ArticleBiophysical journal2021
Refining conformational ensembles of flexible proteins against small-angle x-ray scattering data.
Article in Biophysical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.
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24 citing papers in PubMed, 40 citations in OpenAlex.
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- Atomic resolution ensembles of intrinsically disordered proteins with Alphafold.Nature communications · 2026Article
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- GōMartini 3: From large conformational changes in proteins to environmental bias corrections.Nature communications · 2025Article
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- Design of intrinsically disordered protein variants with diverse structural properties.Science advances · 2024Article
- Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution.Nature communications · 2024Article
- Autonomous screening of complex phase spaces using Bayesian optimization for SAXS measurements.Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment · 2023Article
- Design of intrinsically disordered protein variants with diverse structural properties.bioRxiv : the preprint server for biology · 2023Article
- Architecture of the MKK6-p38α complex defines the basis of MAPK specificity and activation.Science (New York, N.Y.) · 2023Article
- Data-Driven Models for Predicting Intrinsically Disordered Protein Polymer Physics Directly from Composition or Sequence.Molecular systems design & engineering · 2023Article
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- Assessment of models for calculating the hydrodynamic radius of intrinsically disordered proteins.Biophysical journal · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intrinsically disordered proteins and flexible regions in multidomain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modeling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model (i.e., an algorithm to calculate experimental observables from individual conformations or ensembles). In many cases, this involves one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle x-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data but across the entire ensemble. Here, we present a protocol to dissect the effect of the free parameters on the calculated SAXS intensities and to identify a reliable set of values. We have implemented this procedure in our Bayesian/maximum entropy framework for ensemble refinement and demonstrate the results on four intrinsically disordered proteins and a protein with three domains connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects and suggest that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins.
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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.