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Open-sourced. A cloud-based workflow to evaluate the confidence of a given docked pose with binding pose metadynamics

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quantaosun/Dock-MD-BPMD

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Dock-MD-BPMD

This is a three-step workflow based on the cloud to help you increase the confidence of a docked pose of a small molecule bound to a target protein. To achieve this, two aspects of the puzzle are needed,

  • The algorithm or software if you like, for this end, this repository relies on all open-sourced packages,
  • The hardware or platforms, for this, this workflow depends on the free Binder platform and the paid Google Colab GPU serice.

1. Docking with labodock_binder on Binder

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(free service, only CPU required)

Note, in most cases people would use a PDB id that has been registered in the PDB bank, but if you have an in-house receptor, use this variation. https://colab.research.google.com/github/quantaosun/labodock_binder/blob/main/labodock_native_interaction/wedock_mac_local_receptor_native_interaction.ipynb

2. Amber inputs generation on Binder

Binder

(free service, only CPU required)

3. Binding pose metadynamics with OpenBPMD on Colab

Open In Colab

(paid service, GPU required, V100 or above)

Credits/References//Platforms

  1. https://github.com/quantaosun/labodock_binder
  2. https://github.com/RyanZR/labodock
  3. https://github.com/pablo-arantes/making-it-rain
  4. Arantes P.R., Depólo Polêto M., Pedebos C., Ligabue-Braun R. Making it rain: cloud-based molecular simulations for everyone. Journal of Chemical Information and Modeling 2021. DOI: 10.1021/acs.jcim.1c00998.
  5. A. J. Clark, P. Tiwary, K. Borrelli, S. Feng, E. Miller, R. Abel, R. A. Friesner, B. J. Berne, J. Chem. Theory Comput. 2016, 12, 6, 2990–2998, DOI:https://doi.org/10.1021/acs.jctc.6b00201
  6. D. Lukauskis, M. L. Samways, S. Aureli, B. P. Cossins, R. D. Taylor, F. L. Gervasio, J. Chem. Inf. Model. 2022, 62, 23, 6209–6216, DOI:https://doi.org/10.1021/acs.jctc.6b00201
  7. https://mybinder.org/
  8. https://colab.research.google.com/

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Open-sourced. A cloud-based workflow to evaluate the confidence of a given docked pose with binding pose metadynamics

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