Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine
Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited numbe...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037020303433 |
| _version_ | 1829489935098314752 |
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| author | Tiziana Sanavia Giovanni Birolo Ludovica Montanucci Paola Turina Emidio Capriotti Piero Fariselli |
| author_facet | Tiziana Sanavia Giovanni Birolo Ludovica Montanucci Paola Turina Emidio Capriotti Piero Fariselli |
| author_sort | Tiziana Sanavia |
| collection | DOAJ |
| description | Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases. |
| first_indexed | 2024-12-15T00:14:16Z |
| format | Article |
| id | doaj.art-4da72bc6299646fcbd3407b6a7edd179 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-12-15T00:14:16Z |
| publishDate | 2020-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-4da72bc6299646fcbd3407b6a7edd1792022-12-21T22:42:28ZengElsevierComputational and Structural Biotechnology Journal2001-03702020-01-011819681979Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicineTiziana Sanavia0Giovanni Birolo1Ludovica Montanucci2Paola Turina3Emidio Capriotti4Piero Fariselli5Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, ItalyDepartment of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, ItalyDepartment of Comparative Biomedicine and Food Science (BCA), University of Padova, Viale dell’Università 16, 35020 Legnaro, ItalyDepartment of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, ItalyDepartment of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy; Corresponding authors.Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, Italy; Corresponding authors.Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases.http://www.sciencedirect.com/science/article/pii/S2001037020303433Non-synonymous single nucleotide variantsProtein stabilityProtein functionComputational tools and databasesMachine learningPerformance bias |
| spellingShingle | Tiziana Sanavia Giovanni Birolo Ludovica Montanucci Paola Turina Emidio Capriotti Piero Fariselli Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine Computational and Structural Biotechnology Journal Non-synonymous single nucleotide variants Protein stability Protein function Computational tools and databases Machine learning Performance bias |
| title | Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine |
| title_full | Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine |
| title_fullStr | Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine |
| title_full_unstemmed | Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine |
| title_short | Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine |
| title_sort | limitations and challenges in protein stability prediction upon genome variations towards future applications in precision medicine |
| topic | Non-synonymous single nucleotide variants Protein stability Protein function Computational tools and databases Machine learning Performance bias |
| url | http://www.sciencedirect.com/science/article/pii/S2001037020303433 |
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