Rational and Semirational Protein Design

New advances in protein engineering for industrial applications: Key takeaways

Recent advancements in protein/enzyme engineering have enabled the production of a diverse array of high-value compounds in microbial systems with the potential for industrial applications. The goal of this review is to articulate some of the most recent protein engineering advances in bacteria, yeast, and other microbial systems to produce valuable substances. These high-value substances include α-farnesene, vitamin B12, fumaric acid, linalool, glucaric acid, carminic acid, mycosporine-like amino acids, patchoulol, orcinol glucoside, d-lactic acid, keratinase, α-glucanotransferases, β-glucosidase, seleno-methylselenocysteine, fatty acids, high-efficiency β-glucosidase enzymes, cellulase, β-carotene, physcion, and glucoamylase. Additionally, recent advances in enzyme engineering for enhancing thermostability will be discussed. These findings have the potential to revolutionize various industries, including biotechnology, food, pharmaceuticals, and biofuels.

AbMelt: Learning antibody thermostability from molecular dynamics

Antibody thermostability is challenging to predict from sequence and/or structure. This difficulty is likely due to the absence of direct entropic information. Herein, we present AbMelt where we model the inherent flexibility of homologous antibody structures using molecular dynamics simulations at three temperatures and learn the relevant descriptors to predict the temperatures of aggregation (Tagg), melt onset (Tm,on), and melt (Tm). We observed that the radius of gyration deviation of the complementarity determining regions at 400 K is the highest Pearson correlated descriptor with aggregation temperature (rp = -0.68 ± 0.23) and the deviation of internal molecular contacts at 350 K is the highest correlated descriptor with both Tm,on (rp = -0.74 ± 0.04) as well as Tm (rp = -0.69 ± 0.03). Moreover, after descriptor selection and machine learning regression, we predict on a held-out test set containing both internal and public data and achieve robust performance for all endpoints compared with baseline models (Tagg R2 = 0.57 ± 0.11, Tm,on R2 = 0.56 ± 0.01, and Tm R2 = 0.60 ± 0.06). In addition, the robustness of the AbMelt molecular dynamics methodology is demonstrated by only training on <5% of the data and outperforming more traditional machine learning models trained on the entire data set of more than 500 internal antibodies. Users can predict thermostability measurements for antibody variable fragments by collecting descriptors and using AbMelt, which has been made available.

Molecular modification and biotechnological applications of microbial aspartic proteases

The growing preference for incorporating microbial aspartic proteases in industries is due to their high catalytic function and high degree of substrate selectivity. These properties, however, are attributable to molecular alterations in their structure and a variety of other characteristics. Molecular tools, functional genomics, and genome editing technologies coupled with other biotechnological approaches have aided in improving the potential of industrially important microbial proteases by addressing some of their major limitations, such as: low catalytic efficiency, low conversion rates, low thermostability, and less enzyme yield. However, the native folding within their full domain is dependent on a surrounding structure which challenges their functionality in substrate conversion, mainly due to their mutual interactions in the context of complex systems. Hence, manipulating their structure and controlling their expression systems could potentially produce enzymes with high selectivity and catalytic functions. The proteins produced by microbial aspartic proteases are industrially capable and far-reaching in regulating certain harmful distinctive industrial processes and the benefits of being eco-friendly. This review provides: an update on current trends and gaps in microbial protease biotechnology, exploring the relevant recombinant strategies and molecular technologies widely used in expression platforms for engineering microbial aspartic proteases, as well as their potential industrial and biotechnological applications.

Structure-Guided Evolution Modulate Alcohol Oxidase to Improve Ethanol Oxidation Performance

A high ethanol usage of alcohol oxidase (AOX) was required in industry. In this study, a "expand substrate pocket" strategy achieved a high activity AOX from Hansenula polymorpha (H. polymorpha) by Phe to Val residue (F/V) site-directed mutation to enlarge ethanol channel. Although H. Polymorpha AOX (HpAOX) possessed respectively 71.3% and 76.1% similarity with AOX (PpAOX) from Pichia pastoris (P. pastoris) in DNA and protein sequences, their active site structures including catalytic site and substrate channel were similar according to computer-aided analysis. After 3D structure analysis, Phe99 residue of their substrate channels was the most important residue to impact enzyme activity because of its large aromatic side chains. F99V mutation of HpAOX (HpAOXF99V) was designed and executed based on the enzyme catalytic mechanism and molecular computation in order to allow more larger size ethanol into active site. The highest enzyme activity of the fourth strains of HpAOXF99V mutant strain exhibited 12.06-folds increase than that of the host GS115 strain. Furthermore, kinetic studies indicated that the HpAOXF99V significantly promoted catalytic efficiency of ethanol than HpAOX, including Km, Vmax, kcat and kcat/Km. We also provided a new insight that the cofactor FAD irritated both active AOX octamer biosynthesis production and enzyme-catalysed ability due to help enzyme assembly and redox potential.

Rational peptide design for targeting cancer cell invasion

Cell invasion is an important process in cancer progression and recurrence. Invasion and implantation of cancer cells from their original place to other tissues, by disabling vital organs, challenges the treatment of cancer patients. Given the importance of the matter, many molecular treatments have been developed to inhibit cancer cell invasion. Because of their low production cost and ease of production, peptides are valuable therapeutic molecules for inhibiting cancer cell invasion. In recent years, advances in the field of computational biology have facilitated the design of anti-cancer peptides. In our investigation, using computational biology approaches such as evolutionary analysis, residue scanning, protein-peptide interaction analysis, molecular dynamics, and free energy analysis, our team designed a peptide library with about 100 000 candidates based on A6 (acetyl-KPSSPPEE-amino) sequence which is an anti-invasion peptide. During computational studies, two of the designed peptides that give the highest scores and showed the greatest sequence similarity to A6 were entered into the experimental analysis workflow for further analysis. In experimental analysis steps, the anti-metastatic potency and other therapeutic effects of designed peptides were evaluated using MTT assay, RT-qPCR, zymography analysis, and invasion assay. Our study disclosed that the IK1 (acetyl-RPSFPPEE-amino) peptide, like A6, has great potency to inhibit the invasion of cancer cells.

Stabilization challenges and aggregation in protein-based therapeutics in the pharmaceutical industry

Protein-based therapeutics have revolutionized the pharmaceutical industry and become vital components in the development of future therapeutics. They offer several advantages over traditional small molecule drugs, including high affinity, potency and specificity, while demonstrating low toxicity and minimal adverse effects. However, the development and manufacturing processes of protein-based therapeutics presents challenges related to protein folding, purification, stability and immunogenicity that should be addressed. These proteins, like other biological molecules, are prone to chemical and physical instabilities. The stability of protein-based drugs throughout the entire manufacturing, storage and delivery process is essential. The occurrence of structural instability resulting from misfolding, unfolding, and modifications, as well as aggregation, poses a significant risk to the efficacy of these drugs, overshadowing their promising attributes. Gaining insight into structural alterations caused by aggregation and their impact on immunogenicity is vital for the advancement and refinement of protein therapeutics. Hence, in this review, we have discussed some features of protein aggregation during production, formulation and storage as well as stabilization strategies in protein engineering and computational methods to prevent aggregation.

Engineering and Expression Strategies for Optimization of L-Asparaginase Development and Production

Genetic engineering for heterologous expression has advanced in recent years. Model systems such as Escherichia coli, Bacillus subtilis and Pichia pastoris are often used as host microorganisms for the enzymatic production of L-asparaginase, an enzyme widely used in the clinic for the treatment of leukemia and in bakeries for the reduction of acrylamide. Newly developed recombinant L-asparaginase (L-ASNase) may have a low affinity for asparagine, reduced catalytic activity, low stability, and increased glutaminase activity or immunogenicity. Some successful commercial preparations of L-ASNase are now available. Therefore, obtaining novel L-ASNases with improved properties suitable for food or clinical applications remains a challenge. The combination of rational design and/or directed evolution and heterologous expression has been used to create enzymes with desired characteristics. Computer design, combined with other methods, could make it possible to generate mutant libraries of novel L-ASNases without costly and time-consuming efforts. In this review, we summarize the strategies and approaches for obtaining and developing L-ASNase with improved properties.

QM/MM Modeling Aided Enzyme Engineering in Natural Products Biosynthesis

Natural products and their derivatives are widely used across various industries, particularly pharmaceuticals. Modern engineered biosynthesis provides an alternative way of producing and meeting the growing need for diverse natural products. Natural enzymes, on the other hand, often exhibit unsatisfactory catalytic characteristics and necessitate further enzyme engineering modifications. QM/MM, as a powerful and extensively used computational tool in the field of enzyme catalysis, has been increasingly applied in rational enzyme engineering over the past decade. In this review, we summarize recent advances in QM/MM computational investigation on enzyme catalysis and enzyme engineering for natural product biosynthesis. The challenges and perspectives for future QM/MM applications aided enzyme engineering in natural product biosynthesis will also be discussed.

Trends in in-silico guided engineering of efficient polyethylene terephthalate (PET) hydrolyzing enzymes to enable bio-recycling and upcycling of PET

Polyethylene terephthalate (PET) is the largest produced polyester globally, and less than 30% of all the PET produced globally (∼6 billion pounds annually) is currently recycled into lower-quality products. The major drawbacks in current recycling methods (mechanical and chemical), have inspired the exploration of potentially efficient and sustainable PET depolymerization using biological approaches. Researchers have discovered efficient PET hydrolyzing enzymes in the plastisphere and have demonstrated the selective degradation of PET to original monomers thus enabling biological recycling or upcycling. However, several significant hurdles such as the less efficiency of the hydrolytic reaction, low thermostability of the enzymes, and the inability of the enzyme to depolymerize crystalline PET must be addressed in order to establish techno-economically feasible commercial-scale biological PET recycling or upcycling processes. Researchers leverage a synthetic biology-based design; build, test, and learn (DBTL) methodology to develop commercially applicable efficient PET hydrolyzing enzymes through 1) high-throughput metagenomic and proteomic approaches to discover new PET hydrolyzing enzymes with superior properties: and, 2) enzyme engineering approaches to modify and optimize PET hydrolyzing properties. Recently, in-silico platforms including molecular mechanics and machine learning concepts are emerging as innovative tools for the development of more efficient and effective PET recycling through the exploration of novel mutations in PET hydrolyzing enzymes. In-silico-guided PET hydrolyzing enzyme engineering with DBTL cycles enables the rapid development of efficient variants of enzymes over tedious conventional enzyme engineering methods such as random or directed evolution. This review highlights the potential of in-silico-guided PET degrading enzyme engineering to create more efficient variants, including Ideonella sakaiensis PETase (IsPETase) and leaf-branch compost cutinases (LCC). Furthermore, future research prospects are discussed to enable a sustainable circular economy through the bioconversion of PET to original or high-value platform chemicals.

Designing artificial pathways for improving chemical production

Metabolic engineering exploits manipulation of catalytic and regulatory elements to improve a specific function of the host cell, often the synthesis of interesting chemicals. Although naturally occurring pathways are significant resources for metabolic engineering, these pathways are frequently inefficient and suffer from a series of inherent drawbacks. Designing artificial pathways in a rational manner provides a promising alternative for chemicals production. However, the entry barrier of designing artificial pathway is relatively high, which requires researchers a comprehensive and deep understanding of physical, chemical and biological principles. On the other hand, the designed artificial pathways frequently suffer from low efficiencies, which impair their further applications in host cells. Here, we illustrate the concept and basic workflow of retrobiosynthesis in designing artificial pathways, as well as the most currently used methods including the knowledge- and computer-based approaches. Then, we discuss how to obtain desired enzymes for novel biochemistries, and how to trim the initially designed artificial pathways for further improving their functionalities. Finally, we summarize the current applications of artificial pathways from feedstocks utilization to various products synthesis, as well as our future perspectives on designing artificial pathways.

Solvent tolerant enzymes in extremophiles: Adaptations and applications

Non-aqueous enzymology has always drawn attention due to the wide range of unique possibilities in biocatalysis. In general, the enzymes do not or insignificantly catalyze substrate in the presence of solvents. This is due to the interfering interactions of the solvents between enzyme and water molecules at the interface. Therefore, information about solvent-stable enzymes is scarce. Yet, solvent-stable enzymes prove quite valuable in the present day biotechnology. The enzymatic hydrolysis of the substrates in solvents synthesizes commercially valuable products, such as peptides, esters, and other transesterification products. Extremophiles, the most valuable yet not extensively explored candidates, can be an excellent source to investigate this avenue. Due to inherent structural attributes, many extremozymes can catalyze and maintain stability in organic solvents. In the present review, we aim to consolidate information about the solvent-stable enzymes from various extremophilic microorganisms. Further, it would be interesting to learn about the mechanism adapted by these microorganisms to sustain solvent stress. Various approaches to protein engineering are used to enhance catalytic flexibility and stability and broaden biocatalysis's prospects under non-aqueous conditions. It also describes strategies to achieve optimal immobilization with minimum inhibition of the catalysis. The proposed review would significantly aid our understanding of non-aqueous enzymology.

Improving ethanol tolerance of ethyl carbamate hydrolase by diphasic high pressure molecular dynamic simulations

Ethyl carbamate (EC) is mainly found in fermented foods and fermented alcoholic beverages, which could cause carcinogenic potential to humans. Reducing EC is one of the key research priorities to address security of fermented foods. Enzymatic degradation of EC with EC hydrolase in food is the most reliable and efficient method. However, poor tolerance to ethanol severely hinders application of EC hydrolase. In this study, the mutants of EC hydrolase were screened by diphasic high pressure molecular dynamic simulations (dHP-MD). The best variant with remarkable improvement in specific activity and was H68A/K70R/S325N, whose specific activity was approximately 3.42-fold higher than WT, and relative enzyme activity under 20% (v/v) was 5.02-fold higher than WT. Moreover, the triple mutant increased its stability by acquiring more hydration shell and forming extra hydrogen bonds. Furthermore, the ability of degrading EC of the immobilized triple mutant was both detected in mock wine and under certain reaction conditions. The stability of immobilized triple mutant and WT were both improved, and immobilized triple mutant degraded nearly twice as much EC as that of immobilized WT. Overall, dHP-MD was proved to effectively improve enzyme activity and ethanol tolerance for extent application at industrial scale.

Proteins and their functionalization for finding therapeutic avenues in cancer: Current status and future prospective

Despite the remarkable advancement in the health care sector, cancer remains the second most fatal disease globally. The existing conventional cancer treatments primarily include chemotherapy, which has been associated with little to severe side effects, and radiotherapy, which is usually expensive. To overcome these problems, target-specific nanocarriers have been explored for delivering chemo drugs. However, recent reports on using a few proteins having anticancer activity and further use of them as drug carriers have generated tremendous attention for furthering the research towards cancer therapy. Biomolecules, especially proteins, have emerged as suitable alternatives in cancer treatment due to multiple favourable properties including biocompatibility, biodegradability, and structural flexibility for easy surface functionalization. Several in vitro and in vivo studies have reported that various proteins derived from animal, plant, and bacterial species, demonstrated strong cytotoxic and antiproliferative properties against malignant cells in native and their different structural conformations. Moreover, surface tunable properties of these proteins help to bind a range of anticancer drugs and target ligands, thus making them efficient delivery agents in cancer therapy. Here, we discuss various proteins obtained from common exogenous sources and how they transform into effective anticancer agents. We also comprehensively discuss the tumor-killing mechanisms of different dietary proteins such as bovine α-lactalbumin, hen egg-white lysozyme, and their conjugates. We also articulate how protein nanostructures can be used as carriers for delivering cancer drugs and theranostics, and strategies to be adopted for improving their in vivo delivery and targeting. We further discuss the FDA-approved protein-based anticancer formulations along with those in different phases of clinical trials.

Building biomaterials through genetic code expansion

Genetic code expansion (GCE) enables directed incorporation of noncoded amino acids (NCAAs) and unnatural amino acids (UNAAs) into the active core that confers dedicated structure and function to engineered proteins. Many protein biomaterials are tandem repeats that intrinsically include NCAAs generated through post-translational modifications (PTMs) to execute assigned functions. Conventional genetic engineering approaches using prokaryotic systems have limited ability to biosynthesize functionally active biomaterials with NCAAs/UNAAs. Codon suppression and reassignment introduce NCAAs/UNAAs globally, allowing engineered proteins to be redesigned to mimic natural matrix-cell interactions for tissue engineering. Expanding the genetic code enables the engineering of biomaterials with catechols - growth factor mimetics that modulate cell-matrix interactions - thereby facilitating tissue-specific expression of genes and proteins. This method of protein engineering shows promise in achieving tissue-informed, tissue-compliant tunable biomaterials.

Engineering DszC Mutants from Transition State Macrodipole Considerations and Evolutionary Sequence Analysis

We describe an approach to identify enzyme mutants with increased turnover using the enzyme DszC as a case study. Our approach is based on recalculating the barriers of alanine mutants through single-point energy calculations at the hybrid QM/MM level in the wild-type reactant and transition state geometries. We analyze the difference in the electron density between the reactant and transition state to identify sites/residues where electrostatic interactions stabilize the transition state over the reactants. We also assess the insertion of a unit probe charge to identify positions in which the introduction of charged residues lowers the barrier.

Feruloyl Esterases Protein Engineering to Enhance Their Performance as Biocatalysts: A Review

Feruloyl esterases (FAEs) are versatile enzymes able to release hydroxycinnamic acids or synthesize their ester derivatives, both molecules with interesting biological activities such as: antioxidants, antifungals, antivirals, antifibrotic, anti-inflammatory, among others. The importance of these molecules in medicine, food or cosmetic industries provides FAEs with several biotechnological applications as key industrial biocatalysts. However, FAEs have some operational limitations that must be overcome, which can be addressed through different protein engineering approaches to enhance their thermal stability, catalytic efficiencies, and selectivity. This review aims to present a brief historical tour through the mutagenesis strategies employed to improve enzymes performance and analyze the current protein engineering strategies applied to FAEs as interesting biocatalysts. Finally, an outlook of the future of FAEs protein engineering approaches to achieve successful industrial biocatalysts is given.

Biocatalysis for the asymmetric synthesis of Active Pharmaceutical Ingredients (APIs): this time is for real

INTRODUCTION

Biocatalysis has emerged as a powerful and useful strategy for the synthesis of active pharmaceutical ingredients (APIs). The outstanding developments in molecular biology techniques allow nowadays the screening, large-scale production, and designing of biocatalysts, adapting them to desired reactions. Many enzymes can perform reactions both in aqueous and non-aqueous media, broadening even further the opportunities to integrate them in complex pharmaceutical multi-step syntheses.

AREAS COVERED

This paper showcases several examples of biocatalysis in the pharmaceutical industry, covering examples of different enzymes, such as lipases, oxidoreductases, and transaminases, to deliver active drugs through complex synthetic routes. Examples are critically discussed in terms of reaction conditions, motivation for using an enzyme, and how biocatalysts can be integrated in multi-step syntheses. When possible, biocatalytic routes are benchmarked with chemical reactions.

EXPERT OPINION

The reported enzymatic examples are performed with high substrate loadings (>100 g L^-1) and with excellent selectivity, making them inspiring strategies for present and future industrial applications. The combination of powerful molecular biology techniques with the needs of the pharmaceutical industry can be aligned, creating promising platforms for synthesis under more sustainable conditions.

Role of Enzyme and Active Site Conformational Dynamics in the Catalysis by α-Amylase Explored with QM/MM Molecular Dynamics

We assessed enzyme:substrate conformational dynamics and the rate-limiting glycosylation step of a human pancreatic α-amylase:maltopentose complex. Microsecond molecular dynamics simulations suggested that the distance of the catalytic Asp197 nucleophile to the anomeric carbon of the buried glucoside is responsible for most of the enzyme active site fluctuations and that both Asp197 and Asp300 interact the most with the buried glucoside unit. The buried glucoside binds either in a ⁴C₁ chair or ²S_O skew conformations, both of which can change to TS-like conformations characteristic of retaining glucosidases. Starting from four distinct enzyme:substrate complexes, umbrella sampling quantum mechanics/molecular mechanics simulations (converged within less than 1 kcal·mol^-1 within a total simulation time of 1.6 ns) indicated that the reaction occurrs with a Gibbs barrier of 13.9 kcal·mol ^-1, in one asynchronous concerted step encompassing an acid-base reaction with Glu233 followed by a loose S_N2-like nucleophilic substitution by the Asp197. The transition state is characterized by a ²H₃ half-chair conformation of the buried glucoside that quickly changes to the E₃ envelope conformation preceding the attack of the anomeric carbon by the Asp197 nucleophile. Thermodynamic analysis of the reaction supported that a water molecule tightly hydrogen bonded to the glycosidic oxygen of the substrate at the reactant state (∼1.6 Å) forms a short hydrogen bond with Glu233 at the transition state (∼1.7 Å) and lowers the Gibbs barrier in over 5 kcal·mol^-1. The resulting Asp197-glycosyl was mostly found in the ⁴C₁ conformation, although the more endergonic B_3,O conformation was also observed. Altogether, the combination of short distances for the acid-base reaction with the Glu233 and for the nucleophilic attack by the Asp197 nucleophile and the availability of water within hydrogen bonding distance of the glycosidic oxygen provides a reliable criteria to identify reactive conformations of α-amylase complexes.

Sequence and Structure-Guided Engineering of Urethanase from Agrobacterium tumefaciens d3 for Improved Catalytic Activity

The amidase from Agrobacterium tumefaciens d3 (AmdA) degrades the carcinogenic ethyl carbamate (EC) in alcoholic beverages. However, its limited catalytic activity hinders practical applications. Here, multiple sequence alignment was first used to predict single variants with improved activity. Afterward, AlphaFold 2 was applied to predict the three-dimensional structure of AmdA and 21 amino acids near the catalytic triad were randomized by saturation mutagenesis. Each of the mutation libraries was then screened, and the improved single variants were combined to obtain the best double variant I97L/G195A that showed a 3.1-fold increase in the urethanase activity and a 1.5-fold increase in ethanol tolerance. MD simulations revealed that the mutations shortened the distance between catalytic residues and the substrate and enhanced the occurrence of a critical hydrogen bond in the catalytic pocket. This study displayed a useful strategy to engineer an amidase for the improvement of urethanase activity, and the variant obtained provided a good candidate for applications in the food industry.

Improvement of Fusel Alcohol Production by Engineering of the Yeast Branched-Chain Amino Acid Aminotransaminase

Branched-chain higher alcohols (BCHAs), or fusel alcohols, including isobutanol, isoamyl alcohol, and active amyl alcohol, are useful compounds in several industries. The yeast Saccharomyces cerevisiae can synthesize these compounds via the metabolic pathways of branched-chain amino acids (BCAAs). Branched-chain amino acid aminotransaminases (BCATs) are the key enzymes for BCHA production via the Ehrlich pathway of BCAAs. BCATs catalyze a bidirectional transamination reaction between branched-chain α-keto acids (BCKAs) and BCAAs. In S. cerevisiae, there are two BCAT isoforms, Bat1 and Bat2, which are encoded by the genes BAT1 and BAT2. Although many studies have shown the effects of deletion or overexpression of BAT1 and BAT2 on BCHA production, there have been no reports on the enhancement of BCHA production by functional variants of BCATs. Here, to improve BCHA productivity, we designed variants of Bat1 and Bat2 with altered enzyme activity by using in silico computational analysis: the Gly333Ser and Gly333Trp Bat1 and corresponding Gly316Ser and Gly316Trp Bat2 variants, respectively. When expressed in S. cerevisiae cells, most of these variants caused a growth defect in minimal medium. Interestingly, the Gly333Trp Bat1 and Gly316Ser Bat2 variants achieved 18.7-fold and 17.4-fold increases in isobutanol above that for the wild-type enzyme, respectively. The enzyme assay revealed that the catalytic activities of all four BCAT variants were lower than that of the wild-type enzyme. Our results indicate that the decreased BCAT activity enhanced BCHA production by reducing BCAA biosynthesis, which occurs via a pathway that directly competes with BCHA production.

IMPORTANCE Recently, several studies have attempted to increase the production of branched-chain higher alcohols (BCHAs) in the yeast Saccharomyces cerevisiae. The key enzymes for BCHA biosynthesis in S. cerevisiae are the branched-chain amino acid aminotransaminases (BCATs) Bat1 and Bat2. Deletion or overexpression of the genes encoding BCATs has an impact on the production of BCHAs; however, amino acid substitution variants of Bat1 and Bat2 that could affect enzymatic properties—and ultimately BCHA productivity—have not been fully studied. By using in silico analysis, we designed variants of Bat1 and Bat2 and expressed them in yeast cells. We found that the engineered BCATs decreased catalytic activities and increased BCHA production. Our approach provides new insight into the functions of BCATs and will be useful in the future construction of enzymes optimized for high-level production of BCHAs.

The stability and dynamics of computationally designed proteins

Protein stability, dynamics and function are intricately linked. Accordingly, protein designers leverage dynamics in their designs and gain insight to their successes and failures by analyzing their proteins' dynamics. Molecular dynamics (MD) simulations are a powerful computational tool for quantifying both local and global protein dynamics. This review highlights studies where MD simulations were applied to characterize the stability and dynamics of designed proteins and where dynamics were incorporated into computational protein design. First, we discuss the structural basis underlying the extreme stability and thermostability frequently observed in computationally designed proteins. Next, we discuss examples of designed proteins, where dynamics were not explicitly accounted for in the design process, whose coordinated motions or active site dynamics, as observed by MD simulation, enhanced or detracted from their function. Many protein functions depend on sizeable or subtle conformational changes, so we finally discuss the computational design of proteins to perform a specific function that requires consideration of motion by multi-state design.

Switching promotor recognition of phage RNA polymerase in silico along lab-directed evolution path

In this work, we computationally investigated how a viral RNA polymerase (RNAP) from bacteriophage T7 evolves into RNAP variants under lab-directed evolution to switch recognition from T7 promoter to T3 promoter in transcription initiation. We first constructed a closed initiation complex for the wild-type T7 RNAP and then for six mutant RNAPs discovered from phage-assisted continuous evolution experiments. All-atom molecular dynamics simulations up to 1 μs each were conducted on these RNAPs in a complex with the T7 and T3 promoters. Our simulations show notably that protein-DNA electrostatic interactions or stabilities at the RNAP-DNA promoter interface well dictate the promoter recognition preference of the RNAP and variants. Key residues and structural elements that contribute significantly to switching the promoter recognition were identified. Followed by a first point mutation N748D on the specificity loop to slightly disengage the RNAP from the promoter to hinder the original recognition, we found an auxiliary helix (206-225) that takes over switching the promoter recognition upon further mutations (E222K and E207K) by forming additional charge interactions with the promoter DNA and reorientating differently on the T7 and T3 promoters. Further mutations on the AT-rich loop and the specificity loop can fully switch the RNAP-promoter recognition to the T3 promoter. Overall, our studies reveal energetics and structural dynamics details along an exemplary directed evolutionary path of the phage RNAP variants for a rewired promoter recognition function. The findings demonstrate underlying physical mechanisms and are expected to assist knowledge and data learning or rational redesign of the protein enzyme structure function.

Strategies for Improving Small-Molecule Biosensors in Bacteria

In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.

Protein Engineering: Advances in Phage Display for Basic Science and Medical Research

Functional Protein Engineering became the hallmark in biomolecule manipulation in the new millennium, building on and surpassing the underlying structural DNA manipulation and recombination techniques developed and employed in the last decades of 20th century. Because of their prominence in almost all biological processes, proteins represent extremely important targets for engineering enhanced or altered properties that can lead to improvements exploitable in healthcare, medicine, research, biotechnology, and industry. Synthetic protein structures and functions can now be designed on a computer and/or evolved using molecular display or directed evolution methods in the laboratory. This review will focus on the recent trends in protein engineering and the impact of this technology on recent progress in science, cancer- and immunotherapies, with the emphasis on the current achievements in basic protein research using synthetic antibody (sABs) produced by phage display pipeline in the Kossiakoff laboratory at the University of Chicago (KossLab). Finally, engineering of the highly specific binding modules, such as variants of Streptococcal protein G with ultra-high orthogonal affinity for natural and engineered antibody scaffolds, and their possible applications as a plug-and-play platform for research and immunotherapy will be described.

Rational Design of Anti-Angiogenic Peptides to Inhibit VEGF/VEGFR2 Interactions for Cancer Therapeutics

BACKGROUND

Angiogenesis is a critical physiological process that plays a key role in tumor progression, metastatic dissemination, and invasion. In the last two decades, the vascular endothelial growth factor (VEGF) signaling pathway has been the area of extensive researches. VEGF executes its special effects by binding to vascular endothelial growth factor receptors (VEGFRs), particularly VEGFR-2.

OBJECTIVE

The inhibition of VEGF/VEGFR2 interaction is known as an effective cancer therapy strategy. The current study pointed to design and model an anti-VEGF peptide based on VEGFR2 binding regions.

METHOD

The large-scale peptide mutation screening was used to achieve a potent peptide with high binding affinity to VEGF for possible application in inhibition of VEGF/VEGFR2 interaction. The AntiCP and Peptide Ranker servers were used to generate the possible peptides library with anticancer activities and prediction of peptides bioactivity. Then, the interaction of VEGF and all library peptides were analyzed using Hex 8.0.0 and ClusPro tools. A number of six peptides with favorable docking scores were achieved. All of the best docking scores of peptides in complexes with VEGF were evaluated to confirm their stability, using molecular dynamics simulation (MD) with the help of the GROMACS software package.

RESULTS

As a result, two antiangiogenic peptides with 13 residues of PepA (NGIDFNRDFFLGL) and PepC (NGIDFNRDKFLFL) were achieved and introduced to inhibit VEGF/VEGFR2 interactions.

CONCLUSIONS

In summary, this study provided new insights into peptide-based therapeutics development for targeting VEGF signaling pathway in tumor cells. PepA and PepC are recommended as potentially promising anticancer agents for further experimental evaluations.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Temperature-resistant and solvent-tolerant lipases as industrial biocatalysts: Biotechnological approaches and applications

The development of new biocatalytic systems to replace the chemical catalysts, with suitable characteristics in terms of efficiency, stability under high temperature reactions and in the presence of organic solvents, reusability, and eco-friendliness is considered a very important step to move towards the green processes. From this basis, the use of lipase as a catalyst is highly desired for many industrial applications because it offers the reactions in which could be used, stability in harsh conditions, reusability and a greener process. Therefore, the introduction of temperature-resistant and solvent-tolerant lipases have become essential and ideal for industrial applications. Temperature-resistant and solvent-tolerant lipases have been involved in many large-scale applications including biodiesel, detergent, food, pharmaceutical, organic synthesis, biosensing, pulp and paper, textile, animal feed, cosmetics, and leather industry. So, the present review provides a comprehensive overview of the industrial use of lipase. Moreover, special interest in biotechnological and biochemical techniques for enhancing temperature-resistance and solvent-tolerance of lipases to be suitable for the industrial uses.

Advance in glycosyltransferases, the important bioparts for production of diversified ginsenosides

Ginsenosides are a series of glycosylated triterpenoids predominantly originated from Panax species with multiple pharmacological activities such as anti-aging, mediatory effect on the immune system and the nervous system. During the biosynthesis of ginsenosides, glycosyltransferases play essential roles by transferring various sugar moieties to the sapogenins in contributing to form structure and bioactivity diversified ginsenosides, which makes them important bioparts for synthetic biology-based production of these valuable ginsenosides. In this review, we summarized the functional elucidated glycosyltransferases responsible for ginsenoside biosynthesis, the advance in the protein engineering of UDP-glycosyltransferases (UGTs) and their application with the aim to provide in-depth understanding on ginsenoside-related UGTs for the production of rare ginsenosides applying synthetic biology-based microbial cell factories in the future.

Entrapment of glucose oxidase within gold converts it to a general monosaccharide-oxidase

We report that entrapping glucose oxidase (GOx) within metallic gold, expands its activity to become an oxidase for monosaccharides that do not have a natural enzyme with that activity-fructose and xylose-and that this entrapment also removes the enantioselectivity, rendering this enzyme capable of oxidizing the "wrong" L-enantiomer of glucose. These observations suggest that in this biomaterial adsorptive interactions of the outer regions of the protein with the gold cage, pull apart and widen the tunnel between the two monomeric units of GOx, to a degree that its stereoselectivity is compromised; then, the active sites which are more versatile than currently attributed to, are free and capable of acting on the foreign sugars. To test this proposition, we entrapped in gold L-asparaginase, which is also a dimeric enzyme (a dimer of tight dimers), and found, again, that this metallic biomaterial widens the activity of that enzyme, to include the D-amino acid counter enantiomer as well. Detailed kinetic analyses for all substrates are provided for the gold bio-composites, including determination of the difference between the activation energies towards two opposite enantiomers.

Revolutionizing enzyme engineering through artificial intelligence and machine learning

The combinatorial space of an enzyme sequence has astronomical possibilities and exploring it with contemporary experimental techniques is arduous and often ineffective. Multi-target objectives such as concomitantly achieving improved selectivity, solubility and activity of an enzyme have narrow plausibility under approaches of restricted mutagenesis and combinatorial search. Traditional enzyme engineering approaches have a limited scope for complex optimization due to the requirement of a priori knowledge or experimental burden of screening huge protein libraries. The recent surge in high-throughput experimental methods including Next Generation Sequencing and automated screening has flooded the field of molecular biology with big-data, which requires us to re-think our concurrent approaches towards enzyme engineering. Artificial Intelligence (AI) and Machine Learning (ML) have great potential to revolutionize smart enzyme engineering without the explicit need for a complete understanding of the underlying molecular system. Here, we portray the role and position of AI techniques in the field of enzyme engineering along with their scope and limitations. In addition, we explain how the traditional approaches of directed evolution and rational design can be extended through AI tools. Recent successful examples of AI-assisted enzyme engineering projects and their deviation from traditional approaches are highlighted. A comprehensive picture of current challenges and future avenues for AI in enzyme engineering are also discussed.

IND-enzymes: a repository for hydrolytic enzymes derived from thermophilic and psychrophilic bacterial species with potential industrial usage

Biocatalysts provide many advantages over the traditional chemically assisted processes prevalent in industries. Consequently, the search for novel enzymes has increased over the years with a renewed interest in thermophilic and psychrophilic bacterial species. Enzymes or extremozymes extracted from such species have exhibited an affinity to extreme temperatures which is a prerequisite for many industrial applications. However, utilisation of these enzymes faces a major bottleneck. The distribution of sequence data associated with thermophiles and psychrophiles is overwhelming, spanning various databases and scientific literature. Based on more than 100 publications and genomes from over 300 thermophilic and psychrophilic bacterial species, we have constructed the database IND-Enzymes (indenzymes.srmist.edu.in). This database consists of over 20,120 nucleotide and protein sequences belonging to the hydrolytic enzyme class lipase, protease, esterase and amylase. Users can access over 100 published enzymes, 200 PDB structural data. Enzymes derived from genomes can be directly downloaded and users can also access the entire annotation data derived from species individually. Along with an alignment tool and python based pipelines, IND-Enzymes serves as the largest sequence repository for hydrolytic enzymes from thermophilic and psychrophilic bacterial species. This database showcases resources that are essential for protein engineering of hot-cold stable enzymes.

From Enzyme Stability to Enzymatic Bioelectrode Stabilization Processes

Bioelectrocatalysis using redox enzymes appears as a sustainable way for biosensing, electricity production, or biosynthesis of fine products. Despite advances in the knowledge of parameters that drive the efficiency of enzymatic electrocatalysis, the weak stability of bioelectrodes prevents large scale development of bioelectrocatalysis. In this review, starting from the understanding of the parameters that drive protein instability, we will discuss the main strategies available to improve all enzyme stability, including use of chemicals, protein engineering and immobilization. Considering in a second step the additional requirements for use of redox enzymes, we will evaluate how far these general strategies can be applied to bioelectrocatalysis.

Improving the activity and stability of Bacillus clausii alkaline protease using directed evolution and molecular dynamics simulation

Detergent enzymes have been developed extensively as eco-friendly substitutes for the harmful chemicals in detergent. Among them, alkaline protease accounts for a large share of detergent enzyme sales. Thus, improving the specific activity of alkaline protease could play an important role in reducing the cost of detergent enzymes. In our study, alkaline protease from Bacillus clausii (PRO) was used to construct a mutant library through directed evolution using error-prone PCR, and a variant (G95P) with 9-fold enhancement in specific activity was obtained. After incubation at a pH of 11.0 for 70 h, G95P maintained 67 % of its maximal activity, which was 46 % more than wild-type PRO (WT), indicating that G95P has better alkaline stability than WT. The thermostability of G95P was also enhanced, as G95P achieved 17 % initial activity after incubation for 50 h at 60 °C, while WT lost its activity. The MD simulation results verified that variant G95P possessed improved stability of its Gly95-Gly100 loop region and Arg19-Asp265 salt bridge, leading to enhanced stability and catalytic efficiency. This work enhances the understanding of the structure-function relationship of PRO and provides an academic foundation for improving the enzymatic properties of PRO to satisfy industrial requirements using protein engineering.

Using Mutability Landscapes To Guide Enzyme Thermostabilization

Thermostabilizing enzymes while retaining their activity and enantioselectivity for applied biocatalysis is an important topic in protein engineering. Rational and computational design strategies as well as directed evolution have been used successfully to thermostabilize enzymes. Herein, we describe an alternative mutability-landscape approach that identified three single mutations (R11Y, R11I and A33D) within the enzyme 4-oxalocrotonate tautomerase (4-OT), which has potential as a biocatalyst for pharmaceutical synthesis, that gave rise to significant increases in apparent melting temperature Tm (up to 20 °C) and in half-life at 80 °C (up to 111-fold). Introduction of these beneficial mutations in an enantioselective but thermolabile 4-OT variant (M45Y/F50A) afforded improved triple-mutant enzyme variants showing an up to 39 °C increase in Tm value, with no reduction in catalytic activity or enantioselectivity. This study illustrates the power of mutability-landscape-guided protein engineering for thermostabilizing enzymes.

Large-scale production of enzymes for biotechnology uses

Enzymes are biocatalysts that speed up the chemical reaction to obtain the final valuable product/s. Biotechnology has revolutionized the use of traditional enzymes to be applicable in industries such as food, beverage, personal and household care, agriculture, bioenergy, pharmaceutical, and various other segments. With respect to the exponential growth of enzymes in biotech industries, it becomes important to highlight the advancements and impact of enzyme technology over recent years. In this review article, we discuss the existing and emerging production approaches, applications, developments, and global need for enzymes. Special emphasis is given to the predominantly utilized hydrolytic microbial enzymes in industrial bioprocesses.

Design of Calcium-Binding Proteins to Sense Calcium

Calcium controls numerous biological processes by interacting with different classes of calcium binding proteins (CaBP’s), with different affinities, metal selectivities, kinetics, and calcium dependent conformational changes. Due to the diverse coordination chemistry of calcium, and complexity associated with protein folding and binding cooperativity, the rational design of CaBP’s was anticipated to present multiple challenges. In this paper we will first discuss applications of statistical analysis of calcium binding sites in proteins and subsequent development of algorithms to predict and identify calcium binding proteins. Next, we report efforts to identify key determinants for calcium binding affinity, cooperativity and calcium dependent conformational changes using grafting and protein design. Finally, we report recent advances in designing protein calcium sensors to capture calcium dynamics in various cellular environments.

Enzymes to unravel bioproducts architecture

Enzymes are essential and ubiquitous biocatalysts involved in various metabolic pathways and used in many industrial processes. Here, we reframe enzymes not just as biocatalysts transforming bioproducts but also as sensitive probes for exploring the structure and composition of complex bioproducts, like meat tissue, dairy products and plant materials, in both food and non-food bioprocesses. This review details the global strategy and presents the most recent investigations to prepare and use enzymes as relevant probes, with a focus on glycoside-hydrolases involved in plant deconstruction and proteases and lipases involved in food digestion. First, to expand the enzyme repertoire to fit bioproduct complexity, novel enzymes are mined from biodiversity and can be artificially engineered. Enzymes are further characterized by exploring sequence/structure/dynamics/function relationships together with the environmental factors influencing enzyme interactions with their substrates. Then, the most advanced experimental and theoretical approaches developed for exploring bioproducts at various scales (from nanometer to millimeter) using active and inactive enzymes as probes are illustrated. Overall, combining multimodal and multiscale approaches brings a better understanding of native-form or transformed bioproduct architecture and composition, and paves the way to mainstream the use of enzymes as probes.

Molecular dynamics simulations suggest stabilizing mutations in a de novo designed α/β protein

Designing functional proteins that can withstand extreme heat is beneficial for industrial and protein therapeutic applications. Thus, elucidating the atomic-level determinants of thermostability is a major interest for rational protein design. To that end, we compared the structure and dynamics of a set of previously designed, thermostable proteins based on the activation domain of human procarboxypeptidase A2 (AYEwt). The mutations in these designed proteins were intended to increase hydrophobic core packing and inter-secondary-structure interactions. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations of AYEwt and three designed variants at both 25 and 100°C. Our MD simulations agreed with the relative experimental stabilities of the designs based on their secondary structure content, Cα root-mean-square deviation/fluctuation, and buried-residue solvent accessible surface area. Using a contact analysis, we found that the designs stabilize inter-secondary structure interactions and buried hydrophobic surface area, as intended. Based on our analysis, we designed three additional variants to test the role of helix stabilization, core packing, and a Phe → Met mutation on thermostability. We performed the additional MD simulations and analysis on these variants, and these data supported our predictions.

Rational molecular design for improving digestive enzyme resistance of beta-glucosidase from Trichoderma viride based on inhibition of bound state formation

Beta-glucosidase (BGL1) is widely used in animal feed industries. However, degradation caused by digestive enzymes in the intestine hampers its application. Improving the resistance of feed enzymes against proteases is crucial in livestock farming. To improve the resistance of beta-glucosidase against pepsin and trypsin, a rational molecular design based on the inhibition of bound-state formation and secondary design was developed. The strategy includes: (1) prediction of the interaction surface of the pepsin-BGL1 complex structure, (2) prediction of key amino acids affecting the formation of the complex, (3) optimization of pepsin-resistant mutants by structural evaluation, (4) secondary molecular design based on pepsin-resistant mutants, and optimization of pepsin and trypsin-resistant mutants. Two BGL1 protein mutants (BGL1^Q627C and BGL1^{Q627C/R543H/R646W}) were constructed, and then mutated and wild-type BGL1s were expressed in Pichia pastoris. The half-life of BGL1^Q627C and BGL1^{Q627C/R543H/R646W} were 1.36 and 1.51 times that of the wild type upon pepsin exposure, respectively. For trypsin resistance, the half-life were 0.93 and 1.53 times that of the wild type, respectively. Compare to those of the wild type, most of the basic enzymatic properties of both mutants were not significantly changed except for increased Michaelis constants. The rational design method can be used as a guide for modifying other feed enzymes.