The Advanced Photon Source
a U.S. Department of Energy Office of Science User Facility

Soft Matter Interest Group - Characterizing Peripheral Membrane Proteins with Neutron Reflectometry

Type Of Event
Sponsoring Division
Frank Heinrich, Department of Physics, Carnegie Mellon University, and Center for Neutron Research, National Institute of Standards and Technology
Binhua Lin, Wei Bu, and Natalie Chen
Start Date
Start Time
10:00 a.m.

ABSTRACT: A significant fraction of peripheral membrane proteins has structural flexibility with biomedical implications. Neutron reflectometry is a suitable method to structurally characterize ensembles of such membrane-bound proteins in a biomimetic environment, albeit at low spatial resolution. I will review our longstanding method developments in supported lipid membranes and biological neutron reflectometry [1], and introduce a computational framework for experimental optimization using information theory [2]. I will then highlight recent progress in integrative membrane-protein structure modeling, combining thermodynamic studies, complementary structural techniques, and molecular simulations to derive a high-resolution, dynamic structural model relevant to biomedical applications. I will demonstrate these methods using the cancer-related KRAS [3] and Arf [4] proteins and the HIV-1 accessory protein Nef.

[1] Eells, R. et al. Structural investigations of membrane-associated proteins by neutron reflectometry. in Characterization of Biological Membranes (eds. Nieh, M.-P., Heberle, F. A. & Katsaras, J.) 87–130 (De Gruyter, 2019)
[2] Treece, B. W. et al. Optimization of reflectometry experiments using information theory. Journal of Applied Crystallography 52, 47–59 (2019).
[3] Heinrich F. et al. Membrane-Bound KRAS Approximates an Entropic Ensemble of Configurations. Biophysical Journal 120:4055 (2021)
[4] Soubias O. et al. Membrane surface recognition by the ASAP1 PH domain and consequences for interactions with the small GTPase Arf1. Science Advances 6:eabd1882 (2020)

Meeting ID: 942 2008 0385
Password: 013444



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