Accurate protein stability predictions from homology models

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Accurate protein stability predictions from homology models. / Valanciute, Audrone; Nygaard, Lasse; Zschach, Henrike; Maglegaard Jepsen, Michael; Lindorff-Larsen, Kresten; Stein, Amelie.

In: Computational and Structural Biotechnology Journal, Vol. 21, 2023, p. 66-73.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Valanciute, A, Nygaard, L, Zschach, H, Maglegaard Jepsen, M, Lindorff-Larsen, K & Stein, A 2023, 'Accurate protein stability predictions from homology models', Computational and Structural Biotechnology Journal, vol. 21, pp. 66-73. https://doi.org/10.1016/j.csbj.2022.11.048

APA

Valanciute, A., Nygaard, L., Zschach, H., Maglegaard Jepsen, M., Lindorff-Larsen, K., & Stein, A. (2023). Accurate protein stability predictions from homology models. Computational and Structural Biotechnology Journal, 21, 66-73. https://doi.org/10.1016/j.csbj.2022.11.048

Vancouver

Valanciute A, Nygaard L, Zschach H, Maglegaard Jepsen M, Lindorff-Larsen K, Stein A. Accurate protein stability predictions from homology models. Computational and Structural Biotechnology Journal. 2023;21:66-73. https://doi.org/10.1016/j.csbj.2022.11.048

Author

Valanciute, Audrone ; Nygaard, Lasse ; Zschach, Henrike ; Maglegaard Jepsen, Michael ; Lindorff-Larsen, Kresten ; Stein, Amelie. / Accurate protein stability predictions from homology models. In: Computational and Structural Biotechnology Journal. 2023 ; Vol. 21. pp. 66-73.

Bibtex

@article{1b2f1e97dd76484d84f1dc9baa90d98e,
title = "Accurate protein stability predictions from homology models",
abstract = "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.",
keywords = "Mutation, Protein stability, Protein variant, ΔΔG",
author = "Audrone Valanciute and Lasse Nygaard and Henrike Zschach and {Maglegaard Jepsen}, Michael and Kresten Lindorff-Larsen and Amelie Stein",
note = "Publisher Copyright: {\textcopyright} 2022",
year = "2023",
doi = "10.1016/j.csbj.2022.11.048",
language = "English",
volume = "21",
pages = "66--73",
journal = "Computational and Structural Biotechnology Journal",
issn = "2001-0370",
publisher = "Research Network of Computational and Structural Biotechnology (RNCSB)",

}

RIS

TY - JOUR

T1 - Accurate protein stability predictions from homology models

AU - Valanciute, Audrone

AU - Nygaard, Lasse

AU - Zschach, Henrike

AU - Maglegaard Jepsen, Michael

AU - Lindorff-Larsen, Kresten

AU - Stein, Amelie

N1 - Publisher Copyright: © 2022

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Mutation

KW - Protein stability

KW - Protein variant

KW - ΔΔG

U2 - 10.1016/j.csbj.2022.11.048

DO - 10.1016/j.csbj.2022.11.048

M3 - Journal article

C2 - 36514339

AN - SCOPUS:85144041215

VL - 21

SP - 66

EP - 73

JO - Computational and Structural Biotechnology Journal

JF - Computational and Structural Biotechnology Journal

SN - 2001-0370

ER -

ID: 331317936