Evaluating performance on the Schrödinger JACS dataset

This notebook is an analysis of the errors in relative free energy calculations from the Schrödinger JACS dataset:

Wang, L., Wu, Y., Deng, Y., Kim, B., Pierce, L., Krilov, G., ... & Romero, D. L. (2015). Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. Journal of the American Chemical Society, 137(7), 2695-2703.

http://doi.org/10.1021/ja512751q

Manifest

• AMBER TI chemRxiv analysis - mapped edge DDGs.ipynb - analysis of mapped edge DDG statistics
• AMBER TI chemRxiv analysis - DG and allpairs DDG.ipynb - analysis of DG and all-pairs DDG statistics
• environment.yml - conda environment
• LICENSE - copy of the MIT License this work is licensed under
• jacs-analysis.pdf - figure produced by the analysis
• fep-plus - SI retrieved from Schrödinger publication
• amber-ti - AMBER TI results reported on chemRxiv

To use the notebook

Create a conda environment and activate it

conda env create -f environment.yml -n jacs
source activate jacs

Launch the notebook

jupyter notebook notebook.ipynb