Carbonara: SAXS-Guided Conformational Seeding Accesses Solution-State Ensembles Inaccessible to Conventional Molecular Dynamics [dataset]

Esses, Jonathan (University of Southampton); Fisher, Hayden (European Synchrotron Radiation Facility); Rambo, Robert (Diamond Light Source Ltd); Degiacomi, Matteo (University of Edinburgh); Bale, Arron (Durham University); Prior, Christopher (Durham University); McKeown, Josh (Durham University); Brown, Cameron (University of Southampton)

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Carbonara: SAXS-Guided Conformational Seeding Accesses Solution-State Ensembles Inaccessible to Conventional Molecular Dynamics [dataset] Open Access

Proteins in solution often occupy conformational ensembles that differ from the static states captured by crystallography or AI-based structure prediction. Generating structural models consistent with solution measurements remains challenging when available structures lie far from the relevant conformational basin. Conventional molecular dynamics (MD) simulations often fail to cross the energy barriers separating these states on accessible timescales, and statistical reweighting cannot recover conformations never sampled. Here we present Carbonara, a framework that uses experimental small-angle X-ray scattering (SAXS) data to guide coarse-grained backbone sampling, generating physically plausible seed conformations from which MD can explore the solution-state landscape. Carbonara is coupled to Wiggle, a Ca-based SAXS forward model validated against explicit-solvent calculations, enabling rapid evaluation of thousands of candidate conformations. We apply the framework to two representative cases: an AI-predicted multi-domain helicase (SMARCAL1), where incorrect domain arrangement produces disagreement with solution scattering, and a crystallographic antibody fragment (ChiLob7/4 IgG2), where lattice packing enforces a compact geometry not representative of the solution state conformation. MD ensembles derived from the crystal (in the case of ChiLob) or AF (in the case of smarcal) structures, fail to agree with the SAXS data, while MD ensembles derived from the carbonara structures are consistent with SAXS. We anticipate Carbonara will be used in future to capture biologically-relevant solution-phase protein dynamics, and have developed user friendly software to facilitate its use.

Descriptions

Resource type: Dataset
Contributors: Creator: McKeown, Josh ¹
Creator: Prior, Christopher ¹
Bale, Arron ¹
Brown, Cameron ²
Esses, Jonathan ²
Fisher, Hayden ³
Rambo, Robert ⁴
Degiacomi, Matteo ⁵

¹ Durham University
² University of Southampton
³ European Synchrotron Radiation Facility
⁴ Diamond Light Source Ltd
⁵ University of Edinburgh
Funder: Engineering and Physical Sciences Research Council
Research methods
Other description
Keyword
Subject: Structural bioinformatics
Proteins--Structure--Computer simulation
Computational biology
Molecular biology--Mathematical models
Small-angle x-ray scattering
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Identifier: ark:/32150/r2dr26xx42n
doi:10.15128/r2dr26xx42n
Rights: Creative Commons Attribution 4.0 International (CC BY)
Publisher: Durham University
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