Resources

Gaussian Accelerated Molecular Dynamics (GaMD)

Gaussian Accelerated Molecular Dynamics (GaMD) is a biomolecular enhanced sampling method that works by adding a harmonic boost potential to smoothen the system potential energy surface. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. GaMD has been demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low energy states of the biomolecules and characterize the protein folding and ligand binding pathways quantitatively.

PyReweighting

A toolkit of python scripts "PyReweighting" is provided for reweighting of aMD simulations. PyReweighting implements a list of commonly used reweighting methods, including (1) exponential average that reweights trajectory frames by the Boltzmann factor of the boost potential and then calculates the ensemble average for each bin, (2) Maclaurin series expansion that approximates the exponential Boltzmann factor, and (3) cumulant expansion that expresses the reweighting factor as summation of boost potential cumulants.

GLOW

GLOW integrates Gaussian accelerated molecular dynamics (GaMD) and Deep Learning (DL) for free energy profiling of biomolecules. First, all-atom GaMD enhanced sampling simulations are performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using convolutional neural network (CNN). Important structural contacts can be determined from DL models of saliency (attention) maps of the residue contact gradients, which allow for the identification of system reaction coordinates . Finally, free energy profiles of these reaction coordinates are calculated through energetic reweighting of GaMD simulations.

####################
VMD TCL scripts
####################

Following is a list of TCL scripts that can be executed with VMD (http://www.ks.uiuc.edu/Research/vmd/) using "vmd -dispdev text -e *.tcl". They can used to prepare systems for NAMD simulations and analyze simulation output trajectories, notably on viral capsids. Hope they are helpful for your research.

AddTime2VMDmovie.tcl
A TCL script used to take a set of .ppm images renderred with VMD ("Extensions" -> "Visualization" -> "Movie Maker"), resize/crop the images, add time, and then generate a .gif animation.

para.dat:

Sample input file for running AddTime2VMDmovie.tcl

AddTime2VMDmovie-examples.tgz

A test example for running AddTime2VMDmovie. Uncompress it with command: tar -xvzf AddTime2VMDmovie-examples.tgz

solvate.tcl
Generate the .psf and .pdb files from input PDB structure, solvate the structure in water and ionize the system with VMD to prepare the system for simulation.

analysis-capsid-cRadius-rmsd.tcl
1) Analyize the changes in the radii of viral capsid backbone, i.e., the average, maximum and minimum distances between atoms in the capsid backbone and the capsid center of mass, in a simulation trajectory.
2) Calculate the RMSD between viral capsid snapthots along simulation trajectory and a reference structure.

analysis-sasa.tcl
Calculate the interior, exerior and total SASA of viral capsids from a simulation trajectory.

analysis-capsid-volume.tcl
Calculate the volume of a viral capsid and that inside the capsid cavity. In case the capsid is solvated in a water box, the volume of the host medium outside of the capsid is also calculated.

analysis-capsid-waterdensity.tcl
Calculate the density of water inside viral capsid cavity and that outside of the capsid by using the volume data obtained from executing script "analysis-capsidvolume.tcl".

analysis-56mers-TR.tcl
Analyize the rigid-body translation and rotation of capsomeres (i.e., pentamers and hexamers) in CCMV capsid.

####################
MD/OPX
####################

MD/OPX stands for Molecular Dynamics/Order Parameter eXtrapolation. It is an approach designed to simulate large bionanosystems over long time periods by using short replica MD run(s) to extrapolate the structural order parameters (OPs) of the system over large time intervals and thus advance the system over long time.

The present implementation of MD/OPX is based on NAMD using its Tcl scripting interface and requires NAMD for running. A Fortran code is used to read the output structure of a short dt NAMD run, calculate the resultant OPs, extrapolate the OPs for dT, generate an atomic configuration at t+dT with the extrapolated OPs and put the result all-atom structure back into
NAMD to start the next (dt, dT) cycle. Please refer to the following papers for the theoretical details and implementation algorithms of MD/OPX:

Miao, Y. and P. J. Ortoleva, Molecular dynamics/order parameter extrapolation for bionanosystem simulations. J. Comp. Chem., 2008, 30(3): 423-437. (Abstract | PDF)

Miao, Y. and P. J. Ortoleva (2009), Viral Structural Transition Mechanisms Revealed by Multiscale Molecular Dynamics/Order Parameter eXtrapolation Simulation, Biopoplymers, 93, 61. (Abstract | PDF)

For simulating solvated systems, i.e., nanostructures solvated in a host medium, modules "solvation", "extraction of nanostructure snapshots" and "resolvation" are added to account for water molecules and ions. Refer to the following paper for the MD/OPX implementation and its application ot CCMV capsid swelling:

Miao, Y., J. E. Johnson and P. J. Ortoleva (2010), All-atom Multiscale Simulation of CCMV Capsid Swelling, J. Phys. Chem. B, 114(34), 11181–11195. (Abstract | PDF)

A copy of the latest verion of MD/OPX source code can be downloaded at MDOPX1.4.tgz (~17MB).

####################
Problem/Bug Reporting
####################

Please email Yinglong Miao at miao@ku.edu or yinglong.miao@gmail.com regarding any problems or bugs.

 

◇ Copyright Reserved © 2017-2021. Last updated: Mon, July 18, 2022