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bioRxiv · 10.1101/2021.08.26.457758

Best templates outperform homology models in predicting the impact of mutations on protein stability

Pak, M. A.·Ivankov, D. N.
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Abstract

MotivationPrediction of protein stability change upon mutation ({Delta}{Delta}G) is crucial for facilitating protein engineering and understanding of protein folding principles. Robust prediction of protein folding free energy change requires the knowledge of protein three-dimensional (3D) structure. Unfortunately, protein 3D structure is not always available. In this case, one can still predict the protein stability change by constructing a homology model of the protein; however, the accuracy of homology model-based {Delta}{Delta}G predictions is unknown. The perspectives of using 3D structures of the best templates are also unclear. ResultsTo investigate these questions, we used the most popular and accurate publicly available tools: FoldX for stability change prediction and I-Tasser for homology modeling. We found that both homology models and best templates worsen the {Delta}{Delta}G prediction, with best templates performing 1.5 times better than homology models. For AlphaFold models, we also found that the best templates seem to outperform protein models. Our findings imply using the 3D structures of the best templates for {Delta}{Delta}G prediction if the 3D protein structure is unavailable. Contactd.ivankov@skoltech.ru

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Pak, M. A., Ivankov, D. N.. 2021-08-27. Best templates outperform homology models in predicting the impact of mutations on protein stability. https://doi.org/10.1101/2021.08.26.457758

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