ArticleHuman mutation2019
Predicting changes in protein stability caused by mutation using sequence-and structure-based methods in a CAGI5 blind challenge.
Article in Human mutation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- AI-GuidedJournal of the American Chemical Society · 2026Article
- Development of Antagonist Peptides of the Crk/CrkL SH2 Domains by Modifying the Peripheral Amino Acid Residues of the YXXP Motif.Biochemistry · 2026Article
- Prediction of mutation-induced protein stability changes based on the geometric representations learned by a self-supervised method.BMC bioinformatics · 2024Article
- Protein stability prediction by fine-tuning a protein language model on a mega-scale dataset.PLoS computational biology · 2024Article
- CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods.Genome biology · 2024Article
- Topological deep learning based deep mutational scanning.Computers in biology and medicine · 2023Article
- Computational modeling and prediction of deletion mutants.Structure (London, England : 1993) · 2023Article
- A mutation in DOK7 in congenital myasthenic syndrome forms aggresome in cultured cells, and reduces DOK7 expression and MuSK phosphorylation in patient-derived iPS cells.Human molecular genetics · 2023Article
- Unravelling the epidemiological diversity of Zika virus by analyzing key protein variations.Archives of virology · 2023Article
- VariBench, new variation benchmark categories and data sets.Frontiers in bioinformatics · 2023Article
- High-Affinity Antibodies Designing of SARS-CoV-2 Based on Molecular Dynamics Simulations.International journal of molecular sciences · 2022Article
- Discovery of the Key Mutation Site Influencing the Thermostability ofInternational journal of molecular sciences · 2022Article
- Structure-function relationships of the disease-linked A218T oxytocin receptor variant.Molecular psychiatry · 2022Article
- Multitasking NaBiomedicines · 2022Review
- Site-wise Diversification of Combinatorial Libraries Using Insights from Structure-guided Stability Calculations.Methods in molecular biology (Clifton, N.J.) · 2022Article
- A New World Monkey Resembles Human in Bitter Taste Receptor Evolution and Function via a Single Parallel Amino Acid Substitution.Molecular biology and evolution · 2021Article
- Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures.Molecular biotechnology · 2021Review
- Cancer-causing BRCA2 missense mutations disrupt an intracellular protein assembly mechanism to disable genome maintenance.Nucleic acids research · 2021Article
- Article
- SARS-CoV-2 Spike Glycoprotein and ACE2 Interaction Reveals Modulation of Viral Entry in Wild and Domestic Animals.Frontiers in medicine · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
Predicting the impact of mutations on proteins remains an important problem. As part of the CAGI5 frataxin challenge, we evaluate the accuracy with which Provean, FoldX, and ELASPIC can predict changes in the Gibbs free energy of a protein using a limited data set of eight mutations. We find that different methods have distinct strengths and limitations, with no method being strictly superior to other methods on all metrics. ELASPIC achieves the highest accuracy while also providing a web interface which simplifies the evaluation and analysis of mutations. FoldX is slightly less accurate than ELASPIC but is easier to run locally, as it does not depend on external tools or datasets. Provean achieves reasonable results while being computational less expensive than the other methods and not requiring a structure of the protein. In addition to methods submitted to the CAGI5 community experiment, and with the aim to inform about other methods with high accuracy, we also evaluate predictions made by Rosetta's ddg_monomer protocol, Rosetta's cartesian_ddg protocol, and thermodynamic integration calculations using Amber package. ELASPIC still achieves the highest accuracy, while Rosetta's catesian_ddg protocol appears to perform best in capturing the overall trend in the data.
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