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.


An alignment-based network of bacterial OXA-51 β-lactamases evolving under selection for increased resistance to oxacillin β-lactam antibiotics:

A directed phylogeny-based network of OXA-51 β-lactamases:

Source Code

You can view the current source code on github.

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


Basic functionality of NAPA scripts developed in Python 2.7 should be available across all platforms.


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

Example workflow

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

Primary Citations

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

Beleva Guthrie V, Masica DL, Fraser A, Federico J, Fan Y, Camps M, and Karchin R (2018). Network Analysis of Protein Adaptation: modeling the functional impact of multiple mutations. Mol. Biol. Evo

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