This repository will be used to benchmark and improve KinoML and Perses.
- reproduce ABL:inhibitor structures from Hauser 2018 using the KinoML pipeline
- run mutation benchmark from Aldeghi 2019 using OpenFF 1.2.0
- absolute free energy calculations with Yank might be interesting too
- long simulations to analyze stability of a variety of ABL:inhibitor complexes
- dock ATP/Mg2+ in binding pocket and analyze the effect of point mutations
- scale up to KINOMEScan data
- Clone repository
git clone https://github.com/openkinome/abl_resistance
- Create Conda environment
conda env create -f environment.yml
conda activate abl_resistance
notebooks/atp_kinase_conformations.ipynb
- jupyter notebook analyzing the conformations of ATP bound kinases
notebooks/abl1_atp_modeling.ipynb
- jupyter notebook generating an ABL1 ATP complex
notebooks/abl_complex_modeling.ipynb
- jupyter notebook generating inhibitor bound complexes for the Hauser 2018 benchmark
notebooks/abl_complex_modeling_with_water.ipynb
- jupyter notebook using updated KinoML functionalities to generate inhibitor bound complexes for the Hauser 2018 benchmark including water
- David Schaller [email protected]
- William Glass [email protected]
This repository is licensed under the MIT license.