ABSTRACT
Intrinsically disordered proteins (IDPs) often contain proline residues, which undergo cis/trans isomerisation. While molecular dynamics (MD) simulations have the potential to fully characterise the proline cis and trans sub-ensembles, they are limited by the slow timescales of isomerisation and force field inaccuracies. Nuclear magnetic resonance (NMR) spectroscopy can report on ensemble-averaged observables for both the cis and trans proline states, but a full atomistic characterisation of these sub-ensembles is challenging. Given the importance of proline cis/trans isomerisation for influencing the conformational sampling of disordered proteins, we employed a combination of all-atom MD simulations with enhanced sampling (metadynamics), NMR, and small-angle X-ray scattering (SAXS) to characterise the two sub-ensembles of the ORF6 C-terminal region (ORF6CTR) from SARS-CoV-2 corresponding to the proline-57 (P57) cis and trans states. We performed MD simulations in three distinct force fields: AMBER03ws, AMBER99SB-disp, and CHARMM36m, which are all optimised for disordered proteins. Each simulation was run for an accumulated time of 180-220 µs until convergence was reached, as assessed by blocking analysis. A good agreement between the cis-P57 populations predicted from metadynamics simulations in AMBER03ws was observed with populations obtained from experimental NMR data. Moreover, we observed good agreement between the radius of gyration predicted from the metadynamics simulations in AMBER03ws and that measured using SAXS. Our findings suggest that both the cis-P57 and trans-P57 conformations of ORF6CTR are extremely dynamic and that interdisciplinary approaches combining both multi-scale computations and experiments offer avenues to explore highly dynamic states that cannot be reliably characterised by either approach in isolation.
SIGNIFICANCE This study employs MD simulations (with metadynamics), NMR spectroscopy, and SAXS to elucidate the individual cis and trans proline conformations of ORF6CTR from SARS-CoV-2. The good agreement on proline cis/trans populations observed in experiments (NMR) and those calculated from simulations in the AMBER03ws force field (with SAXS reweighting) showcases the efficiency of this interdisciplinary approach, which can be used to characterise highly dynamic disordered protein states, even for very slow processes. Furthermore, our study emphasises the importance of considering both computational and experimental methodologies to gain a more holistic understanding of highly dynamic proteins. The presented integrative approach sets a precedent for future studies aiming to explore complex and dynamic biological systems with slow transitions such as proline isomerisations.
Competing Interest Statement
The authors have declared no competing interest.
