ArticleProtein science : a publication of the Protein Society2023
Target-template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations.
Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- On the generalization and usability of cofolding models for GPCR drug discovery.npj drug discovery · 2026Article
- Unveiling the bioactive landscape of drug inactive ingredients (DIGs) using deep transfer learning.Acta pharmaceutica Sinica. B · 2026Article
- Antibody Affinity Maturation by Computational Design.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Article
- Structural Adaptation of the Single-Stranded DNA-Binding Protein C-Terminal to DNA Metabolizing Partners Guides Inhibitor Design.Pharmaceutics · 2023Article
- Target-template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations.Protein science : a publication of the Protein Society · 2023Article
- DeepTM: A deep learning algorithm for prediction of melting temperature of thermophilic proteins directly from sequences.Computational and structural biotechnology journal · 2023Article
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Authors and funding
3 authors.
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Abstract
Improving protein thermostability has been a labor- and time-consuming process in industrial applications of protein engineering. Advances in computational approaches have facilitated the development of more efficient strategies to allow the prioritization of stabilizing mutants. Among these is FEP+, a free energy perturbation implementation that uses a thoroughly tested physics-based method to achieve unparalleled accuracy in predicting changes in protein thermostability. To gauge the applicability of FEP+ to situations where crystal structures are unavailable, here we have applied the FEP+ approach to homology models of 12 different proteins covering 316 mutations. By comparing predictions obtained with homology models to those obtained using crystal structures, we have identified that local rather than global sequence conservation between target and template sequence is a determining factor in the accuracy of predictions. By excluding mutation sites with low local sequence identity (<40%) to a template structure, we have obtained predictions with comparable performance to crystal structures (R
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