Combining small angle X-ray scattering (SAXS) with protein structure predictions to characterize conformations in solution

Abstract

Accurate protein structure predictions, enabled by recent advances in machine learning algorithms, provide an entry point to probing structural mechanisms and to integrating and querying many types of biochemical and biophysical results. Limitations in such protein structure predictions can be reduced and addressed through comparison to experimental Small Angle X-ray Scattering (SAXS) data that provides protein structural information in solution. SAXS data can not only validate computational predictions, but can improve conformational and assembly prediction to produce atomic models that are consistent with solution data and biologically relevant states. Here, we describe how to obtain protein structure predictions, compare them to experimental SAXS data and improve models to reflect experimental information from SAXS data. Furthermore, we consider the potential for such experimentally-validated protein structure predictions to broadly improve functional annotation in proteins identified in metagenomics and to identify functional clustering on conserved sites despite low sequence homology.

Keywords: BILBOMD; CASP-SAXS; FoXS; Hybrid method; Metagenomics; Protein flexibility; Protein structure prediction.

Figure 1.. From predictions to solution structures.

A. Schematic showing overall strategy. Shown are representative protein predictions from AlphaFold2 and modification of that model using BILBOMD. The AlphaFold2 prediction is colored from blue to red based on confidence. Note that BILBOMD improved the fit to the experimental SAXS data and suggests that a low confidence helix (see red arrow) does not occur significantly in solution. B and C. Corresponding SAXS data in reciprocal and real space, respectively for experimental, AlphaFold2 protein structure prediction, and BILBOMD model.

Figure 2.. Equations used for comparison of SAXS curves in reciprocal space.

Figure 3.. XRCC1 solution state as identified by integrating AlphaFold2 protein structure prediction and SAXS modeling.

(A) AlphaFold2 model colored by per-residue confidence score (pLDDT) values. (B) Building of restraining file that controls BILBOMD conformational sampling of XRCC1 dimer by selecting rigid domain regions based on pLDDT values. (C) FoXS web server output shows multiple SAXS fit, residual, χ² values, and Radius of gyration for four XRCC1 monomers and four dimer models derived from BILBOMD modeling. Bottom panel-MultiFoXS implementation in FoXS web server show χ² values for one-, two- and three state model. The plot show comparison of SAXS fit and fit-residual for the one- and three-state model. (D) Three state model is shown together with the percentage of each model used to fit the SAXS data shown in panel C. Rigid body domains are highlighted.