Assembly Regulator

Author: Jiayi Wang
Last updated: May 2026

Description

This repository of "Assembly_Regulator" contains the core analysis and simulation code used for the study "Physical principles of building protein megacomplexes in a crowded milieu". The project models emergent assemblies of subunits from protein megacomplexes in a crowded, cell-like environment using coarse-grained statistical mechanics and experimental data, such as protein abundance and cross-linking mass spectrometry.

Key Features

The workflow represents each protein subunit in the INO80 complex as a coarse-grained bead and uses Grand Canonical Monte Carlo (GCMC) simulations to infer the parameters and physical principles that govern assembly:

1. Infer subunit-subunit interaction energies from cross-linking contact intensities.
2. Infer subunit chemical potentials from empirical relative abundances.
3. Classify subunits as convergent or divergent based on whether abundance converges in a grand-canonical reservoir setting.
4. Map particle number versus chemical potential for selected subunits.
5. Perturb particle numbers in canonical simulations to quantify changes in accessible volume, potential energy, and network structure.

Use case

The use case is the assembly of the yeast INO80 chromatin-remodeling complex.

Repository Structure

• Int_convergence/: inverse determination of pair interaction energies from cross-linking-derived contact frequencies.
• Mu_convergence/: inverse determination of chemical potentials for individual subunits while other subunit counts are fixed.
• N_mu_diagram/: scans of particle number as a function of chemical potential.
• N_perturbation_CMC/: canonical particle-number perturbation analyses, including accessible volume and potential energy processing.
• graphing/: conversion of LAMMPS trajectories into graph edgelists.
• graph_statistics/: analysis of graph-derived coordination statistics.

Each subdirectory contains a README with more specific inputs, outputs, and execution notes.

Main Requirements

The scripts are intended for an HPC environment and assume access to:

• LAMMPS with MPI support (lmp_mpi).
• MATLAB for iterative parameter updates and contact analysis.
• Python 3 with numpy, pandas, scipy, networkx, ovito, matplotlib, and tqdm as needed by the analysis scripts.
• A SLURM scheduler for the included .slurm submission scripts.

Several scripts contain absolute paths from the original compute environment such as /gscratch/..., /mmfs1/..., or /home/[PATH_TO_FILE]/. Update these paths before running the code in a new location.

Workflow

1. Run Int_convergence/ to infer pair interaction energies.
2. Use the inferred interactions in Mu_convergence/ to determine chemical potentials for each subunit.
3. Use N_mu_diagram/ to examine particle-number response over chemical potential scans.
4. Use canonical perturbation trajectories with N_perturbation_CMC/ to quantify the systemic thermodynamic effects of subunit particle number perturbation.
5. Use canonical perturbation trajectories with graphing/, and graph_statistics/ to quantify the change in protein-protein interaction network induced by subunit abundance perturbation.

Citation

Physical principles of building protein megacomplexes in a crowded milieu Jiayi Wang, Jules Nde, Andrei G. Gasic, Jacob Haseley, Margaret S. Cheung

https://doi.org/10.48550/arXiv.2602.14005

Ackowledgement

JW, JN, and JH thank the support from the National Science Foundation MCB 2221824. This work is also partially supported by the NW-BRaVE for Biopreparedness project funded by the U. S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research, under FWP 81832. A portion of this research was performed on a project award (Enhancing biopreparedness through a model system to understand the molecular mechanisms that lead to pathogenesis and disease transmission ) from the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. Pacific Northwest National Laboratory is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RL01830.