Follow-up workshop: BespokeFit
Abstract
An example session on using BespokeFit and incorporating it into your workflows.
We'll have a worked example presentation taking a ligand through optimization and simulation for the first 1-2 hours, and then OpenFF developers will be available to support your own exploration for the full 3-hour duration. Consider bringing a protein-ligand system of your own to run through the workflow! While we will end the recording during the Q+A and developer support period, there is no guarantee of privacy, so make sure that any structures you show aren’t proprietary.
Occurrence(s)
Oct 19 2022, at 9 AM Berlin / 8 AM London / 3 AM New York / 12 AM Los Angeles / 3 PM Shanghai / 6 PM Canberra
Duration is 3 hours, with prepared material in the first 1-2 hours and dev support for remainder
(old link deleted)
Oct 25 2022, at 12 AM (+1 day) Berlin / 11 PM London / 6 PM New York / 3 PM Los Angeles / 6 AM (+1 day) Shanghai / 9 AM (+1 day) Canberra
Duration is 3 hours, with prepared material in the first 1-2 hours and dev support for remainder
Zoom Link
Join our Cloud HD Video Meeting
Attendee preparation/install instructions
These instructions assume you have Conda installed already.
Download the materials from the gist below, either from the “Download ZIP” button or through
git clone https://gist.github.com/2860cf864ed1658ceec466bfb599e3fe.git
Extract the ZIP file, if used, and change directory into the appropriate directory
Create a temporary Conda environment in the working directory:
conda env create --prefix ./env-bespoke --file environment.yml
. If you have access to an OpenEye license, you may want to uncomment the relevant lines in both environment files to speed up some calculations.Activate the new environment:
conda activate ./env-bespoke
Create the secondary environment:
mamba env create --prefix ./env-toolkit --file env-toolkit.yml
Run the notebook from the temporary environment:
jupyter lab bespokefit.ipynb
Alternatively, the notebook can be followed and executed online on Binder: Gist: Yoshanuikabundi/2860cf864ed1658ceec466bfb599e3fe/HEAD
Materials
Notebooks, environments and materials: https://gist.github.com/Yoshanuikabundi/2860cf864ed1658ceec466bfb599e3fe