Karchin Lab, Institute of Computational Medicine, Johns Hopkins University.

Author: Violeta Beleva Guthrie

Contact: vbeleva at jhu dot edu

NAPA is a python package that performs network construction and analysis to investigate intra-protein residue coevolution. Network analysis is particularly useful in evaluating recent genetic evolution of novel functions resulting from multiple mutations that interact in a non-linear fashion. An example is the adaptation of β-lactamase to confer antibiotic resistance.

NAPA requires as input a multiple sequence alignment of related protein sequences undergoing adaptation. A phylogenetic tree or a tree ensemble based on the sequence alignment may also be provided as input. NAPA produces protein residue mutation networks (undirected for sequence alignment input; directed with phylogenetic tree input) and performs network analysis to assist with identification of sets of coevolving mutations that interact to improve protein function.

Install
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Sample Data
Input Files
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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. PubMed

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