DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence
Protein–solvent interaction provides important features for protein surface engineering when the structure is absent or partially solved. Presently, we can integrate the notion of solvent exposed/buried residues with that of their flexibility and intrinsic disorder to highlight regions where mutatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037021004384 |
| _version_ | 1819320350768365568 |
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| author | Matteo Manfredi Castrense Savojardo Pier Luigi Martelli Rita Casadio |
| author_facet | Matteo Manfredi Castrense Savojardo Pier Luigi Martelli Rita Casadio |
| author_sort | Matteo Manfredi |
| collection | DOAJ |
| description | Protein–solvent interaction provides important features for protein surface engineering when the structure is absent or partially solved. Presently, we can integrate the notion of solvent exposed/buried residues with that of their flexibility and intrinsic disorder to highlight regions where mutations may increase or decrease protein stability in order to modify proteins for biotechnological reasons, while preserving their functional integrity. Here we describe a web server, which provides the unique possibility of integrating knowledge of solvent and non-solvent exposure with that of residue conservation, flexibility and disorder of a protein sequence, for a better understanding of which regions are relevant for protein integrity. The core of the webserver is DeepREx, a novel deep learning-based tool that classifies each residue in the sequence as buried or exposed. DeepREx is trained on a high-quality, non-redundant dataset derived from the Protein Data Bank comprising 2332 monomeric protein chains and benchmarked on a blind test set including 200 protein sequences unrelated with the training set. Results show that DeepREx performs at the state-of-the-art in the field. In turn, the Web Server, DeepREx-WS, supplements the predictions of DeepREx with features that allow a better characterisation of exposed and buried regions: i) residue conservation derived from multiple sequence alignment; ii) local sequence hydrophobicity; iii) residue flexibility computed with MEDUSA; iv) a predictor of secondary structure; v) the presence of disordered regions as derived from MobiDB-Lite3.0. The web server allows browsing, selecting and intersecting the different features. We demonstrate a possible application of the DeepREx-WS for assisting the identification of residues to be variated in protein surface engineering processes. |
| first_indexed | 2024-12-24T11:18:11Z |
| format | Article |
| id | doaj.art-f6a1c988c0cb4d7481cf93a7c7fbc45b |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-12-24T11:18:11Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-f6a1c988c0cb4d7481cf93a7c7fbc45b2022-12-21T16:58:19ZengElsevierComputational and Structural Biotechnology Journal2001-03702021-01-011957915799DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequenceMatteo Manfredi0Castrense Savojardo1Pier Luigi Martelli2Rita Casadio3Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, ItalyBiocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, ItalyBiocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy; Corresponding author.Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy; Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies (IBIOM), Italian National Research Council (CNR), Bari, ItalyProtein–solvent interaction provides important features for protein surface engineering when the structure is absent or partially solved. Presently, we can integrate the notion of solvent exposed/buried residues with that of their flexibility and intrinsic disorder to highlight regions where mutations may increase or decrease protein stability in order to modify proteins for biotechnological reasons, while preserving their functional integrity. Here we describe a web server, which provides the unique possibility of integrating knowledge of solvent and non-solvent exposure with that of residue conservation, flexibility and disorder of a protein sequence, for a better understanding of which regions are relevant for protein integrity. The core of the webserver is DeepREx, a novel deep learning-based tool that classifies each residue in the sequence as buried or exposed. DeepREx is trained on a high-quality, non-redundant dataset derived from the Protein Data Bank comprising 2332 monomeric protein chains and benchmarked on a blind test set including 200 protein sequences unrelated with the training set. Results show that DeepREx performs at the state-of-the-art in the field. In turn, the Web Server, DeepREx-WS, supplements the predictions of DeepREx with features that allow a better characterisation of exposed and buried regions: i) residue conservation derived from multiple sequence alignment; ii) local sequence hydrophobicity; iii) residue flexibility computed with MEDUSA; iv) a predictor of secondary structure; v) the presence of disordered regions as derived from MobiDB-Lite3.0. The web server allows browsing, selecting and intersecting the different features. We demonstrate a possible application of the DeepREx-WS for assisting the identification of residues to be variated in protein surface engineering processes.http://www.sciencedirect.com/science/article/pii/S2001037021004384Residue solvent accessibilityDeep LearningProtein flexibilityProtein disorderSurface engineering |
| spellingShingle | Matteo Manfredi Castrense Savojardo Pier Luigi Martelli Rita Casadio DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence Computational and Structural Biotechnology Journal Residue solvent accessibility Deep Learning Protein flexibility Protein disorder Surface engineering |
| title | DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence |
| title_full | DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence |
| title_fullStr | DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence |
| title_full_unstemmed | DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence |
| title_short | DeepREx-WS: A web server for characterising protein–solvent interaction starting from sequence |
| title_sort | deeprex ws a web server for characterising protein solvent interaction starting from sequence |
| topic | Residue solvent accessibility Deep Learning Protein flexibility Protein disorder Surface engineering |
| url | http://www.sciencedirect.com/science/article/pii/S2001037021004384 |
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