Extended Experimental Inferential Structure Determination Method in Determining the Structural Ensembles of Disordered Protein States
| Autor: | Claudiu C. Gradinaru, Teresa Head-Gordon, Julie D. Forman-Kay, Mickael Krzeminski, James Lincoff, Gregory-Neal W. Gomes, João M.C. Teixeira, Mojtaba Haghighatlari |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
010402 general chemistry 01 natural sciences Biochemistry Condensed Matter::Disordered Systems and Neural Networks Article lcsh:Chemistry 03 medical and health sciences q-bio.BM Materials Chemistry Environmental Chemistry Conformational isomerism Physics Quantitative Biology::Biomolecules Small-angle X-ray scattering Chemical shift Relaxation (NMR) General Chemistry Single-molecule experiment 0104 chemical sciences Characterization (materials science) 030104 developmental biology Förster resonance energy transfer Structural biology lcsh:QD1-999 Chemical physics physics.bio-ph |
| Zdroj: | Commun Chem Communications Chemistry, Vol 3, Iss 1, Pp 1-12 (2020) Communications chemistry, vol 3, iss 1 |
| Popis: | Proteins with intrinsic or unfolded state disorder comprise a new frontier in structural biology, requiring the characterization of diverse and dynamic structural ensembles. Here we introduce a comprehensive Bayesian framework, the Extended Experimental Inferential Structure Determination (X-EISD) method, which calculates the maximum log-likelihood of a disordered protein ensemble. X-EISD accounts for the uncertainties of a range of experimental data and back-calculation models from structures, including NMR chemical shifts, J-couplings, Nuclear Overhauser Effects (NOEs), paramagnetic relaxation enhancements (PREs), residual dipolar couplings (RDCs), hydrodynamic radii (Rh), single molecule fluorescence Forster resonance energy transfer (smFRET) and small angle X-ray scattering (SAXS). We apply X-EISD to the joint optimization against experimental data for the unfolded drkN SH3 domain and find that combining a local data type, such as chemical shifts or J-couplings, paired with long-ranged restraints such as NOEs, PREs or smFRET, yields structural ensembles in good agreement with all other data types if combined with representative IDP conformers. Characterising ensembles and populations of disordered structures is a challenge in structural biology. Here a Bayesian model allows solution data from NMR, fluorescence, and SAXS experiments to be synthesised in order to quantify the conformational distribution of disordered protein states. |
| Databáze: | OpenAIRE |
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