

Yang Liu ◽

...

Keyword(s):

Machine Learning ◽

Protein Engineering ◽

Directed Evolution ◽

Rational Design ◽

Generative Models ◽

Language Models ◽

Functional Fitness ◽

General Sequence ◽

Sequence Modeling ◽

Evolutionary Context

AbstractProtein engineering seeks to design proteins with improved or novel functions. Compared to rational design and directed evolution approaches, machine learning-guided approaches traverse the fitness landscape more effectively and hold the promise for accelerating engineering and reducing the experimental cost and effort. A critical challenge here is whether we are capable of predicting the function or fitness of unseen protein variants. By learning from the sequence and large-scale screening data of characterized variants, machine learning models predict functional fitness of sequences and prioritize new variants that are very likely to demonstrate enhanced functional properties, thereby guiding and accelerating rational design and directed evolution. While existing generative models and language models have been developed to predict the effects of mutation and assist protein engineering, the accuracy of these models is limited due to their unsupervised nature of the general sequence contexts they captured that is not specific to the protein being engineered. In this work, we propose ECNet, a deep-learning algorithm to exploit evolutionary contexts to predict functional fitness for protein engineering. Our method integrated local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest, as well as the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. This biologically motivated sequence modeling approach enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-orders. Through extensive benchmark experiments, we showed that our method outperforms existing methods on ∼50 deep mutagenesis scanning and random mutagenesis datasets, demonstrating its potential of guiding and expediting protein engineering.

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Protein Engineering Approaches to Enhance Fungal Laccase Production in S. cerevisiae

International Journal of Molecular Sciences ◽

10.3390/ijms22031157 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1157

Author(s):

Pablo Aza ◽

Felipe de Salas ◽

Gonzalo Molpeceres ◽

David Rodríguez-Escribano ◽

Iñigo de la Fuente ◽

...

Keyword(s):

Protein Engineering ◽

Directed Evolution ◽

Signal Peptide ◽

Laccase Activity ◽

Laccase Production ◽

Wide Range ◽

Mating Factor ◽

Conserved Amino Acids ◽

Basidiomycete Fungi

Laccases secreted by saprotrophic basidiomycete fungi are versatile biocatalysts able to oxidize a wide range of aromatic compounds using oxygen as the sole requirement. Saccharomyces cerevisiae is a preferred host for engineering fungal laccases. To assist the difficult secretion of active enzymes by yeast, the native signal peptide is usually replaced by the preproleader of S. cerevisiae alfa mating factor (MFα1). However, in most cases, only basal enzyme levels are obtained. During directed evolution in S. cerevisiae of laccases fused to the α-factor preproleader, we demonstrated that mutations accumulated in the signal peptide notably raised enzyme secretion. Here we describe different protein engineering approaches carried out to enhance the laccase activity detected in the liquid extracts of S. cerevisiae cultures. We demonstrate the improved secretion of native and engineered laccases by using the fittest mutated α-factor preproleader obtained through successive laccase evolution campaigns in our lab. Special attention is also paid to the role of protein N-glycosylation in laccase production and properties, and to the introduction of conserved amino acids through consensus design enabling the expression of certain laccases otherwise not produced by the yeast. Finally, we revise the contribution of mutations accumulated in laccase coding sequence (CDS) during previous directed evolution campaigns that facilitate enzyme production.

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Continuous directed evolution for strain and protein engineering

Current Opinion in Biotechnology ◽

10.1016/j.copbio.2017.12.020 ◽

2018 ◽

Vol 53 ◽

pp. 158-163 ◽

Cited By ~ 9

Author(s):

Simon d’Oelsnitz ◽

Andrew Ellington

Keyword(s):

Protein Engineering ◽

Directed Evolution

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Genetically Engineered Proteins to Improve Biomass Conversion: New Advances and Challenges for Tailoring Biocatalysts

Molecules ◽

10.3390/molecules24162879 ◽

2019 ◽

Vol 24 (16) ◽

pp. 2879 ◽

Cited By ~ 4

Author(s):

Lucas Ferreira Ribeiro ◽

Vanesa Amarelle ◽

Luana de Fátima Alves ◽

Guilherme Marcelino Viana de Siqueira ◽

Gabriel Lencioni Lovate ◽

...

Keyword(s):

Protein Engineering ◽

Rational Design ◽

Biomass Conversion ◽

Low Cost ◽

Catalytic Performance ◽

Genetically Engineered ◽

Production Lines ◽

Current Application ◽

Powerful Approach

Protein engineering emerged as a powerful approach to generate more robust and efficient biocatalysts for bio-based economy applications, an alternative to ecologically toxic chemistries that rely on petroleum. On the quest for environmentally friendly technologies, sustainable and low-cost resources such as lignocellulosic plant-derived biomass are being used for the production of biofuels and fine chemicals. Since most of the enzymes used in the biorefinery industry act in suboptimal conditions, modification of their catalytic properties through protein rational design and in vitro evolution techniques allows the improvement of enzymatic parameters such as specificity, activity, efficiency, secretability, and stability, leading to better yields in the production lines. This review focuses on the current application of protein engineering techniques for improving the catalytic performance of enzymes used to break down lignocellulosic polymers. We discuss the use of both classical and modern methods reported in the literature in the last five years that allowed the boosting of biocatalysts for biomass degradation.

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Rational design of a function-based selection method for genetically encoding acylated lysine derivatives

Organic & Biomolecular Chemistry ◽

10.1039/c9ob00992b ◽

2019 ◽

Vol 17 (25) ◽

pp. 6127-6130

Author(s):

Hui Miao ◽

Chenguang Yu ◽

Anzhi Yao ◽

Weimin Xuan

Keyword(s):

Amino Acids ◽

Genetic Code ◽

Directed Evolution ◽

Rational Design ◽

Selection Method ◽

Genetic Code Expansion

Genetic code expansion depends on the directed evolution of aaRS to recognize non-canonical amino acids. Herein, we reported a function-based method that enables rapidly evolving aaRS for acylated lysine derivatives.

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Engineering Improves Enzymatic Synthesis of L-Tryptophan by Tryptophan Synthase from Escherichia coli

Microorganisms ◽

10.3390/microorganisms8040519 ◽

2020 ◽

Vol 8 (4) ◽

pp. 519

Author(s):

Lisheng Xu ◽

Fangkai Han ◽

Zeng Dong ◽

Zhaojun Wei

Keyword(s):

Thermal Stability ◽

Amino Acid ◽

Directed Evolution ◽

Amino Acid Residue ◽

Rational Design ◽

Molecular Engineering ◽

Mutant Enzyme ◽

Tryptophan Synthase ◽

Mutant Library ◽

Thermal Stability Of

To improve the thermostability of tryptophan synthase, the molecular modification of tryptophan synthase was carried out by rational molecular engineering. First, B-FITTER software was used to analyze the temperature factor (B-factor) of each amino acid residue in the crystal structure of tryptophan synthase. A key amino acid residue, G395, which adversely affected the thermal stability of the enzyme, was identified, and then, a mutant library was constructed by site-specific saturation mutation. A mutant (G395S) enzyme with significantly improved thermal stability was screened from the saturated mutant library. Error-prone PCR was used to conduct a directed evolution of the mutant enzyme (G395S). Compared with the parent, the mutant enzyme (G395S /A191T) had a Km of 0.21 mM and a catalytic efficiency kcat/Km of 5.38 mM−1∙s−1, which was 4.8 times higher than that of the wild-type strain. The conditions for L-tryptophan synthesis by the mutated enzyme were a L-serine concentration of 50 mmol/L, a reaction temperature of 40 °C, pH of 8, a reaction time of 12 h, and an L-tryptophan yield of 81%. The thermal stability of the enzyme can be improved by using an appropriate rational design strategy to modify the correct site. The catalytic activity of tryptophan synthase was increased by directed evolution.

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