Accurate protein structure prediction with hydroxyl radical protein footprinting data

Abstract

Hydroxyl radical protein footprinting (HRPF) in combination with mass spectrometry reveals the relative solvent exposure of labeled residues within a protein, thereby providing insight into protein tertiary structure. HRPF labels nineteen residues with varying degrees of reliability and reactivity. Here, we are presenting a dynamics-driven HRPF-guided algorithm for protein structure prediction. In a benchmark test of our algorithm, usage of the dynamics data in a score term resulted in notable improvement of the root-mean-square deviations of the lowest-scoring ab initio models and improved the funnel-like metric Pnear for all benchmark proteins. We identified models with accurate atomic detail for three of the four benchmark proteins. This work suggests that HRPF data along with side chain dynamics sampled by a Rosetta mover ensemble can be used to accurately predict protein structure.

Validated Determination of NRG1 Ig-like Domain Structure by Mass Spectrometry Coupled with Computational Modeling

“…We employed our recent HRPF-guided Rosetta modeling protocol 29 to predict the structure of NRG1-Ig. As per our published protocol, only lnPF values measured from Trp, Phe, Tyr, His and Leu were used.…”

“…The Lindert group developed the first software to use covalent labeling data in automated Rosetta protein structure prediction 27,28 . Recently, Biehn and Lindert reported a more robust and computationally less expensive method for using HR-HRPF data to generate protein models using conical neighbor count instead of <SASA>, which successfully identified ab initio models of accurate atomic detail for three of the four benchmark proteins examined 29 . However, while these studies indicate the potential of HR-HRPF for the determination of protein structure, no protein of unknown structure has had its structure determined solely using HR-HRPF data to inform computational modeling.…”

“…The first team used HR-HRPF to quantitatively measure topography of various amino acid side chains of the NRG1-Ig. Models of the protein were generated via Rosetta ab initio modeling, scored with the HRPF-guided Rosetta score term, then subjected to a Rosetta relaxation ensemble 29 from which a top scoring model was identified. Meanwhile, the second team determined the structure of NRG1 using standard heteronuclear solution NMR techniques.…”

Protein structure prediction using residue-resolved protection factors from hydrogen-deuterium exchange NMR

“…The accuracy of computational methods can be significantly improved by the inclusion of experimental data (Seffernick and Lindert, 2020). Inclusion efforts began in the 1980s with NMR and X-ray crystallography, with more recent studies aiming toward including data from lower-resolution methods, such as electron paramagnetic resonance (EPR), mass spectrometry (MS), and cryo-EM (Alexander et al, 2008;Aprahamian et al, 2018;Aprahamian and Lindert, 2019;Biehn and Lindert, 2021;Bowers et al, 2000;DiMaio et al, 2015;Harvey et al, 2019;Lindert et al, 2012;Pilla et al, 2017;Roberts et al, 2017;Seffernick et al, 2019a;Srivastava et al, 2018;van Zundert et al, 2015). Ideally, these types of experimental data would be high-throughput and require a smaller sample size.…”

The inhibition mechanism of carp (Cyprinus carpio) stefin to cathepsin B and their tertiary structures

“…X‐ray diffraction (XRD) and nuclear magnetic resonance (NMR) are the two main methods for the study of the tertiary structure of protein (Haran & Mazal, 2020; Biehn & Linder, 2021). However, they always require extremely complex preprocessing and high analysis cost.…”