/mdtoolbox

MDToolbox: A MATLAB/Octave toolbox for statistical analysis of molecular dynamics trajectories

Primary LanguageMATLABOtherNOASSERTION

MDToolbox

MDToolbox is a MATLAB/Octave toolbox for statistical analysis of molecular dynamics (MD) simulation data of biomolecules. It consists of a collection of functions covering the following types of scientific computations:

  • (NEW) Unsupervised learning for correcting Markov State Models (Baum-Welch algorithm and others) (supported by JST PRESTO Project)
  • (NEW) Utilities for constructing Markov State Models (supported by JST PRESTO Project)
  • I/O for trajectory, coordinate, and topology files used for MD simulation
  • Least-squares fitting of structures
  • Potential mean force (PMF) or free energy profile from scattered data
  • Statistical estimates (WHAM and MBAR methods) from biased data
  • Dimensional reductions (Principal Component Analysis, and others)
  • Elastic network models (Gaussian and Anisotropic network models)
  • Utility functions, such as atom selections

For more information, see the documentation.

Install

See the documentation.

Docker

Docker image for MDToolbox is available. The following single line command starts Octave ready for use with MDToolbox.

$ docker run -it --rm -v $(pwd):/home/jovyan/work ymatsunaga/octave octave

For details, see the documentation.

Financial support

JST PRESTO Grant No. JPMJPR1679

Reference

Y. Matsunaga, and Y. Sugita, J. Chem. Phys. 148, 241731 (2018)

Note

This toolbox is now being ported into Julia https://github.com/ymatsunaga/MDToolbox.jl

Files used in our scientific papers

"Minimum Free Energy Path of Ligand-Induced Transition in Adenylate Kinase" PLoS Comput. Biol. (2012)

  • assignvoronoi.m - assigns Voronoi index to trajectory data
  • mbar.m - multistate Bennett acceptance ratio method
  • calcpca.m - Principal Component Analysis (PCA)

"Influence of Structural Symmetry on Protein Dynamics" PLoS One (2012)

  • anmsym.m - anisotropic network model for proteins with circular symmetries
  • calcpca.m - Principal Component Analysis (PCA)

"Sequential data assimilation for single-molecule FRET photon-counting data" J. Chem. Phys. (2015)

  • calcfret.m - generates a FRET photon-count sequence from distance time-series data
  • calccontactvector.m - calculates contact map vectors from trajectory data
  • calcpca.m - Principal Component Analysis (PCA)

"Dimensionality of Collective Variables for Describing Conformational Changes of a Multi-Domain Protein" J. Phys. Chem. Lett. (2016)

  • calcpathcv.m - calculates path collective variable (CV)
  • assigntransitionpath.m - detects transition paths from trajectory data

"Energetics and conformational pathways of functional rotation in the multidrug transporter AcrB" eLife (2018)

  • mbar.m - multistate Bennett acceptance ratio method
  • calcpathcv.m - calculates path collective variable (CV)
  • superimpose2d.m - superimposes structures by using only translation in XY-space and rotation around Z-axis
  • calcmutinf.m - estimates mutual information
  • calcgse.m - calculates electrostatic potential from trajectories by using k-space Gaussian split Ewald

(NEW) "Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning" submitted

  • msmbaumwelchdb.m msmforward.m msmbackward.m msmtransitionmatrix.m - Baum-Welch algorithm with a constraint imposed by the detailed-balance condition
  • msmbaumwelchdb_parallel.m msmforward_parallel.m msmbackward_parallel.m - Parallelized version of the above (requires Parallel Computing Toolbox)
  • msmgenerate.m - Stochastic simulation according to the constructed Markov State Model (MSM)
  • calcqscore.m - calculates Q-score for atomistic model
  • calcorientationfactor.m - calculates Orientation factor for FRET dyes
  • example/msmbaumwelchdb - test data set for msmbaumwelchdb.m and msmbaumwelchdb_parallel.m explaining the usage of these functions

(NEW) "Refining Markov State Models for conformational dynamics using ensemble-averaged data and time-series trajectories" submitted

  • msmbaumwelchdb.m msmforward.m msmbackward.m msmtransitionmatrix.m - Baum-Welch algorithm with a constraint imposed by the detailed-balance condition
  • msmcountmatrix.m - calculates count matrix from indexed trajectory data
  • msmtransitionmatrix.m - reverse Maximum-likelihood estimator for transition matrix from counting matrix
  • msmensemble.m - estimates populations from distribution data
  • calcdistancevector.m - calculate distance-matrix-based vectors from trajectory data
  • calctica.m - time-structure based ICA (tICA)
  • example/msmbaumwelchdb - test data set for msmbaumwelchdb.m and msmbaumwelchdb_parallel.m explaining the usage of these functions

Developer

Yasuhiro Matsunaga ymatsunaga@mail.saitama-u.ac.jp