Protein Structure Prediction from NMR Hydrogen–Deuterium Exchange Data
| العنوان: | Protein Structure Prediction from NMR Hydrogen–Deuterium Exchange Data |
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| المؤلفون: | Justin T Seffernick, Daniel R Marzolf, Steffen Lindert |
| المصدر: | Journal of Chemical Theory and Computation. 17:2619-2629 |
| بيانات النشر: | American Chemical Society (ACS), 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Models, Molecular, Measure (data warehouse), Binding Sites, 010304 chemical physics, Protein Conformation, Computer science, Model selection, Ab initio, Deuterium Exchange Measurement, Proteins, Protein structure prediction, ENCODE, Amides, 01 natural sciences, Computer Science Applications, Protein structure, 0103 physical sciences, Benchmark (computing), Hydrogen–deuterium exchange, Physical and Theoretical Chemistry, Biological system, Nuclear Magnetic Resonance, Biomolecular |
| الوصف: | Amide hydrogen-deuterium exchange (HDX) has long been used to determine regional flexibility and binding sites in proteins; however, the data are too sparse for full structural characterization. Experiments that measure HDX rates, such as HDX-NMR, have far higher throughput compared to structure determination via X-ray crystallography, cryo-EM, or a full suite of NMR experiments. Data from HDX-NMR experiments encode information on the protein structure, making HDX a prime candidate to be supplemented by computational algorithms for protein structure prediction. We have developed a methodology to incorporate HDX-NMR data into ab initio protein structure prediction using the Rosetta software framework to predict structures based on experimental agreement. To demonstrate the efficacy of our algorithm, we examined 38 proteins with HDX-NMR data available, comparing the predicted model with and without the incorporation of HDX data into scoring. The root-mean-square deviation (rmsd, a measure of the average atomic distance between superimposed models) of the predicted model improved by 1.42 A on average after incorporating the HDX-NMR data into scoring. The average rmsd improvement for the proteins where the selected model rmsd changed after incorporating HDX data was 3.63 A, including one improvement of more than 11 A and seven proteins improving by greater than 4 A, with 12/15 proteins improving overall. Additionally, for independent verification, two proteins that were not part of the original benchmark were scored including HDX data, with a dramatic improvement of the selected model rmsd of nearly 9 A for one of the proteins. Moreover, we have developed a confidence metric allowing us to successfully identify near-native models in the absence of a native structure. Improvement in model selection with a strong confidence measure demonstrates that protein structure prediction with HDX-NMR is a powerful tool which can be performed with minimal additional computational strain and expense. |
| تدمد: | 1549-9626 1549-9618 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe132e4d78cbff915d234acb3eaa4f02Test https://doi.org/10.1021/acs.jctc.1c00077Test |
| حقوق: | CLOSED |
| رقم الانضمام: | edsair.doi.dedup.....fe132e4d78cbff915d234acb3eaa4f02 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15499626 15499618 |
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