Accurate protein stability predictions from homology models

2022/11/25 by Audronė Valančiūtė, Lasse Nygaard, Henrike Zschach +3 · 1 voice
Biochemistry, Genetics and Molecular Biology · Materials Science · #Enzyme Structure and Function #Microbial Metabolic Engineering and Bioproduction #Protein Structure and Dynamics

paper · doi:10.1016/j.csbj.2022.11.048

openalex publication_date 2022/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

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.

Citations

• Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template
• Principles of Protein Stability and Their Application in Computational Design
• Highly accurate protein structure prediction with AlphaFold
• A structural biology community assessment of AlphaFold2 applications
• Mutational effects on stability are largely conserved during protein evolution
• Statistical potential for assessment and prediction of protein structures

Discussions

• In this paper we present a null model that ΔΔG = 1.15 kcal/mol for any mutation! Doesn’t do well for correlation but MAE is ok. We also have a more advanced baseline in the same paper doi.org/10.1016 [bsky, 2 points, 1 comments]

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