Skip to content

schlessinger-lab/af2_kinase_conformations

Repository files navigation

# Author: Noah Herrington, Ph.D.
# Email: [email protected]

# This README file explains how to use the useful scripts for AF2-based modeling of kinases
# in alternative conformations.

## This repository includes five scripts:

## 1) AlphaFold2_advanced_modified.py
## - Used to run AlphaFold2 predictions of a given kinase
## - Outputs 5 models
## - Initial stages of program running installs extra dependencies and required packages
## - "is_training" set to "True" to enable model dropout
## - Takes two arguments: 1. input fasta file and 2. desired output directory
## - Dependencies: biopython 1.79, jax 0.4.1, tensorflow 2.11.0
## - Usage: python3 AlphaFold2_advanced_modified.py input_fasta output_dir

## 2) colabfold_alphafold.py
## - Modified version of script from ColabFold repository
## - Allows for output directory argument
## - Dependencies installed by or before running AlphaFold2_advanced_modified.py
## - Replace default script with this one

## 3) AF2_kinase_families_stackedbarplot.py
## - Used to classify models downloaded from the AlphaFold2 Protein Structure Database
##   into their respective kinase families
## - Must be used in conjunction with kinfam.csv and output from
##   Kincore classifier (https://github.com/vivekmodi/Kincore-standalone) as a csv,
##   titled "kinases_classified.csv"
## - Dependencies: matplotlib 3.7.0, numpy 1.23.5, pandas 1.4.4, plotly 5.9.0
## - Usage: python3 AF2_kinase_families_stackedbarplot.py

## 4) Kincore_ConformationDistribution_Doughnutplot.py
## - Used to generate a doughnut-shaped plot of distribution of AF2-predicted models
##   by their conformation
## - Outputs fractions of each conformation to the screen and plotly doughnut plot in browser
## - Dependencies: matplotlib 3.7.0, numpy 1.23.5, pandas 1.4.4
## - Usage: python3 Kincore_ConformationDistribution_Doughnutplot.py

## 5) MSA_models_Mobitz_plot.py
## - Used to generate plot of models by pseudo-dihedral angles (proposed by Mobitz (2015)),
##   which group kinase models by movement of their DFG motif
## - Outputs a saved hi-res image of the plot
## - Allows for input of a chosen MSA depth and projection (3D/2D), where 2D represents the Mobitz
##   plot and 3D adds an additional dimension for RMSD with respect to a prototyical DFG-in structure
## - Necessitates having downloaded the PDB structure 1ATP and renamed it
##   "1ATP_cAMP-dep_prot_kinase_ATP_DFGin_Reference.pdb"
## - Usage: python3 MSA_models_Mobitz_plot.py

## 6) enrichment.py
## - Used to generate enrichment plot of a series of docked models
## - Allows input of colored curves by MSA Depth, pLDDT Score, or Conformation
## 	- If coloring by pLDDT Score is desired, requires presence of CSVs containing
##	  classification of all models at those depths (created with Kincore - Dunbrack Lab)
## - Requires two positional arguments:
##	a) Name of the kinase, for which plots are created
##	b) Quality by which curves are colored (i.e., msa, plddt, conf)
## - Usage: python3 enrichment.py {a} {b}

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages