An Integrative Framework for Mapping Orientational Landscapes of Peripheral Membrane Proteins by Paramagnetic NMR and Atomistic Simulation

The functions of peripheral membrane proteins
(PMPs) can be critically influenced by their orientations on
membrane surfaces, which are inherently dynamic and challenging
to characterize with precision. Molecular dynamics (MD)
simulations, while powerful, face limitations in force field accuracy
and sampling, particularly for systems involving intricate protein−
lipid interactions. Here, we employ artifact-free membrane
paramagnetic relaxation enhancement (mPRE) data as a
quantitative benchmark to evaluate and refine MD simulations of
KRas4B, a classical PMP, bound to anionic bilayers. Discrepancies
between state-of-the-art simulations and experimental data are
quantified and attributed to both inadequate sampling and force
field inaccuracies. By fine-tuning the electrostatic interactions between the negatively charged protein and lipid, moderate
improvement in agreement with experimental data was achieved. Furthermore, we employed the maximum entropy method (MEM)
to reconcile MD simulations with the mPRE rates, generating a statistically robust orientational ensemble that quantitatively
reproduces the mPRE measurements. This integrative approach establishes a powerful framework for atomic-detail characterization
of orientational landscapes of PMPs, offering insights into their functional regulation and guiding therapeutic strategies.