MolClustPy: a Python package to characterize multivalent biomolecular clusters

Bioinformatics. 2023 Jun 1;39(6):btad385. doi: 10.1093/bioinformatics/btad385.

Abstract

Summary: Low-affinity interactions among multivalent biomolecules may lead to the formation of molecular complexes that undergo phase transitions to become supply-limited large clusters. In stochastic simulations, such clusters display a wide range of sizes and compositions. We have developed a Python package, MolClustPy, which performs multiple stochastic simulation runs using NFsim (Network-Free stochastic simulator); MolClustPy characterizes and visualizes the distribution of cluster sizes, molecular composition, and bonds across molecular clusters. The statistical analysis offered by MolClustPy is readily applicable to other stochastic simulation software, such as SpringSaLaD and ReaDDy.

Availability and implementation: The software is implemented in Python. A detailed Jupyter notebook is provided to enable convenient running. Code, user guide, and examples are freely available at https://molclustpy.github.io/.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Computer Simulation
  • Research Design*
  • Software*