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Module for analyzing electrostatics with protein structures

Project Description

AESOP

(A)nalysis of (E)lectrostatic (S)tructures (o)f (P)roteins

Authors: Reed Harrison, Rohith Mohan, and Dimitrios Morikis

Framework

  • AESOP is a computational framework to explore electrostatic structures within proteins. The library depends on external tools including: APBS, PDB2PQR, Modeller, and ProDy
  • Atomic Selections
  • Examples
    • All materials for example cases are provided in the tests folder
  • Documentation
    • HTML documentation provided within the docs folder
  • Dependencies
    • APBS and PDB2PQR
    • Required Python libraries: numpy, scipy, prody, matplotlib, modeller, griddataformats
    • Optional Python libraries: multiprocessing

Methods

  • Alascan
    • Perform a computational alanine scan on a provided protein structure using a side-chain truncation scheme
    • Association free energies for mutatants (relative to the parent) may be predicted if 2 or more selection strings are provided
    • Users may restrict mutations to some region of the protein structure
  • DirectedMutagenesis
    • Perform a directed mutagenesis scan on a provided protein structure using Modeller to swap amino acids
    • Association free energies for mutatants (relative to the parent) may be predicted if 2 or more selection strings are provided
    • Mutations must be specified
  • ElecSimilarity
    • Compare electrostatic potentials of multiple protein structures
    • If structures are very dissimilar, the user should superpose coordinates for each protein structure according to their desired method

General Utilities

  • aesop.plotScan()
    • Show bargraph summary of results from computational mutagenesis methods (Alascan, DirectedMutagenesis)
  • aesop.plotESD()
    • Show heatmap summary of results from methods exploring electrostatic similarity (ElecSimilarity)
  • aesop.plotDend()
    • Show dendrogram summary of results from methods exploring electrostatic similarity (ElecSimilarity)

Notes

  • We recommend using Anaconda to aid in installation of Python scientific libraries
  • Depending on your platform, ProDy may need to be installed with an executable
Release History

Release History

This version
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1.1.0

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