Analyze Protein-Ligand MD [MDAnalysis]

Category Paths

  • Product-based/Molecular Dynamics

  • Role-based/Computational Chemist

  • Role-based/Medicinal Chemist

  • Task-based/Molecular Dynamics

  • Task-based/Affinity Prediction

  • Solution-based/Hit to Lead/Affinity Prediction/STMD

  • Solution-based/Small Molecule Lead-opt/Affinity


  • Purpose:

    • This Floe analyzes protein-ligand MD trajectories for pose stability.

  • Method Recommendations/Requirements:

    • The input dataset to this Floe must be the output dataset from one of the other Floes that run protein-ligand MD:

      • The “Bound Protein-Ligand MD” Floe

      • The “Short Trajectory MD with Analysis” Floe (in this case, this Floe will simply repeat the same analysis).

      • The bound complex dataset from the “Ligand Bound and Unbound Equilibration for NES” Floe.

  • Limitations

    • To avoid excessively large output Floe reports, the Floe report is truncated at the top 100 ligands by ensemble MMPBSA score.

  • Expertise Level:

    • Regular

  • Compute Resource:

    • Minimal

  • Keywords:

    • MDAnalysis

  • Related Floes:

    • Short Trajectory MD with Analysis [MDPrep] [MD] [MDAnalysis]

Trajectories from different starting poses of the same ligand are combined and analysed collectively. One analysis is in terms of interactions between the ligand and the active site. Another looks at clustering the ligand positions in the protein active site after fitting the trajectory based on active site C_alphas. Ensemble MMPBSA and ensemble BintScore calculations are carried out on the trajectory and are localized to the ligand clusters. An HTML Floe report is generated for the top 100 ligands by ensemble MMPBSA score. Once the analysis is done, it generates a ready-to-be-downloaded tarball file in Amazon S3, which includes the analysis results in CSV files, the HTML Floe report, ligand trajectories, and molecular structure files of cluster medians and averages of the protein-ligand complex.

Promoted Parameters

Title in user interface (promoted name)

  • Failed Dataset (fail) type: dataset_out: Output dataset of failed calculations
    Default: failed_dataset
  • MD Input Dataset (in) type: data_source: MD Input Dataset
  • Output Dataset (out) type: dataset_out: Output dataset to write to
    Default: MD_Anlys