MolClustPy: A Python Package to Characterize Multivalent Biomolecular Clusters

bioRxiv [Preprint]. 2023 Mar 15:2023.03.14.532640. doi: 10.1101/2023.03.14.532640.

Abstract

S ummary: Low-affinity interactions among multivalent biomolecules may lead to the formation of molecular complexes that undergo phase transitions to become extra-large clusters. Characterizing the physical properties of these clusters is important in recent biophysical research. Due to weak interactions such clusters are highly stochastic, demonstrating a wide range of sizes and compositions. We have developed a Python package to perform multiple stochastic simulation runs using NFsim (Network-Free stochastic simulator), characterize and visualize the distribution of cluster sizes, molecular composition, and bonds across molecular clusters and individual molecules of different types.

A vailability 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/.

C ontact: achattaraj007@gmail.com , blinov@uchc.edu.

S upplementary information: Available at https://molclustpy.github.io/.

Publication types

  • Preprint