afrc – the Analytical Flory Random Coil

afrc is a Python-based package for computing polymeric properties for unfolded polypeptides using an analytical implementation of the so-called Flory Random Coil (the AFRC).

Briefly, the AFRC is a pre-parameterized polymer model that recapitulates the dimensions of a polypeptide in a theta solvent. Technically speaking, this means both the second and third virial coefficients are set to zero, such that the AFRC enjoys fractal scaling with a true scaling exponent of 0.5 and no finite-size effects. This makes it well-suited as a reference mode for developing intuition, providing a comparison against experimental data, or offering normalization factors for simulations or experiments alike.

We developed the AFRC as a convenient tool for contextualizing simulations and experiments of disordered proteins. The AFRC is not a predictor of the dimensions of intrinsically disordered proteins or protein regions, but it does offer a ‘null model’ for how one might expect an IDR of a given sequence to behave if chain-chain and chain-solvent interactions were perfectly counterbalanced.

The AFRC is parameterized against numerical simulations that recapitulate bona fide theta solvent behavior. As such, you only need to provide an amino acid sequence as input, and the AFRC can provide a variety of information back instantaneously, including:

1. The ensemble-average end-to-end distance.

2. The end-to-end distance distribution.

3. The ensemble-average radius of gyration.

4. The end-to-end distance distribution.

5. The ensemble-average hydrodynamic radius

6. All inter-residue average distances and distance distributions

7. Inter-residue contact fractions

Finally, the afrc package also implements several additional polymer models, including the Worm-like chain (WLC) model [Brien2009], the self-avoid walk (SAW) model [Brien2009], and a scaling-exponent SAW model (SAW-ν) [Zheng2018].

Contents:

• Overview
• Installation
  • Installation from PyPI
  • Installation from GitHub
• AFRC Quickstart
  • Usage
• AnalyticalFRC

Indices and tables

• Index

• Module Index

• Search Page

References

[Brien2009] (1,2)

O’Brien, E. P., Morrison, G., Brooks, B. R., & Thirumalai, D. (2009). How accurate are polymer models in the analysis of Forster resonance energy transfer experiments on proteins? The Journal of Chemical Physics, 130(12), 124903.

[Zheng2018]

Zheng, W., Zerze, G. H., Borgia, A., Mittal, J., Schuler, B., & Best, R. B. (2018). Inferring properties of disordered chains from FRET transfer efficiencies. The Journal of Chemical Physics, 148(12), 123329.