Biophysical Society Thematic Meeting | Bucharest 2026

Biophysics of Membrane Reactions in Brian

Thursday Speaker Abstracts

SEEING FUNCTION IN MOTION: COMPUTATIONAL METHODS FOR PROTEIN DYNAMICS Florence Tama RIKEN Center for Computational Science, Kobe, Japan Proteins involved in cellular signaling and transport undergo large-scale conformational changes that are essential for biological function but remain difficult to characterize using static structural approaches. The objective of this work is to develop and apply computational methods that integrate high-speed atomic force microscopy (HS-AFM) data with molecular modeling to characterize functionally relevant protein dynamics. HS-AFM measurements enable direct observation of nanometer-scale topography and conformational fluctuations of individual proteins under conditions that closely mimic physiological conditions. To interpret these experimental observables, HS-AFM data are combined with elastic network models, normal mode analysis, and data-driven analyses. This integrated framework quantifies AFM measurements in terms of collective, low-f requency protein motions, providing a dynamic description grounded in experimental data.The approach is illustrated using P-glycoprotein (P gp), an ATP-dependent efflux transporter. The analysis shows that P-gp is intrinsically dynamic in its apo state, with its nucleotide-binding domains (NBDs) undergoing large, spontaneous opening and closing motions. ATP binding shifts the conformational ensemble toward states characterized by NBD proximity and a strong tendency toward closure. These observations suggest that HS-AFM–informed computational modeling offers a promising route for probing protein dynamics, with potential applicability across a broader range of biological systems.

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