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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

Project details


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aesop-1.0.13.tar.gz (70.3 kB view hashes)

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