4 research outputs found
Structural diversity and substrate preferences of three tannase enzymes encoded by the anaerobic bacterium Clostridium butyricum
Tannins are secondary metabolites that are enriched in the bark, roots, and knots in trees and are known to hinder microbial attack. The biological degradation of water-soluble gallotannins, such as tannic acid, is initiated by tannase enzymes (EC 3.1.1.20), which are esterases able to liberate gallic acid from aromatic-sugar complexes. However, only few tannases have previously been studied in detail. Here, for the first time, we biochemically and structurally characterize three tannases from a single organism, the anaerobic bacterium Clostridium butyricum, which inhabits both soil and gut environments. The enzymes were named CbTan1-3, and we show that each one exhibits a unique substrate preference on a range of galloyl ester model substrates; CbTan1 and 3 demonstrated preference toward galloyl esters linked to glucose, while CbTan2 was more promiscuous. All enzymes were also active on oak bark extractives. Furthermore, we solved the crystal structure of CbTan2 and produced homology models for CbTan1 and 3. In each structure, the catalytic triad and gallatebinding regions in the core domain were found in very similar positions in the active site compared with other bacterial tannases, suggesting a similar mechanism of action among these enzymes, though large inserts in each enzyme showcase overall structural diversity. In conclusion, the varied structural features and substrate specificities of the C. butyricum tannases indicate that they have different biological roles and could further be used in development of new valorization strategies for renewable plant biomass
Investigation of robustness for supercritical fluid chromatography separation of peptides : Isocratic vs gradient mode
We investigated and compared the robustness of supercritical fluid chromatography (SFC) separations of the peptide gramicidin, using either isocratic or gradient elution. This was done using design of experiments in a design space of co-solvent fraction, water mass fraction in co-solvent, pressure, and temperature. The density of the eluent (CO2-MeOH-H2O) was experimentally determined using a Coriolis mass flow meter to calculate the volumetric flow rate required by the design. For both retention models, the most important factor was the total co-solvent fraction and water mass fraction in co-solvent. Comparing the elution modes, we found that gradient elution was more than three times more robust than isocratic elution. We also observed a relationship between the sensitivity to changes and the gradient steepness and used this to draw general conclusions beyond the studied experimental system. To test the robustness in a practical context, both the isocratic and gradient separations were transferred to another laboratory. The gradient elution was highly reproducible between laboratories, whereas the isocratic system was not. Using measurements of the actual operational conditions (not the set system conditions), the isocratic deviation was quantitatively explained using the retention model. The findings indicate the benefits of using gradient elution in SFC as well as the importance of measuring the actual operational conditions to be able to explain observed differences between laboratories when conducting method transfer
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Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs, as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing post-translational modifications (PTMs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the intrinsic solubility of mAA-containing peptides in aqueous solution at room temperature. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different small-size mAAs for a total number of 37 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides and confirm that our method can accurately assess the solubility of peptides containing mAAs. This method is available as a web server at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm.The project was supported by the Wellcome Trust (203249/Z/16/Z)
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Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
Acknowledgements: M.O. is a PhD student funded by AstraZeneca. P.S. is a Royal Society University Research Fellow (URF\R1\201461). The project was supported by the Wellcome Trust (203249/Z/16/Z).Funder: UKRI 10061100 and 10059436Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing post-translational modifications (PTMs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the intrinsic solubility of mAA-containing peptides in aqueous solution at room temperature. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different small-size mAAs for a total number of 37 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides and confirm that our method can accurately assess the solubility of peptides containing mAAs. This method is available as a web server at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm