Protein Thermostability Research Articles

Analysis of Protein Inhibitors of Trypsin in Quinoa, Amaranth and Lupine Seeds. Selection and Deep Structure–Function Characterization of the Amaranthus caudatus Species

Protease inhibitors are biomolecules with growing biotechnological and biomedical relevance, including those derived from plants. This study investigated strong trypsin inhibitors in quinoa, amaranth, and lupine seeds, plant grains traditionally used in Andean South America. Amaranth seeds displayed the highest trypsin inhibitory activity, despite having the lowest content of aqueous soluble and thermostable protein material. This activity, directly identified by enzymatic assay, HPLC, intensity-fading mass spectrometry (IF-MS), and MS/MS, was attributed to a single protein of 7889.1 Da, identified as identical in Amaranthus caudatus and A. hybridus, with a Ki of 1.2 nM for the canonical bovine trypsin. This form of the inhibitor, which is highly homogeneous and scalable, was selected, purified, and structurally–functionally characterized due to the high nutritional quality of amaranth seeds as well as its promising agriculture–biotech–biomed applicability. The protein was crystallized in complex with bovine trypsin, and its 3D crystal structure resolved at 2.85 Å, revealing a substrate-like transition state interaction. This verified its classification within the potato I inhibitor family. It also evidenced that the single disulfide bond of the inhibitor constrains its binding loop, which is a key feature. Cell culture assays showed that the inhibitor did not affect the growth of distinct plant microbial pathogen models, including diverse bacteria, fungi, and parasite models, such as Mycoplasma genitalium and Plasmodium falciparum. These findings disfavour the notion that the inhibitor plays an antimicrobial role, favouring its potential as an agricultural insect deterrent and prompting a redirection of its functional research.

Trehalose decorated nanostructures stabilize combined cross-linked enzyme aggregates (Combi-CLEAs) of β-galactosidase and glucose isomerase.

Combined cross-linked enzyme aggregates (Combi-CLEAs) of β-Galactosidase (β-Gal) and Glucose Isomerase (GI) allow the transformation of d-lactose to lactose-fructose syrup through one-pot cascade biocatalytic reactions. Despite its promise, the low thermostability of β-Gal and high-temperature demands for GI limits this application. Trehalose is a protein-stabilizing disaccharide which has been utilized in immobilized enzyme systems to enhance protein thermostability. In this work, trehalose decorated poly (amidoamine) (PAMAM) dendrimers were synthesized at low and high surface coverage levels (10 % and 50 %) and used to stabilize Combi-CLEAs of β-Gal and GI. Addition of trehalose decorated nanostructures to β-Gal and GI Combi-CLEAs enhanced β-Gal performance at elevated temperatures (58.6 % higher activity and 2.26× higher stability) while maintaining GI performance of Combi-CLEAs. The resulting Combi-CLEAs containing trehalose decorated nanostructures retained ~40 % β-Gal activity following 7 consecutive reaction cycles and exhibited GI activity for 5 consecutive reaction cycles. Overall, this study demonstrates the potential of trehalose decorated nanostructures to stabilize proteins at elevated temperatures typical of bioprocessing applications and storage of therapeutics.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost.

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

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.

Antibacterial activity of lactobacilli from meat

To highlight the role of lactic acid bacteria in meat safeguarding, bacteria from various types of local red meats (Annaba- Algeria) preserved under various conditions were isolated and characterized. Isolation was limited to lactobacilli and some types of spoilage and pathogenic bacteria. The characterization of the isolated strains was done by means of physiological and biochemical identification tests. Various methods were considered to characterize the antimicrobial activities of the 29 isolated lactobacilli strains from 19 samples. The results revealed that the isolated lactobacilli strains produce and excrete in the culture medium substances showing important inhibiting activities towards Gram positive and Gram negative bacteria. These activities are due to various molecules, but varied according to the lactobacilli and the considered bacteria. Inhibition by lactic acid and H2O2 was observed for the Gram+ and the Gram-, except for Pseudomonas. Bacteriocin inhibition was especially observed for the Gram+, while among the Gram-, only Salmonella was inhibited. Bacteriocin activity towards S. aureus was confirmed for eight strains of lactobacilli, resulting from standard thermostable extracellular proteins for six of them. This study shows that the isolated lactobacilli present important antibacterial activities, which suggested that they can be used for a better conservation of fresh meat, in order to preserve its microbiological quality; since they are already widely used in Europe for the fermentation of meat products like dry sausage.

HyperMPNN-A general strategy to design thermostable proteins learned from hyperthermophiles.

Stability is a key factor to enable the use of recombinant proteins in therapeutic or biotechnological applications. Deep learning protein design approaches like ProteinMPNN have shown strong performance both in creating novel proteins or stabilizing existing ones. However, it is unlikely that the stability of the designs will significantly exceed that of the natural proteins in the training set, which are biophysically only marginally stable. Therefore, we collected predicted protein structures from hyperthermophiles, which differ substantially in their amino acid composition from mesophiles. Notably, ProteinMPNN fails to recover their unique amino acid composition. Here we show that a retrained network on predicted proteins from hyperthermophiles, termed HyperMPNN, not only recovers this unique amino acid composition but can also be applied to proteins from non-hyperthermophiles. Using this novel approach on a protein nanoparticle with a melting temperature of 65°C resulted in designs remaining stable at 95°C. In conclusion, we created a new way to design highly thermostable proteins through self-supervised learning on data from hyperthermophiles.

Structure-based design of covalent nanobody binders for a thermostable green fluorescence protein

Structure-based design of covalent nanobody binders for a thermostable green fluorescence protein

Thermostable phenylacetic acid degradation protein TtPaaI from Thermus thermophilus as a scaffold for tetravalent display of proteins

Numerous proteins in nature strictly require oligomerization for their full activity. Moreover, the function of natural and artificial proteins can me adjusted by altering their oligomeric state, leading to development of biotechnologically-relevant biomacromolecules. Oligomerization scaffolds from natural sources and designed de novo enable shuffling the oligomeric state and valency of biomacromolecules. In this report we probed the scaffolding potential of the thermostable phenylacetic acid degradation protein acyl-CoA from Thermus thermophilus (TtPaaI). We designed and successfully produced the fusion protein between TtPaaI (scaffold) and galectin-7, a multifunctional lectin implicated in human diseases (ligand) and demonstrated that TtPaaI can serve as a framework for functional multivalent display of ligands.

Directed Evolution of an Artificial Hydroxylase Based on a Thermostable Human Carbonic Anhydrase Protein

Directed Evolution of an Artificial Hydroxylase Based on a Thermostable Human Carbonic Anhydrase Protein

A Thermostable Heme Protein Fold Adapted for Stereoselective C-H Bond Hydroxylation Using Peroxygenase Activity.

Thermostable protein folds of natural and synthetic origin are highly sought-after templates for biocatalyst generation due to their enhanced stability to elevated temperatures which overcomes one of the major limitations of applying enzymes for synthesis. Cytochrome P450 enzymes (CYPs) are a family of heme-thiolate monooxygenases that catalyse the oxidation of their substrates in a highly stereo- and regio-selective manner. The CYP enzyme (CYP107PQ1) from the thermophilic bacterium Meiothermus ruber binds the norisoprenoid β-ionone and was employed as a scaffold for catalyst design. The I-helix was modified to convert this enzyme from a monooxygenase into a peroxygenase (CYP107PQ1QE), enabling the enantioselective oxidation of β-ionone to (S)-4-hydroxy-β-ionone (94 % e.e.). The enzyme was resistant to 20 mM H2O2, 20 % (v/v) of organic solvent, supported over 1700 turnovers and was fully functional after incubation at 60 °C for 1 h and 30 °C for 365 days. The reaction was scaled-up to generate multi milligram quantities of the product for characterisation. Overall, we demonstrate that sourcing a CYP protein fold from an extremophile enabled the design of a highly stable enzyme for stereoselective C-H bond activation only using H2O2 as the oxidant, providing a viable strategy for future biocatalyst design.

More is not always better. Multiple carbohydrate-binding domains for efficient starch hydrolysis

Lactobacillus amylovorus α-amylase is an endoenzyme with a peculiar starch-binding domain containing five identical family 26 carbohydrate-binding modules (CBM26). To investigate the impact of CBMs on catalytic activity, C-terminally truncated derivatives were constructed. The catalytic domain alone shows low affinity for the substrate and a very slow reaction rate, highlighting the importance of CBMs in maintaining the enzyme's optimal conformation and dynamics for efficient catalysis. CBMs enhance enzyme performance, as indicated by improved catalytic efficiency (kcat/Km). Interestingly, the enzyme variant LaCD3CBM, with three CBMs, exhibits the best catalytic efficiency on soluble starch, outperforming the wild-type amylase, with five CBMs. In the case of insoluble starch, the catalytic domain alone could not hydrolyze it and even adding a CBM, the release of reducing sugars was very inefficient. However, this efficiency was significantly improved by two orders of magnitude for the three-CBM variant and the wild-type amylase. CBMs also played a crucial role in protein thermostability, contributing to a higher melting temperature of the catalytic domain with just a single CBM. Notably, thermostability did not increase with the number of CBMs. In conclusion, spatial arrangement and interactions between the catalytic domain and CBMs significantly influenced enzymatic efficiency with both soluble and insoluble substrates. These interactions optimize enzymatic activity and improve thermostability.

High-throughput identification of calcium-regulated proteins across diverse proteomes

Calcium ions play important roles in nearly every biological process, yet whole-proteome analysis of calcium effectors has been hindered by a lack of high-throughput, unbiased, and quantitative methods to identify protein-calcium engagement. To address this, we adapted protein thermostability assays in budding yeast, human cells, and mouse mitochondria. Based on calcium-dependent thermostability, we identified 2,884 putative calcium-regulated proteins across human, mouse, and yeast proteomes. These data revealed calcium engagement of signaling hubs and cellular processes, including metabolic enzymes and the spliceosome. Cross-species comparison of calcium-protein engagement and mutagenesis experiments identified residue-specific cation engagement, even within well-known EF-hand domains. Additionally, we found that the dienoyl-coenzyme A (CoA) reductase DECR1 binds calcium at physiologically relevant concentrations with substrate-specific affinity, suggesting direct calcium regulation of mitochondrial fatty acid oxidation. These discovery-based proteomic analyses of calcium effectors establish a key resource to dissect cation engagement and its mechanistic effects across multiple species and diverse biological processes.

QProtein: Exploring Physical Features of Protein Thermostability Based on Structural Proteomics.

Thermostability, which is essential for the functional performance of enzymes, is largely determined by intramolecular physical interactions. Although many tools have been developed, existing computational methods have struggled to find the universal principles of protein thermostability. Recent advancements in structural proteomics have been driven by the introduction of deep neural networks such as AlphaFold2 and ESMFold. These innovations have enabled the characterization of protein structures with unprecedented speed and accuracy. Here, we introduce qProtein, a Python-implemented workflow designed for the quantitative analysis of physical interactions on the scale of structural proteomics. This platform accepts protein sequences as input and produces four structural features, including hydrophobic clusters, hydrogen bonds, electrostatic interactions, and disulfide bonds. To demonstrate the use of qProtein, we investigate the structural features related to protein thermostability in six glycoside hydrolase (GH) families, comprising a total of 3,811 protein structures. Our results indicate that in five enzyme families (GH11, GH12, GH5_2, GH10, and GH48), the thermophilic enzymes have a larger average area of hydrophobic clusters compared to the nonthermophilic enzymes within each family. Furthermore, our analysis of the local-structure regions reveals that the hydrophobic clusters are predominantly distributed in the distal regions of the GH11 enzymes. In addition, the average hydrophobic cluster area of the thermophilic enzymes is significantly higher than that of the nonthermophilic enzymes in the distal regions of the GH11 enzymes. Therefore, qProtein is a well-suited platform for analyzing the structural features of thermal stability at the level of structural proteomics. We provide the source code for qProtein at https://github.com/bj600800/qProtein, and the web server is available at http://qProtein.sdu.edu.cn:8888.

Thermostable Nucleoid Protein Cren7 Slides Along DNA and Rapidly Dissociates From DNA While Not Inhibiting the Sliding of Other DNA-binding Protein

A nucleoid protein Cren7 compacts DNA, contributing to the living of Crenarchaeum in high temperature environment. In this study, we investigated the dynamic behavior of Cren7 on DNA and its functional relation using single-molecule fluorescence microscopy. We found two mobility modes of Cren7, sliding along DNA and pausing on it, and the rapid dissociation kinetics from DNA. The salt dependence analysis suggests a sliding with continuous contact to DNA, rather than hopping/jumping. The mutational analysis demonstrates that Cren7 slides along DNA while Trp (W26) residue interacts with the DNA. Furthermore, Cren7 does not impede the target search by a model transcription factor p53, implying no significant interference to other DNA-binding proteins on DNA. At high concentration of Cren7, the molecules form large clusters on DNA via bridging, which compacts DNA. We discuss how the dynamic behavior of Cren7 on DNA enables DNA-compaction and protein-bypass functions.

A High-Throughput Screening Platform for Engineering Poly(ethylene Terephthalate) Hydrolases.

The ability of enzymes to hydrolyze the ubiquitous polyester, poly(ethylene terephthalate) (PET), has enabled the potential for bioindustrial recycling of this waste plastic. To date, many of these PET hydrolases have been engineered for improved catalytic activity and stability, but current screening methods have limitations in screening large libraries, including under high-temperature conditions. Here, we developed a platform that can simultaneously interrogate PET hydrolase libraries of 104-105 variants (per round) for protein solubility, thermostability, and activity via paired, plate-based split green fluorescent protein and model substrate screens. We then applied this platform to improve the performance of a benchmark PET hydrolase, leaf-branch compost cutinase, by directed evolution. Our engineered enzyme exhibited higher catalytic activity relative to the benchmark, LCC-ICCG, on amorphous PET film coupon substrates (∼9.4% crystallinity) in pH-controlled bioreactors at both 65 °C (8.5% higher conversion at 48 h and 38% higher maximum rate, at 2.9% substrate loading) and 68 °C (11.2% higher conversion at 48 h and 43% higher maximum rate, at 16.5% substrate loading), up to 48 h, highlighting the potential of this screening platform to accelerate enzyme development for PET recycling.

The use of thermostable fluorescent proteins for live imaging in Sulfolobus acidocaldarius.

Among hyperthermophilic organisms, in vivo protein localization is challenging due to the high growth temperatures that can disrupt proper folding and function of mostly mesophilic-derived fluorescent proteins. While protein localization in the thermophilic model archaeon S. acidocaldarius has been achieved using antibodies with fluorescent probes in fixed cells, the use of thermostable fluorescent proteins for live imaging in thermophilic archaea has so far been unsuccessful. Given the significance of live protein localization in the field of archaeal cell biology, we aimed to identify fluorescent proteins for use in S. acidocaldarius. We expressed various previously published and optimized thermostable fluorescent proteins along with fusion proteins of interest and analyzed the cells using flow cytometry and (thermo-) fluorescent microscopy. Of the tested proteins, thermal green protein (TGP) exhibited the brightest fluorescence when expressed in Sulfolobus cells. By optimizing the linker between TGP and a protein of interest, we could additionally successfully fuse proteins with minimal loss of fluorescence. TGP-CdvB and TGP-PCNA1 fusions displayed localization patterns consistent with previous immunolocalization experiments. These initial results in live protein localization in S. acidocaldarius at high temperatures, combined with recent advancements in thermomicroscopy, open new avenues in the field of archaeal cell biology. This progress finally enables localization experiments in thermophilic archaea, which have so far been limited to mesophilic organisms.

Accurate Identification of Periplasmic Urea-binding Proteins by Structure- and Genome Context-assisted Functional Analysis

ABC transporters are ancient and ubiquitous nutrient transport systems in bacteria and play a central role in defining lifestyles. Periplasmic solute-binding proteins (SBPs) are components that deliver ligands to their translocation machinery. SBPs have diversified to bind a wide range of ligands with high specificity and affinity. However, accurate assignment of cognate ligands remains a challenging problem in SBPs. Urea metabolism plays an important role in the nitrogen cycle; anthropogenic sources account for more than half of global nitrogen fertilizer. We report identification of urea-binding proteins within a large SBP sequence family that encodes diverse functions. By combining genetic linkage between SBPs, ABC transporter components, enzymes or transcription factors, we accurately identified cognate ligands, as we verified experimentally by biophysical characterization of ligand binding and crystallographic determination of the urea complex of a thermostable urea-binding homolog. Using three-dimensional structure information, these functional assignments were extrapolated to other members in the sequence family lacking genetic linkage information, which revealed that only a fraction bind urea. Using the same combined approaches, we also inferred that other family members bind various short-chain amides, aliphatic amino acids (leucine, isoleucine, valine), γ-aminobutyrate, and as yet unknown ligands. Comparative structural analysis revealed structural adaptations that encode diversification in these SBPs. Systematic assignment of ligands to SBP sequence families is key to understanding bacterial lifestyles, and also provides a rich source of biosensors for clinical and environmental analysis, such as the thermostable urea-binding protein identified here.

Molecular Analysis of Changes in DNA Binding Affinity and Bending Extent Induced by the Mutations on the Aromatic Amino Residues in Cren7.

Proteins from Crenarchaeal organisms exhibit remarkable thermal stability. The aromatic amino acids in Cren7, a Crenarchaeal protein, regulate protein stability and further modulate DNA binding and its compaction. Specific aromatic amino acids were mutated, and using spectroscopic and theoretical approaches, we have examined the effect of the mutation on the structure, DNA binding affinity, and DNA bending ability of Cren7. The mutants were compared to the structure and function of wild-type (WT) Cren7. The reverse titration profiles were analysed by a noncooperative McGhee-von Hippel model to estimate affinity constant (Ka) and binding site size (n) associated with binding to the DNA. The biolayer interferometry (BLI) measurements showed that the binding affinity decreased at higher salt concentrations. For theoretical analysis of the extent of DNA bending, radius of gyration and bending angle were compared for WT and mutants. The time evolution of order parameters based on the translational and rotational motion of tryptophan residue (W26) was used for the qualitative detection of stacking interactions between W26 of Cren7 and DNA nucleobases. It was observed that the orientation of W26 in F41A favored the formation of a new lone pair-lone pair interaction between DNA and Cren7. Consequently, in thermostable proteins, the aromatic residues at the terminus maintain structural stability, whereas the residues at the core optimize the degree of DNA bending and compaction.

ThermoLink: Bridging disulfide bonds and enzyme thermostability through database construction and machine learning prediction.

Disulfide bonds, covalently formed by sulfur atoms in cysteine residues, play a crucial role in protein folding and structure stability. Considering their significance, artificial disulfide bonds are often introduced to enhance protein thermostability. Although an increasing number of tools can assist with this task, significant amounts of time and resources are often wasted owing to inadequate consideration. To enhance the accuracy and efficiency of designing disulfide bonds for protein thermostability improvement, we initially collected disulfide bond and protein thermostability data from extensive literature sources. Thereafter, we extracted various sequence- and structure-based features and constructed machine-learning models to predict whether disulfide bonds can improve protein thermostability. Among all models, the neighborhood context model based on the Adaboost-DT algorithm performed the best, yielding "area under the receiver operating characteristic curve" and accuracy scores of 0.773 and 0.714, respectively. Furthermore, we also found AlphaFold2 to exhibit high superiority in predicting disulfide bonds, and to some extent, the coevolutionary relationship between residue pairs potentially guided artificial disulfide bond design. Moreover, several mutants of imine reductase 89 (IR89) with artificially designed thermostable disulfide bonds were experimentally proven to be considerably efficient for substrate catalysis. The SS-bond data have been integrated into an online server, namely, ThermoLink, available at guolab.mpu.edu.mo/thermoLink.

The Crystal Structure of Thermal Green Protein Q66E (TGP-E) and Yellow Thermostable Protein (YTP-E) E148D

Thermal green protein Q66E (TGP-E) has previously shown increased thermal stability compared to thermal green protein (TGP), a thermal stable fluorescent protein produced through consensus and surface protein engineering. In this paper, we describe the protein crystal structure of TGP-E to 2.0 Å. This structure reveals alterations in the hydrogen bond network near the chromophore that may result in the observed increase in thermal stability. We compare the very stable TGP-E protein to the structure of a yellow mutant version of this protein YTP-E E148D. The structure of this mutant protein reveals the rationale for the observed low quantum yield and directions for future protein engineering efforts.