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ROBUST-2025

Predicting resistance and loss of inhibitor potency using linear regression models from physical features derived from Molecular Dynamics (MD) simulations.

Requirements

  • python ≥ 3.6
  • os, re, sys, glob, time
  • json
  • numpy
  • pandas
  • matplotlib
  • scipy
  • scikitlearn
  • amber22
  • ambertools22
  • cpptraj
  • pytraj

MD trajectory format

MD simulations in this study were run with the AMBER22 software and AMBER forecfields. The production step was converted from .mcdrc files to .dcd files using cpptraj. It may be possible to apply the feature calculation scripts could to MD trajectories generated on other MD engines if they are converted to the .dcd file and if parameter/topology files are regenerated with amber formatting.

Contact

Lauren Intravaia:

lauren.intravaia@umassmed.edu

Celia Schiffer:

celia.schiffer@umassmed.edu

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Predicting resistance and loss of inhibitor potency using linear regression models from physical features derived fromMD simulations.

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