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. 2024 Jan 2;40(1):btad761.
doi: 10.1093/bioinformatics/btad761.

pyCapsid: identifying dominant dynamics and quasi-rigid mechanical units in protein shells

Colin Brown  1   2 , Anuradha Agarwal  1   3 , Antoni Luque  1   3   4   5
Affiliations

pyCapsid: identifying dominant dynamics and quasi-rigid mechanical units in protein shells

Colin Brown et al. Bioinformatics. .

Abstract

Summary: pyCapsid is a Python package developed to facilitate the characterization of the dynamics and quasi-rigid mechanical units of protein shells and other protein complexes. The package was developed in response to the rapid increase of high-resolution structures, particularly capsids of viruses, requiring multiscale biophysical analyses. Given a protein shell, pyCapsid generates the collective vibrations of its amino-acid residues, identifies quasi-rigid mechanical regions associated with the disassembly of the structure, and maps the results back to the input proteins for interpretation. pyCapsid summarizes the main results in a report that includes publication-quality figures.

Availability and implementation: pyCapsid's source code is available under MIT License on GitHub. It is compatible with Python 3.8-3.10 and has been deployed in two leading Python package-management systems, PIP and Conda. Installation instructions and tutorials are available in the online documentation and in the pyCapsid's YouTube playlist. In addition, a cloud-based implementation of pyCapsid is available as a Google Colab notebook. pyCapsid Colab does not require installation and generates the same report and outputs as the installable version. Users can post issues regarding pyCapsid in the repository's issues section.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1.
Figure 1.
pyCapsid’s key steps. (a) The protein shell (atom coordinates, atom types, and B-factors) is inputted using a PDB file (or a PDB ID). (b) The elastic network model (ENM) is calibrated (parametrized). (c) Normal mode analysis (NMA) determines the distance fluctuations between residues. (d) The correlation coefficient of predicted and experimental B-factors is generated for quality control. (e) Spectral clustering is applied to obtain the quasi-rigid molecular domains in the capsid. (f) The fluctuations between residues within the rigid clusters are calculated. (g) The results are mapped back to the capsid protein atomic model for structural interpretation.
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