Accurate protein stability predictions from homology models
Calculating changes in protein stability (ΔΔG) has been shown to be central for predicting the consequences of single amino acid substitutions in protein engineering as well as interpretation of genomic variants for disease risk. Structure-based calculations are considered most accurate, however the...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037022005426 |
| _version_ | 1827577670243713024 |
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| author | Audrone Valanciute Lasse Nygaard Henrike Zschach Michael Maglegaard Jepsen Kresten Lindorff-Larsen Amelie Stein |
| author_facet | Audrone Valanciute Lasse Nygaard Henrike Zschach Michael Maglegaard Jepsen Kresten Lindorff-Larsen Amelie Stein |
| author_sort | Audrone Valanciute |
| collection | DOAJ |
| description | Calculating changes in protein stability (ΔΔG) has been shown to be central for predicting the consequences of single amino acid substitutions in protein engineering as well as interpretation of genomic variants for disease risk. Structure-based calculations are considered most accurate, however the tools used to calculate ΔΔGs have been developed on experimentally resolved structures. Extending those calculations to homology models based on related proteins would greatly extend their applicability as large parts of e.g. the human proteome are not structurally resolved. In this study we aim to investigate the accuracy of ΔΔG values predicted on homology models compared to crystal structures. Specifically, we identified four proteins with a large number of experimentally tested ΔΔGs and templates for homology modeling across a broad range of sequence identities, and selected three methods for ΔΔG calculations to test. We find that ΔΔG-values predicted from homology models compare equally well to experimental ΔΔGs as those predicted on experimentally established crystal structures, as long as the sequence identity of the model template to the target protein is at least 40%. In particular, the Rosetta cartesian_ddg protocol is robust against the small perturbations in the structure which homology modeling introduces. In an independent assessment, we observe a similar trend when using ΔΔGs to categorize variants as low or wild-type-like abundance. Overall, our results show that stability calculations performed on homology models can substitute for those on crystal structures with acceptable accuracy as long as the model is built on a template with sequence identity of at least 40% to the target protein. |
| first_indexed | 2024-03-08T21:31:12Z |
| format | Article |
| id | doaj.art-604ea8862e664c0f92339efdbbb4177c |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-08T21:31:12Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-604ea8862e664c0f92339efdbbb4177c2023-12-21T07:30:14ZengElsevierComputational and Structural Biotechnology Journal2001-03702023-01-01216673Accurate protein stability predictions from homology modelsAudrone Valanciute0Lasse Nygaard1Henrike Zschach2Michael Maglegaard Jepsen3Kresten Lindorff-Larsen4Amelie Stein5Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, DenmarkLinderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, DenmarkSection for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, DenmarkLinderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, DenmarkLinderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark; Corresponding authors.Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark; Corresponding authors.Calculating changes in protein stability (ΔΔG) has been shown to be central for predicting the consequences of single amino acid substitutions in protein engineering as well as interpretation of genomic variants for disease risk. Structure-based calculations are considered most accurate, however the tools used to calculate ΔΔGs have been developed on experimentally resolved structures. Extending those calculations to homology models based on related proteins would greatly extend their applicability as large parts of e.g. the human proteome are not structurally resolved. In this study we aim to investigate the accuracy of ΔΔG values predicted on homology models compared to crystal structures. Specifically, we identified four proteins with a large number of experimentally tested ΔΔGs and templates for homology modeling across a broad range of sequence identities, and selected three methods for ΔΔG calculations to test. We find that ΔΔG-values predicted from homology models compare equally well to experimental ΔΔGs as those predicted on experimentally established crystal structures, as long as the sequence identity of the model template to the target protein is at least 40%. In particular, the Rosetta cartesian_ddg protocol is robust against the small perturbations in the structure which homology modeling introduces. In an independent assessment, we observe a similar trend when using ΔΔGs to categorize variants as low or wild-type-like abundance. Overall, our results show that stability calculations performed on homology models can substitute for those on crystal structures with acceptable accuracy as long as the model is built on a template with sequence identity of at least 40% to the target protein.http://www.sciencedirect.com/science/article/pii/S2001037022005426Protein stabilityΔΔGProtein variantMutation |
| spellingShingle | Audrone Valanciute Lasse Nygaard Henrike Zschach Michael Maglegaard Jepsen Kresten Lindorff-Larsen Amelie Stein Accurate protein stability predictions from homology models Computational and Structural Biotechnology Journal Protein stability ΔΔG Protein variant Mutation |
| title | Accurate protein stability predictions from homology models |
| title_full | Accurate protein stability predictions from homology models |
| title_fullStr | Accurate protein stability predictions from homology models |
| title_full_unstemmed | Accurate protein stability predictions from homology models |
| title_short | Accurate protein stability predictions from homology models |
| title_sort | accurate protein stability predictions from homology models |
| topic | Protein stability ΔΔG Protein variant Mutation |
| url | http://www.sciencedirect.com/science/article/pii/S2001037022005426 |
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