NAPA @ Karchin lab

NAPA (Network Analysis of Protein Adaptation)

is a computational framework for the reconstruction and analysis of networks of mutations involved in the protein's evolution of new or improved functions, a.k.a. protein adaptation.

Mutation networks can be reconstructed from a protein's evolutionary history, either in the from a multiple sequence alignment or a Bayesian phylogenetic tree ensemble. Nodes are linked in the network when the corresponding mutations are found to co-occur in the alignment or along phylogenetic tree branches. For a phylogeny based network, the links can also be directed, based on observed ordering of pairs of mutations along the tree branches.

After network reconstruction graph-theoretical analysis can be performed to model properties of a protein's adaptive evolution:

  • Mutations likely driving adaptation - by ranking the corresponding nodes in the network by network centrality.
  • Important combinations of mutations from a protein's adaptive trajectories - by centrality rankings of connected paths in the network.
  • Sets of mutations acting synergisticly to improve protein function - by detecting densely connected communities in the network.

NAPA is free for non-commercial use. For more details please refer to our Software License. Commercial users should contact the Johns Hopkins Technology Transfer office.

Current stable release is napa-1.1, last updated on 01/17/2017.

Source Code Releases

You can view the current source code on github.

napa-1.1.tar.gz     01/17/2017    Initial release.

Documentation

Please consult the project wiki page for installation and usage details.

Example workflow

Examples of running NAPA are described on the quick start page.

Gallery

An alignment-based network of the CTX-M group 1 β-lactamases evolving under selection for increased resistance to the extended spectrum antibiotic ceftazidime:
A directed phylogeny-based network of TEM β-lactamases evolving under selection for resistance to cephalosporins:

Platform

Basic functionality of NAPA scripts developed in python should be available across all platforms.

Primary citation

If you use our software for a publication, please cite the following:

Beleva Guthrie V, Allen J, Camps M, and Karchin R (2011) Network models of TEM β-lactamase mutations coevolving under antibiotic selection show modular structure and anticipate evolutionary trajectories. PLoS Computational Biology. 7(9):e1002184

Software primary contact/developer

Violeta Beleva Guthrie:  vbeleva at jhu dot edu