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.
Gallery
- An alignment-based network of bacterial OXA-51 β-lactamases evolving under selection for increased resistance to oxacillin β-lactam antibiotics:
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- A directed phylogeny-based network of OXA-51 β-lactamases:
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Source Code
Platform
- Basic functionality of NAPA scripts developed in Python 2.7 should be available across all platforms.
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.
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 https://doi.org/10.1093/molbev/msy036
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
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Violeta Beleva Guthrie: vbeleva at jhu dot edu
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.