ArticlePloS one2015
Capturing conformational States in proteins using sparse paramagnetic NMR data.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 35 citations in OpenAlex.
- Article
- Combined NMR and molecular dynamics conformational filter identifies unambiguously dynamic ensembles of Dengue protease NS2B/NS3pro.Communications biology · 2023Article
- Recent Advances in NMR Protein Structure Prediction with ROSETTA.International journal of molecular sciences · 2023Review
- Reweighting methods for elucidation of conformation ensembles of proteins.Current opinion in structural biology · 2022Review
- Modeling of protein conformational changes with Rosetta guided by limited experimental data.Structure (London, England : 1993) · 2022Article
- Paramagnetic Chemical Probes for Studying Biological Macromolecules.Chemical reviews · 2022Review
- Article
- Structure and Dynamics of Zika Virus Protease and Its Insights into Inhibitor Design.Biomedicines · 2021Review
- Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement.Journal of chemical information and modeling · 2020Article
- Probing contacts of inhibitor locked in transition states in the catalytic triad of DENV2 type serine protease and its mutants by 1H, 19F and 15 N NMR spectroscopy.BMC molecular and cell biology · 2020Article
- Insights into Structures and Dynamics of Flavivirus Proteases from NMR Studies.International journal of molecular sciences · 2020Review
- A Double-Armed, Hydrophilic Transition Metal Complex as a Paramagnetic NMR Probe.Angewandte Chemie (International ed. in English) · 2019Review
- Structure restraints from heteronuclear pseudocontact shifts generated by lanthanide tags at two different sites.Journal of biomolecular NMR · 2017Article
- An encodable lanthanide binding tag with reduced size and flexibility for measuring residual dipolar couplings and pseudocontact shifts in large proteins.Journal of biomolecular NMR · 2016Article
- Introduction to the Rosetta Special Collection.PloS one · 2015Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Capturing conformational changes in proteins or protein-protein complexes is a challenge for both experimentalists and computational biologists. Solution nuclear magnetic resonance (NMR) is unique in that it permits structural studies of proteins under greatly varying conditions, and thus allows us to monitor induced structural changes. Paramagnetic effects are increasingly used to study protein structures as they give ready access to rich structural information of orientation and long-range distance restraints from the NMR signals of backbone amides, and reliable methods have become available to tag proteins with paramagnetic metal ions site-specifically and at multiple sites. In this study, we show how sparse pseudocontact shift (PCS) data can be used to computationally model conformational states in a protein system, by first identifying core structural elements that are not affected by the environmental change, and then computationally completing the remaining structure based on experimental restraints from PCS. The approach is demonstrated on a 27 kDa two-domain NS2B-NS3 protease system of the dengue virus serotype 2, for which distinct closed and open conformational states have been observed in crystal structures. By changing the input PCS data, the observed conformational states in the dengue virus protease are reproduced without modifying the computational procedure. This data driven Rosetta protocol enables identification of conformational states of a protein system, which are otherwise difficult to obtain either experimentally or computationally.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.