Cells explore their environment by sensing and responding to mechanical forces. Many fundamental cellular processes, such as cell migration, differentiation, and homeostasis, take advantage of this sensing mechanism. At molecular level mechanosensing is mainly driven by mechanically active proteins. These proteins are able to sense and respond to forces by, e.g., undergoing conformational changes, exposing cryptic binding sites, or even by becoming more tightly bound to one another. In humans, defective responses to forces are known to cause a plethora of pathological conditions, including cardiac failure, pulmonary injury and are also linked to cancer. Microorganisms also take advantage of mechano-active proteins and proteins complexes. Employing single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations we have investigated force propagation pathways through a mechanically active protein complexes.

Spotlight: Mathematics for Proteins (Aug 2003)

Stretching an alpha helix

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Many proteins in living cells are nanomachines that undergo mechanical transformations. Modern modeling methods permit the manipulation of such proteins to discover the physical mechanism behind their function. Applying forces, one can induce geometrical changes characteristic of the proteins' role in the cell and, beyond obtaining qualitative insight, calculate the work W done during a machine cycle. Unfortunately, the manipulations realized in computer modeling include irreversible work which needs to be discounted for comparison with the energetics of naturally occurring, i.e., slower, machine cycles. Recent reports [1 , 2] suggest how this can be achieved mathematically by means of statistical physics. The new methodology is demonstrated on the most simple mechanical transformation of a protein, the stretching of a so-called alpha-helix which behaves like a coiled spring.

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  • Mapping mechanical force propagation through biomolecular complexes. Constantin Schoeler, Rafael C. Bernardi, Klara H. Malinowska, Ellis Durner, Wolfgang Ott, Edward A. Bayer, Klaus Schulten, Michael A. Nash, and Hermann E. Gaub. Nano Letters, 15:7370-7376, 2015.
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