Jump to main content
Jump to site search

Issue 36, 2017
Previous Article Next Article

Molecular dynamics-based strength estimates of beta solenoid proteins

Author affiliations


The use of beta solenoid proteins as functionalizable, nanoscale, self-assembling molecular building blocks may have many applications, including templating the growth of wires or higher-dimensional structures. By understanding their mechanical strengths, we can efficiently design the proteins for specific functions. We present a study of the mechanical properties of seven beta solenoid proteins using GROMACS molecular dynamics software to produce force/torque-displacement data, implement umbrella sampling of bending/twisting trajectories, produce Potentials of Mean Force (PMFs), extract effective spring constants, and calculate rigidities for two bending and two twisting directions for each protein. We examine the differences between computing the strength values from force/torque-displacement data alone and PMF data, and show how higher precision estimates can be obtained from the former. In addition to the analysis of the methods, we report estimates for the bend/twist persistence lengths for each protein, which range from 0.5–3.4 μm. We note that beta solenoid proteins with internal disulfide bridges do not enjoy enhanced bending or twisting strength, and that the strongest correlate with bend/twist rigidity is the number of hydrogen bonds per turn. In addition, we compute estimates of the Young's modulus (Y) for each protein, which range from Y = 3.5 to 7.2 GPa.

Graphical abstract: Molecular dynamics-based strength estimates of beta solenoid proteins

Back to tab navigation

Supplementary files

Publication details

The article was received on 29 May 2017, accepted on 31 Jul 2017 and first published on 31 Jul 2017

Article type: Paper
DOI: 10.1039/C7SM01070B
Citation: Soft Matter, 2017,13, 6218-6226
  •   Request permissions

    Molecular dynamics-based strength estimates of beta solenoid proteins

    A. Parker, K. Ravikumar and D. Cox, Soft Matter, 2017, 13, 6218
    DOI: 10.1039/C7SM01070B

Search articles by author