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.


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

Example workflow

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


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:


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