HybridMC: Hybrid Monte Carlo Protein Folding

HybridMC simulates the event-driven dynamics of coarse-grained protein folding. The entropy and mean first passage times (MFPT) of each bond forming or breaking event are calculated, and the Markov transition rate matrix is constructed. The average time needed to fold to the protein's native state, starting from the unfolded state, is evaluated under two conditions.

For more information, see the publication or the preprint.

Directories

See top level comment in each file for more details as to what each file does. Some top level comments also contain examples of how to run each file, if complicated.

• src: C++ source code for HybridMC program

• examples: JSON inputs which specify protein configuration and Bash scripts for running HybridMC

• tools: Python scripts for running HybridMC and extracting data such as the MFPT

• tree: C++ and Bash scripts for generating tree plots

• crambin_s_bias_mfpt: biased entropy and MPFT results for crambin

C++ Program Details

Prerequisite Software

• C++17 compiler with support for C++20 bit library

  see bit operations under C++20 compiler support

  tested with GCC 9.3.0 on CentOS 7.9

• Minimum CMake version is 3.13.1

• Ninja

• HDF5 version 1.10 or later

• Boost

Commands for Compiling

To compile HybridMC for development and testing:

make debug

To perform unit test with verbose output:

cd debug
ctest -V

To compile HybridMC for running simulations:

make release

Python Program Details

Run Program

For any protein with or without staircase potentials, use run.py; for non-staircase crambin folding, use run.py or crambin.sh.

Calculate Entropy

To get biased entropy of each state, use diff_s_bias.py, followed by avg_s_bias.py. To get biased entropy of each state which includes the staircase potential, use diff_s_bias_stair.py, followed by avg_s_bias.py.

To find which transition gives smallest entropy difference, use min_diff_s_bias.py. To get percent error for the entropy of one transition, use get_error_s_bias.py.

Calculate MFPT

To calculate MFPT for a single transition, use mfpt.py. To calculate MFPT for all transitions in current dir, use run_mfpt.py. To combine the MFPT for each step of staircase into a single MFPT for the transition, use mfpt_for_stair.py.

Rerun Files

To move JSON and HDF5 files needed for rerunning transitions to rerun dir, use get_rerun_files.py. To rerun files that were moved to rerun dir, use rerun.py.

Calculate Energy and Folding Time

To calculate energy of each intermediate state and average time to fold to the native state:

1. use fixed_e.py if all nonlocal bonds have the same energy, and temperature varies with each repeat of the simulation, or

2. use min_e.py to hold probability of native state high relative to the unfolded state.

Tree Plots

To output data in the correct format for the tree plots, run fixed_e_tree.py or min_e_tree.py to create a .dat and .mtx file. Then, to generate the tree plots for crambin, run crambin_fixed_e.sh or crambin_min_e.sh, if the executables disconnectionDPS and constructPmatrix exist.

To create the disconnectionDPS executable, the disconnectionDPS package is needed, which can be downloaded here. The download contains many subdirectories, but the one needed for the tree plots is called DISCONNECT. Inside DISCONNECT/source/, to compile disconnectionDPS, run

make F90=gfortran

To compile constructPmatrix, run

g++ -O2 -o constructPmatrix constructPmatrix.cc $(gsl-config --cflags --libs)

Debug

To debug one transition which compiled successfully but crashed once it started running, use testing.py.