Abstract

Mechanosensitive Piezo1 channels are essential mechanotransduction proteins in eukaryotes. Their curved transmembrane domains, called arms, create a convex membrane deformation, or footprint, which is predicted to flatten in response to increased membrane tension. Here, using a hyperbolic tangent model, we show that, due to the intrinsic bending rigidity of the membrane, the overlap of neighboring Piezo1 footprints produces a flattening of the Piezo1 footprints and arms. Multiple all-atom molecular dynamics simulations of Piezo1 further reveal that this tension-independent flattening is accompanied by gating motions that open an activation gate in the pore. This open state recapitulates experimentally obtained ionic selectivity, unitary conductance, and mutant phenotypes. Tracking ion permeation along the open pore reveals the presence of intracellular and extracellular fenestrations acting as cation-selective sites. Simulations also reveal multiple potential binding sites for phosphatidylinositol 4,5-bisphosphate. We propose that the overlap of Piezo channel footprints may act as a cooperative mechanism to regulate channel activity.

Highlights

  • Ð6Þ where C is the covariance matrix for the gaussian function, zo is the plateau height of the gaussian dome model, h is distance from the plateau to the peak of the dome model, and μ is the coordinates of the dome model peak

  • Since C is a covariance matrix, it is by definition positive semi-definite and symmetric

  • For fitting purposes, this model was recast in terms of the standard deviations σp[1]; σp2 of the gaussian model along its two principal axes p1, p2, and angle of orientation θ such that h iÀ1 À1

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Summary

Introduction

Ð6Þ where C is the covariance matrix for the gaussian function, zo is the plateau height of the gaussian dome model, h is distance from the plateau to the peak of the dome model, and μ is the coordinates of the dome model peak. For fitting purposes, this model was recast in terms of the standard deviations σp[1]; σp of the gaussian model along its two principal axes p1, p2, and angle of orientation θ such t

Methods
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Conclusion

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