Computational design of a pH stable enzyme: understanding molecular mechanism of penicillin acylase's adaptation to alkaline conditions

Advancing Enzyme Optimal pH Prediction via Retrieved Embedding Data Augmentation

The optimal enzyme pH is a critical factor that directly influences the catalytic efficiency of the enzymes. Accurate computational prediction of the optimal pH can greatly advance our understanding and design of enzymes for diverse scientific and industrial applications. However, current prediction tools often fall short in terms of accuracy and robustness. In this study, we propose OpHReda, a novel method that significantly improves enzyme optimal pH prediction by leveraging a retrieved embedding data augmentation mechanism. Given an enzyme sequence, OpHReda first retrieves similar sequence embeddings from a preconstructed augmentation database. It then jointly analyzes the original and retrieved embeddings through the Multiple Embedding Alignment transformer to narrow the prediction range. Finally, the calibrator integrates residue-level information with the refined prediction range to make the final prediction. By moving beyond the limitations of single-sequence-based models, OpHReda achieves a 55% improvement in F1-score compared to that of state-of-the-art methods. Extensive ablation studies demonstrate that this enhancement arises from the synergy between our tailored architecture and the augmentation mechanism. Overall, OpHReda offers a promising advancement in enzyme optimal pH prediction and holds potential for downstream applications such as enzyme engineering and rational design.

Enhancement of the catalytic activity of thermostable Endo-1,4-β-glucanase B (TnCelB) from Thermotoga neapolitana by error-prone PCR

Endo-1,4-β-glucanase plays a crucial role in converting cellulose from lignocellulosic biomass into fermentable sugars for biofuel production. However, its commercial utility is hindered by poor catalytic performance under extreme conditions. This study enhanced the catalytic activity of the endo-1,4-β-glucanase (TnCelB) from Thermotoga neapolitana through error-prone PCR directed evolution. After screening >4000 colonies, three mutants with enhanced activity were obtained. Mutants TnCelBY88F, TnCelBA233T, and TnCelBW219R displayed 52.14 U/mg, 44.90 U/mg, and 34.70 U/mg of specific activity on CMC, respectively, which is 1.9, 1.7, and 1.3 times higher than that of the wild-type (26.74 U/mg), correspondingly. Likewise, their enzyme activity on barley β-D-glucan increased by 3.5, 2.2, and 1.8 times, respectively. Notably, TnCelBY88F maintained over 90 % activity after 60 mins at high temperatures (80-100 °C), indicating an exceptional thermostability. Protein docking revealed that TnCelBY88F had higher binding affinity, aligned with kinetic studies. TnCelB was capble of released more non-oxidized sugars from the hydrolysis of regenerated amorphous cellulose (RAC) by synergy with auxiliary action family 10 (AA10), which is potential in development of efficient lignocellulosic saccharification. This study can provide useful insights for the future engineering of other endoglucanases in the glycoside hydrolases family 12.

A Deep Retrieval-Enhanced Meta-Learning Framework for Enzyme Optimum pH Prediction

The potential of hydrogen (pH) influences the function of the enzyme. Measuring or predicting the optimal pH (pHopt) at which enzymes exhibit maximal catalytic activity is crucial for enzyme design and application. The rapid development of enzyme mining and de novo design has produced a large number of new enzymes, making it impractical to measure their pHopt in the wet laboratory. Consequently, in-silico computational approaches such as machine learning and deep learning models, which offer pH prediction at minimal cost, have attracted considerable interest. This work presents Venus-DREAM, an enzyme pHopt prediction model based on the kNN algorithm and few-shot learning, which achieves state-of-the-art accuracy in pHopt prediction. Venus-DREAM regards the pHopt prediction of an enzyme as a few-shot learning task: learning from the k-closest labeled enzymes to predict the pHopt of the target enzyme. The value of k is determined by the optimal k-value of the kNN regression algorithm. And the distance between two enzymes is defined as the cosine similarity of their mean-pooled embeddings obtained from protein language models (PLMs). The few-shot learner is based on the Reptile algorithm, which first adapts to the k-nearest labeled enzymes to create a specialized model for the target enzyme and then predicts its pHopt. This efficient method enables high-throughput virtual exploration of protein space, facilitating the identification of sequences with the desired pHopt ranges in a high-throughput manner. Moreover, our method can be easily adapted in other protein function prediction tasks.

Unveiling the hydrolase Oph2876 mediated chlorpyrifos degradation mechanism in Pseudomonas nitroreducens and its potential for environmental bioremediation

Chlorpyrifos contamination is a currently on-going issue with significant environmental impacts. As such, rapid and effective techniques that remove chlorpyrifos from the environment are urgently required. Here, a strain of Pseudomonas nitroreducens W-7 exhibited exceptional degradation ability towards both chlorpyrifos and its major metabolite 3,5,6-trichloro-2-pyridinol (TCP). W-7 can effectively reduce the toxicity of chlorpyrifos and TCP towards a variety of sensitive organisms through its superior degradation capacity. W-7 demonstrated efficient soil bioremediation by removing over 50 % of chlorpyrifos (25 mg/kg) from both sterile and non-sterile soils within 5 days, with significantly reduced half-lives. Additionally, 16S rDNA high-throughput sequencing of the soil revealed that the introduction of W-7 had no significant impact on the soil microbial community. A pivotal hydrolase Oph2876 containing conserved motif (HxHxDH) and a bimetallic catalytic center was identified from W-7. Oph2876 was a heat- and alkali-resistant enzyme with low sequence similarity (< 44 %) with other reported organophosphorus hydrolases, with a better substrate affinity for hydrolysis of chlorpyrifos to TCP. The molecular docking and site-directed mutagenesis studies indicated that the amino acid residues Asp235, His214, and His282, which were associated with the conserved sequence "HxHxDH", were crucial for the activity of Oph2876. These findings contribute to a better understanding of the biodegradation mechanism of chlorpyrifos and present useful agents for the development of effective chlorpyrifos bioremediation strategies.

Accurately predicting optimal conditions for microorganism proteins through geometric graph learning and language model

Proteins derived from microorganisms that survive in the harshest environments on Earth have stable activity under extreme conditions, providing rich resources for industrial applications and enzyme engineering. Due to the time-consuming nature of experimental determinations, it is imperative to develop computational models for fast and accurate prediction of protein optimal conditions. Previous studies were limited by the scarcity of data and the neglect of protein structures. To solve these problems, we constructed an up-to-date dataset with 175,905 non-redundant proteins and proposed a new model GeoPoc based on geometric graph learning for the protein optimal temperature, pH, and salt concentration prediction. GeoPoc leverages protein structures and sequence embeddings extracted from pre-trained language model, and further employs a geometric graph transformer network to capture the sequence and spatial information. We first focused on in-house validation for optimal temperature prediction for robustness assessment, and achieved a PCC of 0.78. The algorithm is further confirmed in an independent test set, where GeoPoc surpasses the state-of-the-art method by 2.3% in AUC. Additionally, GeoPoc was extended to pH and salt concentration prediction, and obtained AUC scores of 0.78 and 0.77, respectively. Through further interpretable analysis, GeoPoc elucidates the critical physicochemical properties that contribute to enhancing protein thermostability.

Mining and rational design of psychrophilic catalases using metagenomics and deep learning models

A complete catalase-encoding gene, designated soiCat1, was obtained from soil samples via metagenomic sequencing, assembly, and gene prediction. soiCat1 showed 73% identity to a catalase-encoding gene of Mucilaginibacter rubeus strain P1, and the amino acid sequence of soiCAT1 showed 99% similarity to the catalase of a psychrophilic bacterium, Pedobacter cryoconitis. soiCAT1 was identified as a psychrophilic enzyme due to the low optimum temperature predicted by the deep learning model Preoptem, which was subsequently validated through analysis of enzymatic properties. Experimental results showed that soiCAT1 has a very narrow range of optimum temperature, with maximal specific activity occurring at the lowest test temperature (4 °C) and decreasing with increasing reaction temperature from 4 to 50 °C. To rationally design soiCAT1 with an improved temperature range, soiCAT1 was engineered through site-directed mutagenesis based on molecular evolution data analyzed through position-specific amino acid possibility calculation. Compared with the wild type, one mutant, soiCAT1S205K, exhibited an extended range of optimum temperature ranging from 4 to 20 °C. The strategies used in this study may shed light on the mining of genes of interest and rational design of desirable proteins. KEY POINTS: • Numerous putative catalases were mined from soil samples via metagenomics. • A complete sequence encoding a psychrophilic catalase was obtained. • A mutant psychrophilic catalase with an extended range of optimum temperature was engineered through site-directed mutagenesis.

Killer yeasts: expanding frontiers in the age of synthetic biology

Killer yeasts secrete protein toxins that are selectively lethal to other yeast and filamentous fungi. These exhibit exceptional genetic and functional diversity, and have several biotechnological applications. However, despite decades of research, several limitations hinder their widespread adoption. In this perspective we contend that technical advances in synthetic biology present an unprecedented opportunity to unlock the full potential of yeast killer systems across a spectrum of applications. By leveraging these new technologies, engineered killer toxins may emerge as a pivotal new tool to address antifungal resistance and food security. Finally, we speculate on the biotechnological potential of re-engineering host double-stranded (ds) RNA mycoviruses, from which many toxins derive, as a safe and noninfectious system to produce designer RNA.

Exploring the Structurally Conserved Regions and Functional Significance in Bacterial N-Terminal Nucleophile (Ntn) Amide-Hydrolases

The initial adoption of penicillin as an antibiotic marked the start of exploring other compounds essential for pharmaceuticals, yet resistance to penicillins and their side effects has compromised their efficacy. The N-terminal nucleophile (Ntn) amide-hydrolases S45 family plays a key role in catalyzing amide bond hydrolysis in various compounds, including antibiotics like penicillin and cephalosporin. This study comprehensively analyzes the structural and functional traits of the bacterial N-terminal nucleophile (Ntn) amide-hydrolases S45 family, covering penicillin G acylases, cephalosporin acylases, and D-succinylase. Utilizing structural bioinformatics tools and sequence analysis, the investigation delineates structurally conserved regions (SCRs) and substrate binding site variations among these enzymes. Notably, sixteen SCRs crucial for substrate interaction are identified solely through sequence analysis, emphasizing the significance of sequence data in characterizing functionally relevant regions. These findings introduce a novel approach for identifying targets to enhance the biocatalytic properties of N-terminal nucleophile (Ntn) amide-hydrolases, while facilitating the development of more accurate three-dimensional models, particularly for enzymes lacking structural data. Overall, this research advances our understanding of structure-function relationships in bacterial N-terminal nucleophile (Ntn) amide-hydrolases, providing insights into strategies for optimizing their enzymatic capabilities.

Advances in recombinant protease production: current state and perspectives

Proteases, enzymes that catalyze the hydrolysis of peptide bonds in proteins, are important in the food industry, biotechnology, and medical fields. With increasing demand for proteases, there is a growing emphasis on enhancing their expression and production through microbial systems. However, proteases' native hosts often fall short in high-level expression and compatibility with downstream applications. As a result, the recombinant production of proteases has become a significant focus, offering a solution to these challenges. This review presents an overview of the current state of protease production in prokaryotic and eukaryotic expression systems, highlighting key findings and trends. In prokaryotic systems, the Bacillus spp. is the predominant host for proteinase expression. Yeasts are commonly used in eukaryotic systems. Recent advancements in protease engineering over the past five years, including rational design and directed evolution, are also highlighted. By exploring the progress in both expression systems and engineering techniques, this review provides a detailed understanding of the current landscape of recombinant protease research and its prospects for future advancements.

Biodegradation of patulin in fresh pear juice by an aldo-keto reductase from Meyerozyma guilliermondii

Bio-enzymes have shown broad application prospects in controlling mycotoxins due to their strong specificity, fast reaction rate and mild reaction conditions. However, the number of enzymes isolated, purified and characterized to degrade patulin (PAT) is limited. We expressed an aldo-keto reductase (MgAKR) from Meyerozyma guilliermondii in Escherichia coli. The results demonstrated that the purified MgAKR could convert PAT into ascladiol in vitro with NADPH serving as a coenzyme. Adding 300 μg/mL MgAKR resulted in an 88 % reduction of PAT in fresh pear juice without affecting its quality in the biodegradation process. The site-directed mutagenesis suggested that the interaction between MgAKR and PAT occurred through the active sites of Lys242 and Leu240. This study serves as a valuable theoretical reference for the development of enzymes aimed at detoxifying PAT in fruit and their derivatives.

Living in trinity of extremes: Genomic and proteomic signatures of halophilic, thermophilic, and pH adaptation

Since nucleic acids and proteins of unicellular prokaryotes are directly exposed to extreme environmental conditions, it is possible to explore the genomic-proteomic compositional determinants of molecular mechanisms of adaptation developed by them in response to harsh environmental conditions. Using a wealth of currently available complete genomes/proteomes we were able to explore signatures of adaptation to three environmental factors, pH, salinity, and temperature, observing major trends in compositions of their nucleic acids and proteins. We derived predictors of thermostability, halophilic, and pH adaptations and complemented them by the principal components analysis. We observed a clear difference between thermophilic and salinity/pH adaptations, whereas latter invoke seemingly overlapping mechanisms. The genome-proteome compositional trade-off reveals an intricate balance between the work of base paring and base stacking in stabilization of coding DNA and r/tRNAs, and, at the same time, universal requirements for the stability and foldability of proteins regardless of the nucleotide biases. Nevertheless, we still found hidden fingerprints of ancient evolutionary connections between the nucleotide and amino acid compositions indicating their emergence, mutual evolution, and adjustment. The evolutionary perspective on the adaptation mechanisms is further studied here by means of the comparative analysis of genomic/proteomic traits of archaeal and bacterial species. The overall picture of genomic/proteomic signals of adaptation obtained here provides a foundation for future engineering and design of functional biomolecules resistant to harsh environments.

A Hydrolase Produced by Rhodococcus erythropolis HQ Is Responsible for the Detoxification of Zearalenone

Zearalenone (ZEN), an estrogenic mycotoxin, is one of the prevalent contaminants found in food and feed, posing risks to human and animal health. In this study, we isolated a ZEN-degrading strain from soil and identified it as Rhodococcus erythropolis HQ. Analysis of degradation products clarified the mechanism by which R. erythropolis HQ degrades ZEN. The gene zenR responsible for degrading ZEN was identified from strain HQ, in which zenR is the key gene for R. erythropolis HQ to degrade ZEN, and its expression product is a hydrolase named ZenR. ZenR shared 58% sequence identity with the hydrolase ZenH from Aeromicrobium sp. HA, but their enzymatic properties were significantly different. ZenR exhibited maximal enzymatic activity at pH 8.0-9.0 and 55 °C, with a Michaelis constant of 21.14 μM, and its enzymatic activity is 2.8 times that of ZenH. The catalytic triad was identified as S132-D157-H307 via molecular docking and site-directed mutagenesis. Furthermore, the fermentation broth of recombinant Bacillus containing ZenR can be effectively applied to liquefied corn samples, with the residual amount of ZEN decreased to 0.21 μg/g, resulting in a remarkable ZEN removal rate of 93%. Thus, ZenR may serve as a new template for the modification of ZEN hydrolases and a new resource for the industrial application of biological detoxification. Consequently, ZenR could potentially be regarded as a novel blueprint for modifying ZEN hydrolases and as a fresh resource for the industrial implementation of biological detoxification.

Acid-resistant enzymes: the acquisition strategies and applications

Enzymes have promising applications in chemicals, food, pharmaceuticals, and other variety products because of their high efficiency, specificity, and environmentally friendly properties. However, due to the complexity of raw materials, pH, temperature, solvents, etc., the application range of enzymes is greatly limited in the industry. Protein engineering and enzyme immobilization are classical strategies to overcome the limitations of industrial applications. Although the pH tendency of enzymes has been extensively researched, the mechanism underlying enzyme acid resistance is unclear, and a less practical strategy for altering the pH propensity of enzymes has been suggested. This review proposes that the optimum pH of enzyme is determined by the pKa values of active center ionizable amino acid residues. Three levels of acquiring acid-resistant enzymes are summarized: mining from extreme environments and enzyme databases, modification with protein engineering and enzyme microenvironment engineering, and de novo synthesis. The industrial applications of acid-resistant enzymes in chemicals, food, and pharmaceuticals are also summarized. KEY POINTS: • The mechanism of enzyme acid resistance is fundamentally determined. • The three aspects of the method for acquiring acid-resistant enzymes are summarized. • Computer-aided strategies and artificial intelligence are used to obtain acid-resistant enzymes.

Development of thermostable dextranase from Streptococcus mutans (SmdexTM) through in silico design employing B-factor and Cartesian-ΔΔG

The thermal stability of enzymes dramatically limits their application in the industrial field. Based on the crystal structure, we conducted a semi-rational design according to the B-factor and free energy values to improve the stability of dextranase from Streptococcus mutans (SmdexTM). The B-factor values of Asn102, Asn503, Asp501 and Asp500 were the highest predicted by B-FITTER. Then Rosetta was used to simulate the saturation mutations of Asn102, Asn503, Asp501 and Asp500. The mutated amino acid was designed according to the change of acG. The results showed that the thermal stability of N102P, N102C, D500G, and D500T was improved, and the half-lives of N102P/D500G and N102P/D500T at 45 °C were increased to 3.14 times and 2.44 times, respectively. Analyzing the interaction of amino acids by using Discovery Studio 4.5, it was observed that the thermal stability of dextranase was improved due to the increase in hydrophobicity and the number of hydrogen bonds of the mutant enzyme. The catalytic efficiency of N102P/D500T was increased. Compared with the hydrolyzed products of SmdexTM, the mutant enzymes do not change the specificity of hydrolysates.

Improving the activity and synergistic catalysis of l-aspartate β-decarboxylase by arginine introduction on the surface

Introduction of arginine on the surface relieved the pH-dependent inactivation of l-aspartate-β-decarboxylase, which promoted its application in synthetic biology and biocatalysis.

A Brief History of Colour, the Environmental Impact of Synthetic Dyes and Removal by Using Laccases

The history of colour is fascinating from a social and artistic viewpoint because it shows the way; use; and importance acquired. The use of colours date back to the Stone Age (the first news of cave paintings); colour has contributed to the social and symbolic development of civilizations. Colour has been associated with hierarchy; power and leadership in some of them. The advent of synthetic dyes has revolutionized the colour industry; and due to their low cost; their use has spread to different industrial sectors. Although the percentage of coloured wastewater discharged by the textile; food; pharmaceutical; cosmetic; and paper industries; among other productive areas; are unknown; the toxic effect and ecological implications of this discharged into water bodies are harmful. This review briefly shows the social and artistic history surrounding the discovery and use of natural and synthetic dyes. We summarise the environmental impact caused by the discharge of untreated or poorly treated coloured wastewater to water bodies; which has led to physical; chemical and biological treatments to reduce the colour units so as important physicochemical parameters. We also focus on laccase utility (EC 1.10.3.2), for discolouration enzymatic treatment of coloured wastewater, before its discharge into water bodies. Laccases (p-diphenol: oxidoreductase dioxide) are multicopper oxidoreductase enzymes widely distributed in plants, insects, bacteria, and fungi. Fungal laccases have employed for wastewater colour removal due to their high redox potential. This review includes an analysis of the stability of laccases, the factors that influence production at high scales to achieve discolouration of high volumes of contaminated wastewater, the biotechnological impact of laccases, and the degradation routes that some dyes may follow when using the laccase for colour removal.

Recombinant laccase rPOXA 1B real-time, accelerated and molecular dynamics stability study

Background

Laccases (EC 1.10.3.2) are multi-copper oxidoreductases with great biotechnological importance due to their high oxidative potential and utility for removing synthetic dyes, oxidizing phenolic compounds, and degrading pesticides, among others.

Methods

A real-time stability study (RTS) was conducted for a year, by using enzyme concentrates from 3 batches (L1, L3, and L4). For which, five temperatures 243.15, 277.15, 298.15, 303.15, 308.15, and 313.15 K were assayed. Using RTS data and the Arrhenius equation, we calculated the rPOXA 1B accelerated stability (AS). Molecular dynamics (MD) computational study results were very close to those obtained experimentally at four different temperatures 241, 278, 298, and 314 K.

Results

In the RTS, 101.16, 115.81, 75.23, 46.09, 5.81, and 4.83% of the relative enzyme activity were recovered, at respective assayed temperatures. AS study, showed that rPOXA 1B is stable at 240.98 ± 5.38, 277.40 ± 1.32 or 297.53 ± 3.88 K; with t_1/2 values of 230.8, 46.2, and 12.6 months, respectively. Kinetic and thermodynamic parameters supported the high stability of rPOXA 1B, with an E_d value of 41.40 KJ mol^− 1, a low variation of K_M and V_max, at 240.98 ± 5.38, and 297.53 ± 3.88 K, and ∆G values showing deactivation reaction does not occur. The MD indicates that fluctuations in loop, coils or loops with hydrophilic or intermediate polarity amino acids as well as in some residues of POXA 1B 3D structure, increases with temperature; changing from three fluctuating residues at 278 K to six residues at 298 K, and nine residues at 314 K.

Conclusions

Laccase rPOXA 1B demonstrated experimentally and computationally to be a stable enzyme, with t_1/2 of 230.8, 46.2 or 12.6 months, if it is preserved impure without preservatives at temperatures of 240.98 ± 5.38, 277.40 ± 1.32 or 297.53 ± 3.88 K respectively; this study could be of great utility for large scale producers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12896-021-00698-3.

An alkali-tolerant phospholipase D from Sphingobacterium thalpophilum 2015: Gene cloning, overproduction and characterization

The phospholipase pl-S.t gene of Sphingobacterium thalpophilum 2015 was cloned and the gene sequence was submitted to NCBI with Accession Number KX674735.1. The phylogenetic analysis showed that this PL-S.t was clustered to phospholipase D (PLD). As far as we know, the PL-S.t with a molecular mass of 22.5 kDa is the lowest of the currently purified bacterial PLDs, which belongs to a non-HKD PLD enzyme. This PL-S.t was resistant to a wide range of alkali pHs (7.5-9.0) after 1 h incubation, retaining more than 90% of its maximum activity. The PL-S.t activity can be enhanced by Ni²⁺, Co²⁺ and Mn²⁺. This PL-S.t has only one cysteine residue and fewer negatively-charged amino acids (AAs). The hydrogen bonds network was found around the cystein108, which may be beneficial to the stability and activity of PL-S.t in Ni²⁺ solution. This study has laid the foundation for further research on the molecular mechanism of the catalytic characteristics of low molecular weight alkalic PLD from S. thalpophilum 2015.

Mustguseal and Sister Web-Methods: A Practical Guide to Bioinformatic Analysis of Protein Superfamilies

Bioinformatic analysis of functionally diverse superfamilies can help to study the structure-function relationship in proteins, but represents a methodological challenge. The Mustguseal web-server can build large structure-guided sequence alignments of thousands of homologs that cover all currently available sequence variants within a common structural fold. The input to the method is a PDB code of the query protein, which represents the protein superfamily of interest. The collection and subsequent alignment of protein sequences and structures is fully automated and driven by the particular choice of parameters. Four integrated sister web-methods-the Zebra, pocketZebra, visualCMAT, and Yosshi-are available to further analyze the resulting superimposition and identify conserved, subfamily-specific, and co-evolving residues, as well as to classify and study disulfide bonds in protein superfamilies. The integration of these web-based bioinformatic tools provides an out-of-the-box easy-to-use solution, first of its kind, to study protein function and regulation and design improved enzyme variants for practical applications and selective ligands to modulate their functional properties. In this chapter, we provide a step-by-step protocol for a comprehensive bioinformatic analysis of a protein superfamily using a web-browser as the main tool and notes on selecting the appropriate values for the key algorithm parameters depending on your research objective. The web-servers are freely available to all users at https://biokinet.belozersky.msu.ru/m-platform with no login requirement.

Enhancement of laccase immobilization onto wet chitosan microspheres using an iterative protocol and its potential to remove micropollutants

This study was focused on creating a new and effective immobilization method for Trametes versicolor laccase (Lc) by using chitosan (CS) microspheres activated with 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride. The activation of the support alternated with immobilization of the enzyme, in repetitive procedures, led to obtaining three different products. Also, the physicochemical properties of the new products were investigated and compared with those of free laccase. The discoloration and reusability properties of the immobilized Lc were evaluated using indigo carmine (IC) as a model micropollutant. The ESEM and FT-IR methods demonstrated that the Lc was successfully immobilized. The relative reaction rate and the total amount of immobilized Lc were tripled using the iterative protocol as proved by specific and Bradford assays. The maximum amount of immobilized Lc was 8.4 mg Lc/g CS corresponding to the third immobilization procedure. Compared to the free Lc, the operational stability of the immobilized Lc was significantly improved, presenting a maximum activity plateau over a pH range of 3-5 and a temperature range of 25-50 °C. The thermal inactivation study at 55 °C proved that the immobilized enzyme is three times more stable than the free Lc. The isoconversional and Michaelis-Menten methods showed that the immobilization did not affect the enzyme catalytic properties. After 32 days of storage, the residual activities are 85% for the immobilized laccase and 40% for the free one. In similar conditions, the free and immobilized Lc (2.12 x 10^-6 M) completely decolorized IC (7.15 x 10^-5 M) within 14 min. The immobilized Lc activity remained almost constant (80%) during 10 reusability cycles. All these results highlight the substantial advantages of the new immobilization protocol and demonstrate that immobilized Lc can be used as a promising micropollutant removal from real wastewater.

Zebra2: advanced and easy-to-use web-server for bioinformatic analysis of subfamily-specific and conserved positions in diverse protein superfamilies

Zebra2 is a highly automated web-tool to search for subfamily-specific and conserved positions (i.e. the determinants of functional diversity as well as the key catalytic and structural residues) in protein superfamilies. The bioinformatic analysis is facilitated by Mustguseal—a companion web-server to automatically collect and superimpose a large representative set of functionally diverse homologs with high structure similarity but low sequence identity to the selected query protein. The results are automatically prioritized and provided at four information levels to facilitate the knowledge-driven expert selection of the most promising positions on-line: as a sequence similarity network; interfaces to sequence-based and 3D-structure-based analysis of conservation and variability; and accompanied by the detailed annotation of proteins accumulated from the integrated databases with links to the external resources. The integration of Zebra2 and Mustguseal web-tools provides the first of its kind out-of-the-box open-access solution to conduct a systematic analysis of evolutionarily related proteins implementing different functions within a shared 3D-structure of the superfamily, determine common and specific patterns of function-associated local structural elements, assist to select hot-spots for rational design and to prepare focused libraries for directed evolution. The web-servers are free and open to all users at https://biokinet.belozersky.msu.ru/zebra2, no login required.

Computational Analysis of the Primary and Secondary Structure of Amidases in Relation to their pH Adaptation

Background:

Amidases are ubiquitous enzymes and biological functions of these enzymes vary widely. They are considered to be synergistically involved in the synthesis of a wide variety of carboxylic acids, hydroxamic acids and hydrazides, which find applications in commodity chemicals synthesis, pharmaceuticals agrochemicals and wastewater treatments.

Methods:

They hydrolyse a wide variety of amides (short-chain aliphatic amides, mid-chain amides, arylamides, α-aminoamides and α-hydroxyamides) and can be grouped on the basis of their catalytic site and preferred substrate. Despite their economic importance, we lack knowledge as to how these amidases withstand elevated pH and temperature whereas others cannot.

Results:

The present study focuses on the statistical comparison between the acid-tolerant, alkali tolerant and neutrophilic organisms. In silico analysis of amidases of acid-tolerant, alkali tolerant and neutrophilic organisms revealed some striking trends as to how amino acid composition varies significantly. Statistical analysis of primary and secondary structure revealed amino acid trends in amidases of these three groups of bacteria. The abundance of isoleucine (Ile, I) in acid-tolerant and leucine (Leu, L) in alkali tolerant showed the aliphatic amino acid dominance in extreme conditions of pH in acidtolerant and alkali tolerant amidases.

Conclusion:

The present investigation insights physiochemical properties and dominance of some crucial amino acid residues in the primary and secondary structure of some amidases from acid-tolerant, alkali tolerant and neutrophilic microorganisms.

Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design

Rab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.

Mustguseal: a server for multiple structure-guided sequence alignment of protein families

Motivation

Comparative analysis of homologous proteins in a functionally diverse superfamily is a valuable tool at studying structure-function relationship, but represents a methodological challenge.

Results

The Mustguseal web-server can automatically build large structure-guided sequence alignments of functionally diverse protein families that include thousands of proteins basing on all available information about their structures and sequences in public databases. Superimposition of protein structures is implemented to compare evolutionarily distant relatives, whereas alignment of sequences is used to compare close homologues. The final alignment can be downloaded for a local use or operated on-line with the built-in interactive tools and further submitted to the integrated sister web-servers of Mustguseal to analyze conserved, subfamily-specific and co-evolving residues at studying a protein function and regulation, designing improved enzyme variants for practical applications and selective ligands to modulate functional properties of proteins.

Availability and implementation

Freely available on the web at https://biokinet.belozersky.msu.ru/mustguseal.

Contact

vytas@belozersky.msu.ru.

Supplementary information

Supplementary data are available at Bioinformatics online.

Tuning the pH profile of β-glucuronidase by rational site-directed mutagenesis for efficient transformation of glycyrrhizin

In this study, we aimed to shift the optimal pH of acidic β-glucuronidase from Aspergillus oryzae Li-3 (PGUS) to the neutral region by site-directed mutagenesis, thus allowing high efficient biotransformation of glycyrrhizin (GL) into glycyrrhetinic acid (GA) under higher pH where the solubility of GL could be greatly enhanced. Based on PGUS structure analysis, five critical aspartic acid and glutamic acid residues were replaced with arginine on the surface to generate a variant 5Rs with optimal pH shifting from 4.5 to 6.5. The catalytic efficiency (k_cat /K_m) value of 5Rs at pH 6.5 was 10.7-fold higher than that of PGUS wild-type at pH 6.5, even 1.4-fold higher than that of wild-type at pH 4.5. Molecular dynamics simulation was performed to explore the molecular mechanism for the shifted pH profile and enhanced pH stability of 5Rs.

Biophysical characterization of a recombinant lipase KV1 from Acinetobacter haemolyticus in relation to pH and temperature

Spectroscopic and calorimetric methods were employed to assess the stability and the folding aspect of a novel recombinant alkaline-stable lipase KV1 from Acinetobacter haemolyticus under varying pH and temperature. Data on far ultraviolet-circular dichroism of recombinant lipase KV1 under two alkaline conditions (pH 8.0 and 12.0) at 40 °C reveal strong negative ellipticities at 208, 217, 222 nm, implying its secondary structure belonging to a α + β class with 47.3 and 39.0% ellipticity, respectively. Results demonstrate that lipase KV1 adopts its most stable conformation at pH 8.0 and 40 °C. Conversely, the protein assumes a random coil structure at pH 4.0 and 80 °C, evident from a strong negative peak at ∼ 200 nm. This blue shift suggests a general decline in enzyme activity in conjunction with the partially or fully unfolded state that invariably exposed more hydrophobic surfaces of the lipase protein. The maximum emission at ∼335 nm for pH 8.0 and 40 °C indicates the adoption of a favorable protein conformation with a high number of buried tryptophan residues, reducing solvent exposure. Appearance of an intense Amide I absorption band at pH 8.0 corroborates an intact secondary structure. A lower enthalpy value for pH 4.0 over pH 8.0 and 12.0 in the differential scanning calorimetric data corroborates the stability of the lipase at alkaline conditions, while a low K_m (0.68 ± 0.03 mM) for tributyrin verifies the high affinity of lipase KV1 for the substrate. The data, herein offer useful insights into future structure-based tunable catalytic activity of lipase KV1.

Molecular Docking Analysis and Biochemical Evaluation of Levansucrase from Sphingobium chungbukense DJ77

Bacterial exopolymer Levan (β-(2,6) polyfructan) synthesized by levansucrase has attracted interest for various applications due to its low intrinsic viscosity compared with other polysaccharides. We report a novel levansucrase (Lsc) isolated from Sphingobium chunbukense DJ77 and verify its biochemical characteristics by comparative analysis of molecular docking analysis (MOE) and catalytic residue analysis. The complete sequence of the Lsc encoding gene ( lsc) was cloned under the direction of the T7 promoter and purified in an Escherichia coli BL21 (DE3) protein expression system. The enzyme activity analysis and ligand docking MOE study of S. chungbukense DJ77 Lsc revealed that Arg 77, Ser112, Arg 195, Asp196, Glu257, and Gln275 were involved in the sucrose binding and splitting as well as transfructosylation activity. A catalytic comparison of Lsc of S. chungbukense DJ77 with the results of site-directed mutational analysis indicated that Gln275 may coordinate a favorable substrate binding environment, offering broad pH resistance in the range of 5-10. The results suggest that the recombinant E. coli carrying S. chungbukense DJ77 Lsc might produce levan under the regular growth conditions with less need for pH manipulation.

Redesigning pH optimum of Geobacillus sp. TF16 endoxylanase through in silico designed DNA swapping strategy

Thermoalkaliphilic xylanases are highly desired and of great importance due to their vast potential in paper pulp and bleaching processes. Here, we report rapid, cost-effective, and result-oriented combinatorial potential of in silico DNA swapping strategy to engineer the pH optimum of industrially crucial enzymes, particularly engineering of Geobacillus sp. TF16 endoxylanase for alkaline environments. The 3D structures of Geobacillus sp. TF16 and donor Bacillus halodurans C-125 endoxylanases were firstly predicted, analyzed, and compared for their similarities before any in silico design of mutants. Reasonably, to improve its alkaline pH tolerance, the corresponding regions in Geobacillus sp.TF16 endoxylanase were further engineered by swapping with negatively-charged amino acid-rich regions from B. halodurans C-125 endoxylanase. Through only two of four in silico-designed mutants, the optimum pH of GeoTF16 endoxylanase was improved from 8.5 to 10.0. Moreover, as compared to GeoTF16 parental enzyme, both GeoInt3 and GeoInt4 mutants revealed (i) enhanced biobleaching performance, (ii) improved adaptability to alkaline conditions, and (iii) better activity for broader pH range. Unlike GeoTF16 losing activity at pH 11.0 completely, GeoInt4 retained 60% and 40% of its activity at pH 11.0 and 12.0, respectively. Thus, GeoInt4 stands out as a more competent biocatalyst that is suitable for alkaline environments of diverse industrial applications. The current study represents an efficient protein engineering strategy to adapt industrial catalysts to diverse processing conditions. Further comprehensive and fine-tuned research efforts may result in biotechnologically more promising outcomes.

Multifactorial level of extremostability of proteins: can they be exploited for protein engineering?

Research on extremostable proteins has seen immense growth in the past decade owing to their industrial importance. Basic research of attributes related to extreme-stability requires further exploration. Modern mechanistic approaches to engineer such proteins in vitro will have more impact in industrial biotechnology economy. Developing a priori knowledge about the mechanism behind extreme-stability will nurture better understanding of pathways leading to protein molecular evolution and folding. This review is a vivid compilation about all classes of extremostable proteins and the attributes that lead to myriad of adaptations divulged after an extensive study of 6495 articles belonging to extremostable proteins. Along with detailing on the rationale behind extreme-stability of proteins, emphasis has been put on modern approaches that have been utilized to render proteins extremostable by protein engineering. It was understood that each protein shows different approaches to extreme-stability governed by minute differences in their biophysical properties and the milieu in which they exist. Any general rule has not yet been drawn regarding adaptive mechanisms in extreme environments. This review was further instrumental to understand the drawback of the available 14 stabilizing mutation prediction algorithms. Thus, this review lays the foundation to further explore the biophysical pleiotropy of extreme-stable proteins to deduce a global prediction model for predicting the effect of mutations on protein stability.

Insights from molecular dynamics simulations for computational protein design

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.

Rapid enzyme regeneration results in the striking catalytic longevity of an engineered, single species, biocatalytic biofilm

BACKGROUND

Engineering of single-species biofilms for enzymatic generation of fine chemicals is attractive. We have recently demonstrated the utility of an engineered Escherichia coli biofilm as a platform for synthesis of 5-halotryptophan. E. coli PHL644, expressing a recombinant tryptophan synthase, was employed to generate a biofilm. Its rapid deposition, and instigation of biofilm formation, was enforced by employing a spin-down method. The biofilm presents a large three-dimensional surface area, excellent for biocatalysis. The catalytic longevity of the engineered biofilm is striking, and we had postulated that this was likely to largely result from protection conferred to recombinant enzymes by biofilm's extracellular matrix. SILAC (stable isotopic labelled amino acids in cell cultures), and in particular dynamic SILAC, in which pulses of different isotopically labelled amino acids are administered to cells over a time course, has been used to follow the fate of proteins. To explore within our spin coated biofilm, whether the recombinant enzyme's longevity might be in part due to its regeneration, we introduced pulses of isotopically labelled lysine and phenylalanine into medium overlaying the biofilm and followed their incorporation over the course of biofilm development.

RESULTS

Through SILAC analysis, we reveal that constant and complete regeneration of recombinant enzymes occurs within spin coated biofilms. The striking catalytic longevity within the biofilm results from more than just simple protection of active enzyme by the biofilm and its associated extracellular matrix. The replenishment of recombinant enzyme is likely to contribute significantly to the catalytic longevity observed for the engineered biofilm system.

CONCLUSIONS

Here we provide the first evidence of a recombinant enzyme's regeneration in an engineered biofilm. The recombinant enzyme was constantly replenished over time as evidenced by dynamic SILAC, which suggests that the engineered E. coli biofilms are highly metabolically active, having a not inconsiderable energetic demand. The constant renewal of recombinant enzyme highlights the attractive possibility of utilising this biofilm system as a dynamic platform into which enzymes of interest can be introduced in a "plug-and-play" fashion and potentially be controlled through promoter switching for production of a series of desired fine chemicals.

Experimental and computational studies on the unusual substrate specificity of branched-chain amino acid aminotransferase from Thermoproteus uzoniensis

PLP-Dependent fold-type IV branched-chain amino acid aminotransferases (BCATs) from archaea have so far been poorly characterized. A new BCAT from the hyperthermophilic archaeon Thermoproteus uzoniensis (TUZN1299) has been studied. TUZN1299 was found to be highly active toward branched-chain amino acids (BCAAs), positively charged amino acids, l-methionine, l-threonine, l-homoserine, l-glutamine, as well as toward 2-oxobutyrate and keto analogs of BCAAs, whereas l-glutamate and α-ketoglutarate were not converted in the overall reaction. According to stopped-flow experiments, the enzyme showed the highest specificity to BCAAs and their keto analogs. In order to explain the molecular mechanism of the unusual specificity of TUZN1299, bioinformatic analysis was implemented to identify the subfamily-specific positions in the aminotransferase class IV superfamily of enzymes. The role of the selected residues in binding of various ligands in the active site was further studied using molecular modeling. The results indicate that Glu188 forms a novel binding site for positively charged and polar side-chains of amino acids. Lack of accommodation for α-ketoglutarate and l-glutamate is due to the unique orientation and chemical properties of residues 102-106 in the loop forming the A-pocket. The likely functional roles of TUZN1299 in cellular metabolism - in the synthesis and degradation of BCAAs - are discussed.

Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer

Rapid expansion of online resources providing access to genomic, structural, and functional information associated with biological macromolecules opens an opportunity to gain a deeper understanding of the mechanisms of biological processes due to systematic analysis of large datasets. This, however, requires novel strategies to optimally utilize computer processing power. Some methods in bioinformatics and molecular modeling require extensive computational resources. Other algorithms have fast implementations which take at most several hours to analyze a common input on a modern desktop station, however, due to multiple invocations for a large number of subtasks the full task requires a significant computing power. Therefore, an efficient computational solution to large-scale biological problems requires both a wise parallel implementation of resource-hungry methods as well as a smart workflow to manage multiple invocations of relatively fast algorithms. In this work, a new computer software mpiWrapper has been developed to accommodate non-parallel implementations of scientific algorithms within the parallel supercomputing environment. The Message Passing Interface has been implemented to exchange information between nodes. Two specialized threads — one for task management and communication, and another for subtask execution — are invoked on each processing unit to avoid deadlock while using blocking calls to MPI. The mpiWrapper can be used to launch all conventional Linux applications without the need to modify their original source codes and supports resubmission of subtasks on node failure. We show that this approach can be used to process huge amounts of biological data efficiently by running non-parallel programs in parallel mode on a supercomputer. The C++ source code and documentation are available from http://biokinet.belozersky.msu.ru/mpiWrapper .

Sequence and structure-based comparative analysis to assess, identify and improve the thermostability of penicillin G acylases

Penicillin acylases are enzymes employed by the pharmaceutical industry for the manufacture of semi-synthetic penicillins. There is a continuous demand for thermostable and alkalophilic enzymes in such applications. We have carried out a computational analysis of known penicillin G acylases (PGAs) in terms of their thermostable nature using various protein-stabilizing factors. While the presence of disulfide bridges was considered initially to screen putative thermostable PGAs from the database, various other factors such as high arginine to lysine ratio, less content of thermolabile amino acids, presence of proline in β-turns, more number of ion-pair and other non-bonded interactions were also considered for comparison. A modified consensus approach designed could further identify stabilizing residue positions by site-specific comparison between mesostable and thermostable PGAs. A most likely thermostable enzyme identified from the analysis was PGA from Paracoccus denitrificans (PdPGA). This was cloned, expressed and tested for its thermostable nature using biochemical and biophysical experiments. The consensus site-specific sequence-based approach predicted PdPGA to be more thermostable than Escherichia coli PGA, but not as thermostable as the PGA from Achromobacter xylosoxidans. Experimental data showed that PdPGA was comparatively less thermostable than Achromobacter xylosoxidans PGA, although thermostability factors favored a much higher stability. Despite being mesostable, PdPGA being active and stable at alkaline pH is an advantage. Finally, several residue positions could be identified in PdPGA, which upon mutation selectively could improve the thermostability of the enzyme.

Study of Functional and Allosteric Sites in Protein Superfamilies

The interaction of proteins (enzymes) with a variety of low-molecular-weight compounds, as well as protein-protein interactions, is the most important factor in the regulation of their functional properties. To date, research effort has routinely focused on studying ligand binding to the functional sites of proteins (active sites of enzymes), whereas the molecular mechanisms of allosteric regulation, as well as binding to other pockets and cavities in protein structures, remained poorly understood. Recent studies have shown that allostery may be an intrinsic property of virtually all proteins. Novel approaches are needed to systematically analyze the architecture and role of various binding sites and establish the relationship between structure, function, and regulation. Computational biology, bioinformatics, and molecular modeling can be used to search for new regulatory centers, characterize their structural peculiarities, as well as compare different pockets in homologous proteins, study the molecular mechanisms of allostery, and understand the communication between topologically independent binding sites in protein structures. The establishment of an evolutionary relationship between different binding centers within protein superfamilies and the discovery of new functional and allosteric (regulatory) sites using computational approaches can improve our understanding of the structure-function relationship in proteins and provide new opportunities for drug design and enzyme engineering.

Engineering protocells: prospects for self-assembly and nanoscale production-lines

The increasing ease of producing nucleic acids and proteins to specification offers potential for design and fabrication of artificial synthetic "organisms" with a myriad of possible capabilities. The prospects for these synthetic organisms are significant, with potential applications in diverse fields including synthesis of pharmaceuticals, sources of renewable fuel and environmental cleanup. Until now, artificial cell technology has been largely restricted to the modification and metabolic engineering of living unicellular organisms. This review discusses emerging possibilities for developing synthetic protocell "machines" assembled entirely from individual biological components. We describe a host of recent technological advances that could potentially be harnessed in design and construction of synthetic protocells, some of which have already been utilized toward these ends. More elaborate designs include options for building self-assembling machines by incorporating cellular transport and assembly machinery. We also discuss production in miniature, using microfluidic production lines. While there are still many unknowns in the design, engineering and optimization of protocells, current technologies are now tantalizingly close to the capabilities required to build the first prototype protocells with potential real-world applications.