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@nathanmlim nathanmlim commented Jan 18, 2018

This PR adds in an analysis module I've been working on that automatically identify metastable ligand binding modes using tools from PyEMMA. Included is a juypter notebook that provides a brief walk through usage of the analysis modules, located in notebooks/example-id_bmodes.ipynb

The analysis modules can be accessed like blues.analysis import msm,cluster. Helper functions for these modules are located in tools.py

ConstructMSM provides convenience functions for using PyEMMA.
This class assists in selecting the appropriate lagtime
through plots, TICA-transforms the input feature coordinates for
k-means clustering to discretize the trajectories, and constructs the MSM
for the purpose of identifying the metastable binding modes.
FindBindingModes provides functions to analyze and determine the number of
metastable modes from the resulting MSM data out of ConstructMSM() via
spectral clustering from PCCA.
    BindingModeOccupancy provides functionality to calculate the occupancy
    of each defined binding mode, determined from FindBindingModes().

@nathanmlim nathanmlim changed the title [WIP] Add analysis tools for identifying ligand binding modes. Analysis tools for identifying ligand binding modes from MD or BLUES simulations. Jan 22, 2018
@nathanmlim nathanmlim changed the title Analysis tools for identifying ligand binding modes from MD or BLUES simulations. [WIP] Analysis tools for identifying ligand binding modes from MD or BLUES simulations. Mar 29, 2018
@nathanmlim
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This will need some changes with upcoming changes to our NCMC reporter.

@nathanmlim nathanmlim changed the title [WIP] Analysis tools for identifying ligand binding modes from MD or BLUES simulations. Analysis tools for identifying ligand binding modes from MD or BLUES simulations. Jul 31, 2018
@nathanmlim nathanmlim changed the title Analysis tools for identifying ligand binding modes from MD or BLUES simulations. [WIP] Analysis tools for identifying ligand binding modes from MD or BLUES simulations. May 6, 2019
@stevenayoub
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@davidlmobley

This PR looks quite useful—it adds a modular analysis toolkit (blues.analysis) for identifying metastable ligand binding modes using PyEMMA. It’s well-scoped and does not alter the core functionality of BLUES, making it a safe and valuable addition for post-simulation analysis.

For future development, it may be worth refactoring to support deeptime ( https://deeptime-ml.github.io/latest/index.html ) , given the deprecation of PyEMMA.

I did encounter some merge conflicts with the following files:
• Both added: .gitignore
• Both modified: .travis.yml
• Deleted by us: blues/version.py
• Both modified: setup.py

These are all straightforward and can be resolved by merging both sets of changes.

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3 participants