SubscoresScatterPlot on ChemCompute

The goal of this lesson is to have students use a Jupyter notebook and Chemcompute. This can serve as a first point of use for these resources and requires no adjustment to nor generation of code. They will use their existing data (from Virtual Screening 1 lab with docking scores and compound names) If no existing data, a sample data set (bestranking.lst) is provided in the repository. Students using this lesson are first and second year undergraduates in a CURE (course based undergraduate research experience).

Time Required: about 20-30 minutes if connecting to Chemcompute works smoothly.

Lesson Contents

• SubscoresScatterPlot

  • Directory: `virtual-screening-analysis'

  • Files:

    • SubscoresScatterPlot Jupyter notebook
    • bestranking.lst - sample data file to use

  • Description: Generate scatter plots and best fit lines from docking data

  • Time: 20-30 minutes

Getting started in ChemCompute instructions

OPTION A: 

1. Open Chemcompute : https://chemcompute.org/

2. Login >> Accept & Confirm >> Login using your Institutional Email >> search for your school's name e.g. 'The University of Texas at Austin > enter your id

3. Right click to Open this link in a new window

• If you get an error, log out of Chemcompute/close it and re-open it, then click on the link above again.

4. In Chemcompute, on top line, click on Jupyter >> Use Jupyter notebook >> CPU Node >> Jupyter notebook (vs. jupyter lab) >> Python >> Select a premade image (just use the default one, latest usually) >> Start

5. Go to the virtual-screening-analysis folder (if this is missing, revisit step 2 or go to Option B)

6. Open SubscoresScatterPlot_ChemCompute_.ipynb

OPTION B: 

1. Download the .ipynb file from this Git Hub 

2. In Chemcompute, on top line, click on Jupyter >> Use Jupyter notebook >> CPU Node >> Jupyter notebook (vs. jupyter lab) >> Python >> Select a premade image (just use the default one, latest usually) >> Start

3. At the right, click 'New' to create a new folder and name it (e.g. virtualanalysis), if you'd like (optional), then click into that folder

4. At the right, click Upload >> then find the .ipynb file that you can got from Git Hub

5. In Chemcompute, then click on the name of the .ipynb that you just uploaded