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Thermophilic proteins are important for academic research and industrial processes, and various computational methods have been developed to identify and screen them. However, their performance has been limited due to the lack of high-quality labeled data and efficient models for representing protein. Here, we proposed a novel sequence-based thermophilic proteins prediction framework, called ThermoFinder. The results demonstrated that ThermoFinder outperforms previous state-of-the-art tools on two benchmark datasets, and feature ablation experiments confirmed the effectiveness of our approach. Additionally, ThermoFinder exhibited exceptional performance and consistency across two newly constructed datasets, one of these was specifically constructed for the regression-based prediction of temperature optimum values directly derived from protein sequences. The feature importance analysis, using shapley additive explanations, further validated the advantages of ThermoFinder. We believe that ThermoFinder will be a valuable and comprehensive framework for predicting thermophilic proteins, and we have made our model open source and available on Github at https://github.com/Luo-SynBioLab/ThermoFinder.
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Biología Computacional , Programas Informáticos , Biología Computacional/métodos , Proteínas/química , Bases de Datos de Proteínas , Análisis de Secuencia de Proteína/métodos , Algoritmos , TemperaturaRESUMEN
Conventional statistical investigations have primarily focused on the comparison of the simple one-dimensional characteristics of protein cavities, such as number, surface area, and volume. These studies have failed to discern the crucial distinctions in cavity properties between thermophilic and mesophilic proteins that contribute to protein thermostability. In this study, the significance of cavity properties, i.e., flexibility and location, in protein thermostability was investigated by comparing structural differences between homologous thermophilic and mesophilic proteins. Three dimensions of protein structure were categorized into three regions (core, boundary, and surface) and a comparative analysis of cavity properties using this structural index was conducted. The statistical analysis revealed that cavity flexibility is closely related to protein thermostability. The core cavities of thermophilic proteins were less flexible than those of mesophilic proteins (averaged B' factor values, -0.6484 and -0.5111), which might be less deleterious to protein thermostability. Thermophilic proteins exhibited fewer cavities in the boundary and surface regions. Notably, cavities in mesophilic proteins, across all regions, exhibited greater flexibility than those in thermophilic proteins (>95% probability). The increased flexibility of cavities in the boundary and surface regions of mesophilic proteins, as opposed to thermophilic proteins, may compromise stability. Recent protein engineering investigations involving mesophilic xylanase and protease showed results consistent with the findings of this study, suggesting that the manipulation of flexible cavities in the surface region can enhance thermostability. Consequently, our findings suggest that a rational or computational approach to the design of flexible cavities in surface or boundary regions could serve as an effective strategy to enhance the thermostability of mesophilic proteins.
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Using wet experimental methods to discover new thermophilic proteins or improve protein thermostability is time-consuming and expensive. Machine learning methods have shown powerful performance in the study of protein thermostability in recent years. However, how to make full use of multiview sequence information to predict thermostability effectively is still a challenge. In this study, we proposed a deep learning-based classifier named DeepPPThermo that fuses features of classical sequence features and deep learning representation features for classifying thermophilic and mesophilic proteins. In this model, deep neural network (DNN) and bi-long short-term memory (Bi-LSTM) are used to mine hidden features. Furthermore, local attention and global attention mechanisms give different importance to multiview features. The fused features are fed to a fully connected network classifier to distinguish thermophilic and mesophilic proteins. Our model is comprehensively compared with advanced machine learning algorithms and deep learning algorithms, proving that our model performs better. We further compare the effects of removing different features on the classification results, demonstrating the importance of each feature and the robustness of the model. Our DeepPPThermo model can be further used to explore protein diversity, identify new thermophilic proteins, and guide directed mutations of mesophilic proteins.
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Aprendizaje Profundo , Aminoácidos , Redes Neurales de la Computación , Proteínas/genética , AlgoritmosRESUMEN
Siderophore-binding proteins from two thermophilic bacteria, Geobacillus stearothermophilus and Parageobacillus thermoglucosidasius, were identified from a search of sequence databases, cloned and overexpressed. They are homologues of the well characterized protein CjCeuE from Campylobacter jejuni. The iron-binding histidine and tyrosine residues are conserved in both thermophiles. Crystal structures were determined of the apo proteins and of their complexes with iron(III)-azotochelin and its analogue iron(III)-5-LICAM. The thermostability of both homologues was shown to be about 20°C higher than that of CjCeuE. Similarly, the tolerance of the homologues to the organic solvent dimethylformamide (DMF) was enhanced, as reflected by the respective binding constants for these ligands measured in aqueous buffer at pH 7.5 in the absence and presence of 10% and 20% DMF. Consequently, these thermophilic homologues offer advantages in the development of artificial metalloenzymes using the CeuE family.
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Proteínas de Unión Periplasmáticas , Sideróforos , Sideróforos/metabolismo , Proteínas de Unión Periplasmáticas/química , Geobacillus stearothermophilus/metabolismo , Compuestos Férricos/metabolismo , Hierro/metabolismoRESUMEN
Thermophilic proteins have important value in the fields of biopharmaceuticals and enzyme engineering. Most existing thermophilic protein prediction models are based on traditional machine learning algorithms and do not fully utilize protein sequence information. To solve this problem, a deep learning model based on self-attention and multiple-channel feature fusion was proposed to predict thermophilic proteins, called DeepTP. First, a large new dataset consisting of 20,842 proteins was constructed. Second, a convolutional neural network and bidirectional long short-term memory network were used to extract the hidden features in protein sequences. Different weights were then assigned to features through self-attention, and finally, biological features were integrated to build a prediction model. In a performance comparison with existing methods, DeepTP had better performance and scalability in an independent balanced test set and validation set, with AUC values of 0.944 and 0.801, respectively. In the unbalanced test set, DeepTP had an average precision (AP) of 0.536. The tool is freely available.
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Aprendizaje Profundo , Redes Neurales de la Computación , Proteínas/metabolismo , Algoritmos , Aprendizaje AutomáticoRESUMEN
Proteins from hyperthermophilic organisms are evolutionary optimised to adopt functional structures and dynamics under conditions in which their mesophilic homologues are generally inactive or unfolded. Understanding the nature of such adaptation is of crucial interest to clarify the underlying mechanisms of biological activity in proteins. Here we measured NMR residual dipolar couplings of a hyperthermophilic acylphosphatase enzyme at 80°C and used these data to generate an accurate structural ensemble representative of its native state. The resulting energy landscape was compared to that obtained for a human homologue at 37°C, and additional NMR experiments were carried out to probe fast (15N relaxation) and slow (H/D exchange) backbone dynamics, collectively sampling fluctuations of the two proteins ranging from the nanosecond to the millisecond timescale. The results identified key differences in the strategies for protein-protein and protein-ligand interactions of the two enzymes at the respective physiological temperatures. These include the dynamical behaviour of a ß-strand involved in the protection against aberrant protein aggregation and concerted motions of loops involved in substrate binding and catalysis. Taken together these results elucidate the structure-dynamics-function relationship associated with the strategies of thermal adaptation of protein molecules.
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Thermophilic proteins have various practical applications in theoretical research and in industry. In recent years, the demand for thermophilic proteins on an industrial scale has been increasing; therefore, the engineering of thermophilic proteins has become a hot direction in the field of protein engineering. However, the exact mechanism of thermostability of proteins is not yet known, for engineering thermophilic proteins knowing the basis of thermostability is necessary. In order to understand the basis of the thermostability in proteins, we have made a statistical analysis of the sequences, secondary structures, hydrogen bonds, salt bridges, DHA (Donor-Hydrogen-Accepter) angles, and bond lengths of ten pairs of thermophilic proteins and their non-thermophilic orthologous. Our findings suggest that polar amino acids contribute to thermostability in proteins by forming hydrogen bonds and salt bridges which provide resistance against protein denaturation. Short bond length and a wider DHA angle provide greater bond stability in thermophilic proteins. Moreover, the increased frequency of aromatic amino acids in thermophilic proteins contributes to thermal stability by forming more aromatic interactions. Additionally, the coil, helix, and loop in the secondary structure also contribute to thermostability.
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Aminoácidos , Proteínas , Aminoácidos/química , Enlace de Hidrógeno , Desnaturalización Proteica , Ingeniería de Proteínas , Proteínas/química , TemperaturaRESUMEN
Thermophilic proteins have important application value in biotechnology and industrial processes. The correct identification of thermophilic proteins provides important information for the application of these proteins in engineering. The identification method of thermophilic proteins based on biochemistry is laborious, time-consuming, and high cost. Therefore, there is an urgent need for a fast and accurate method to identify thermophilic proteins. Considering this urgency, we constructed a reliable benchmark dataset containing 1,368 thermophilic and 1,443 non-thermophilic proteins. A multi-layer perceptron (MLP) model based on a multi-feature fusion strategy was proposed to discriminate thermophilic proteins from non-thermophilic proteins. On independent data set, the proposed model could achieve an accuracy of 96.26%, which demonstrates that the model has a good application prospect. In order to use the model conveniently, a user-friendly software package called iThermo was established and can be freely accessed at http://lin-group.cn/server/iThermo/index.html. The high accuracy of the model and the practicability of the developed software package indicate that this study can accelerate the discovery and engineering application of thermally stable proteins.
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Chloroflexus aurantiacus J-10-f1 is an anoxygenic, photosynthetic, facultative autotrophic gram negative bacterium found from hot spring at a temperature range of 50-60°C. It can sustain itself in dark only if oxygen is available thereby exhibiting a dark orange color, however display a dark green color when grown in sunlight. Genome of the organism contains total of 3853 proteins out of which 785 (~20%) proteins are uncharacterised or hypothetical proteins (HPs). Therefore in this work we have characterized the 785 hypothetical proteins of Chloroflexus aurantiacus J-10-f1 using bioinformatics tools and databases. HPs annotated by more than five domain prediction tools were filtered and named high confidence-hypothetical proteins (HC-HPs). These HC-HPs were further annotated by calculating their physiochemical properties, homologous, subcellular locations, signal peptides and transmembrane regions. We found most of the HC-HPs were involved in photosynthesis, carbohydrate metabolism, biofuel production and cellulose synthesis processes. Furthermore, few of these HC-HPs could provide resistance to bacteria at high temperature due to their thermophilic nature. Hence these HC-HPs have the potential to be used in industrial as well as in biomedical needs. To conclude, the bioinformatics approach used in this study provides an insight to better understand the nature and role of Chloroflexus aurantiacus J-10-f1 hypothetical proteins.
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Thermophilicity is a very important property of proteins, as it sometimes determines denaturation and cell death. Thus, methods for predicting thermophilic proteins and non-thermophilic proteins are of interest and can contribute to the design and engineering of proteins. In this article, we describe the use of feature dimension reduction technology and LIBSVM to identify thermophilic proteins. The highest accuracy obtained by cross-validation was 96.02% with 119 parameters. When using only 16 features, we obtained an accuracy of 93.33%. We discuss the importance of the different characteristics in identification and report a comparison of the performance of support vector machine to that of other methods.
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C-phycoyanins are abundant light-harvesting pigments which have an important role in the energy transfer cascade of photosystems in prokaryotic cyanobacteria and eukaryotic red algae. These proteins have important biotechnological applications, since they can be used in food, cosmetics, nutraceutical, pharmaceutical industries and in biomedical research. Here, C-phycocyanin from the extremophilic red alga Galdieria phlegrea (GpPC) has been purified and characterized from a biophysical point of view by SDS-PAGE, mass spectrometry, UV-Vis absorption spectroscopy, circular dichroism and intrinsic fluorescence. Stability against pH variations, addition of the oxidizing agent hydrogen peroxide and the effects of temperature have been also investigated, together with its in cell antioxidant potential and antitumor activity. GpPC is stable under different pHs and unfolds at a temperature higher than 80 °C within the pH range 5.0-7.0. Its fluorescence spectra present a maximum at 650 nm, when excited at 589 nm. The protein exerts interesting in cell antioxidant properties even after high temperature treatments, like the pasteurization process, and is cytotoxic for A431 and SVT2 cancer cells, whereas it is not toxic for non-malignant cells. Our results assist in the development of C-phycocyanin as a multitasking protein, to be used in the food industry, as antioxidant and anticancer agent.
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Fenómenos Químicos , Ficocianina/química , Secuencia de Aminoácidos , Antineoplásicos/química , Antineoplásicos/aislamiento & purificación , Antineoplásicos/farmacología , Antioxidantes/química , Antioxidantes/aislamiento & purificación , Antioxidantes/farmacología , Cromatografía Liquida , Concentración de Iones de Hidrógeno , Ficocianina/aislamiento & purificación , Ficocianina/farmacología , Estabilidad Proteica , Especies Reactivas de Oxígeno/metabolismo , Rhodophyta/química , Espectrometría de Masas en Tándem , TemperaturaRESUMEN
Literature from the past two decades has outlined the existence of a trade-off between protein stability and function. This trade-off creates a unique challenge for protein engineers who seek to introduce new functionality to proteins. These engineers must carefully balance the mutation-mediated creation and/or optimization of function with the destabilizing effect of those mutations. Subsequent research has shown that protein stability is positively correlated with "evolvability" or the ability to support mutations which bestow new functionality on the protein. Since the ultimate goal of protein engineering is to create and/or optimize a protein's function, highly stable proteins are preferred as potential scaffolds for protein engineering. This review focuses on the application potential for thermophilic proteins as scaffolds for protein engineering. The relatively high inherent thermostability of these proteins grants them a great deal of mutational robustness, making them promising scaffolds for various protein engineering applications. Comparative studies on the evolvability of thermophilic and mesophilic proteins have strongly supported the argument that thermophilic proteins are more evolvable than mesophilic proteins. These findings indicate that thermophilic proteins may represent the scaffold of choice for protein engineering in the future.
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Despite an intense interest and a remarkable number of studies on the subject, the relationships between thermostability and (primary, secondary and tertiary) structure of proteins are still not fully understood. Here, comparing the protein density - defined by the ratio between the residue number and protein excluded volume - for a set of thermophilic/mesophilic pairs, we provide evidence that this property is connected to the optimal growth temperature. In particular, our results indicate that thermophilic proteins have - in general - a lower density with respect to the mesophilic counterparts, being such a correlation more pronounced for optimal growth temperature differences greater than 40°C. The effect of the protein thermostability changes on the molecular shape is also presented.
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Aminoácidos/química , Bacterias/química , Proteínas Bacterianas/química , Estabilidad Proteica , Secuencia de Aminoácidos , Bacterias/metabolismo , Proteínas Bacterianas/metabolismo , Calor , TemperaturaRESUMEN
Enzymes from thermophilic and hyper-thermophilic organisms have an intrinsic high stability. Understanding the mechanisms behind their high stability will be important knowledge for the engineering of novel enzymes with high stability. Lysine methylation of proteins is prevalent in Sulfolobus, a genus of hyperthermophilic and acidophilic archaea. Both unspecific and temperature dependent lysine methylations are seen, but the significance of this post-translational modification has not been investigated. Here, we test the effect of eliminating in vivo lysine methylation on the stability of an esterase (EstA). The enzyme was purified from the native host S. islandicus as well as expressed as a recombinant protein in E. coli, a mesophilic host that does not code for any machinery for in vivo lysine methylation. We find that lysine mono methylation indeed has a positive effect on the stability of EstA, but the effect is small. The effect of the lysine methylation on protein stability is secondary to that of protein expression in E. coli, as the E. coli recombinant enzyme is compromised both on stability and activity. We conclude that these differences are not attributed to any covalent difference between the protein expressed in hyperthermophilic versus mesophilic hosts.
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Proteínas Arqueales/química , Proteínas Arqueales/metabolismo , Hidrolasas de Éster Carboxílico/química , Hidrolasas de Éster Carboxílico/metabolismo , Sulfolobus/enzimología , Proteínas Arqueales/genética , Hidrolasas de Éster Carboxílico/genética , Escherichia coli/genética , Lisina/metabolismo , Metilación , Procesamiento Proteico-Postraduccional , Estabilidad Proteica , Proteínas Recombinantes/química , Proteínas Recombinantes/genética , Proteínas Recombinantes/metabolismo , Sulfolobus/genéticaRESUMEN
An entropic stabilization mechanism has recently gained attention and credibility as the physical ground for the extra thermal stability of globular proteins from thermophilic microorganisms. An empirical result, obtained from the analysis of thermodynamic data for a large set of proteins, strengthens the general reliability of the theoretical approach originally devised to rationalize the occurrence of cold denaturation [Graziano, PCCP 2014, 16, 21755-21767]. It is shown that this theoretical approach can readily account for the entropic stabilization mechanism. On decreasing the conformational entropy gain associated with denaturation, the thermal stability of a model globular protein increases markedly.
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Frío , Calor , Modelos Químicos , Proteínas/química , Animales , Entropía , Humanos , Desnaturalización Proteica , Estabilidad ProteicaRESUMEN
O-Phosphoserine sulfhydrylase (OPSS) synthesizes cysteine from O-phospho-L-serine (OPS) and sulfide. We have determined the three-dimensional structures of OPSS from hyperthermophilic archaeon Aeropyrum pernix K1 (ApOPSS) in complex with aminoacrylate intermediate (AA) formed from pyridoxal 5'-phosphate with OPS or in complex with cysteine and compared them with that of ApOPSS. We found an orientational change of F225 at the active-site entrance and constructed an F225A mutant to examine its activities and AA stability and clarify the role of F225 in ApOPSS. The OPS and O-acetyl-L-serine (OAS) sulfhydrylase activities of the F225A mutant decreased by 4.2- and 15-fold compared to those of the wild-type (wt) ApOPSS, respectively. The ability of OPS and OAS to form AA also decreased by 12- and 27-fold, respectively. AA was less stable in the F225A mutant than in the wt ApOPSS. Simulated docking showed that leaving groups, such as phosphate and acetate, were oriented to the inside of the active site in the F225A mutant, whereas they were oriented to the entrance in the wt ApOPSS. These results suggest that F225 in ApOPSS plays important roles in maintaining the hydrophobic environment of AA from solvent water and in controlling the orientation of leaving groups.
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Aeropyrum/enzimología , Liasas de Carbono-Oxígeno/química , Simulación del Acoplamiento Molecular , Aeropyrum/genética , Sustitución de Aminoácidos , Liasas de Carbono-Oxígeno/genética , Liasas de Carbono-Oxígeno/metabolismo , Dominio CatalíticoRESUMEN
Proteins belonging to the same class, having similar structures thus performing the same function are known to have different thermal stabilities depending on the source- thermophile or mesophile. The variation in thermo-stability has not been attributed to any unified factor yet and understanding this phenomenon is critically needed in several areas, particularly in protein engineering to design stable variants of the proteins. Toward this motive, the present study focuses on the sequence and structural investigation of a dataset of 373 pairs of proteins; a thermophilic protein and its mesophilic structural analog in each pair, from the perspectives of hydrophobic free energy, hydrogen bonds, physico-chemical properties of amino acids and residue-residue contacts. Our results showed that the hydrophobic free energy due to carbon, charged nitrogen and charged oxygen atoms was stronger in 65% of thermophilic proteins. The number of hydrogen bonds which bridges the buried and exposed regions of proteins was also greater in case of thermophiles. Amino acids of extended shape, volume and molecular weight along with more medium and long range contacts were observed in many of the thermophilic proteins. These results highlight the preference of thermophiles toward the amino acids with larger side chain and charged to make up greater free energy, better packing of residues and increase the overall compactness.
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Modelos Moleculares , Proteínas/química , Termodinámica , Aminoácidos/química , Enlace de Hidrógeno , Interacciones Hidrofóbicas e Hidrofílicas , Conformación Proteica , Estabilidad ProteicaRESUMEN
We present the first investigation of the kinetic and thermodynamic stability of two homologous thermophilic and mesophilic proteins based on the coarse-grained model OPEP. The object of our investigation is a pair of G-domains of relatively large size, 200 amino acids each, with an experimental stability gap of about 40 K. The OPEP force field is able to maintain stable the fold of these relatively large proteins within the hundrend-nanosecond time scale without including external constraints. This makes possible to characterize the conformational landscape of the folded protein as well as to explore the unfolding. In agreement with all-atom simulations used as a reference, we show that the conformational landscape of the thermophilic protein is characterized by a larger number of substates with slower dynamics on the network of states and more resilient to temperature increase. Moreover, we verify the stability gap between the two proteins using replica-exchange simulations and estimate a difference between the melting temperatures of about 23 K, in fair agreement with experiment. The detailed investigation of the unfolding thermodynamics, allows to gain insight into the mechanism underlying the enhanced stability of the thermophile relating it to a smaller heat capacity of unfolding.
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Processing of Holliday junctions is essential in recombination. We have identified the gene for the junction-resolving enzyme GEN1 from the thermophilic fungus Chaetomium thermophilum and expressed the N-terminal 487-amino-acid section. The protein is a nuclease that is highly selective for four-way DNA junctions, cleaving 1nt 3' to the point of strand exchange on two strands symmetrically disposed about a diagonal axis. CtGEN1 binds to DNA junctions as a discrete homodimer with nanomolar affinity. Analysis of the kinetics of cruciform cleavage shows that cleavage of the second strand occurs an order of magnitude faster than the first cleavage so as to generate a productive resolution event. All these properties are closely similar to those described for bacterial, phage and mitochondrial junction-resolving enzymes. CtGEN1 is also similar in properties to the human enzyme but lacks the problems with aggregation that currently prevent detailed analysis of the latter protein. CtGEN1 is thus an excellent enzyme with which to engage in biophysical and structural analysis of eukaryotic GEN1.