JProNet: Systematic Network Analysis of Topological Properties of Protein 3D Structures

JProNet is a Java-based network tool for systematic analysis of structure-based topological properties of proteins. It incorporates new developments in network theory such as the scale-free and the small-world properties. JProNet can generate rich information of the residue packing topology of protein structure networks. JProNet is a platform independent, interactive and user-friendly tool. Users are empowered with the flexibility to input their customized protein structure-based network and define the weight of the edges in the network prior to the analysis.

[1]  Jun Gao,et al.  Conserved network properties of helical membrane protein structures and its implication for improving membrane protein homology modeling at the twilight zone , 2009, J. Comput. Aided Mol. Des..

[2]  L. Lally.  The CCP 4 Suite — Computer programs for protein crystallography , 1998 .

[3]  Zhijun Li,et al.  Uncover the conserved property underlying sequence-distant and structure-similar proteins. , 2009, Biopolymers.

[4]  M Karplus,et al.  Small-world view of the amino acids that play a key role in protein folding. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Zhijun Li,et al.  Inter-residue interactions in protein structures exhibit power-law behavior. , 2008, Biopolymers.

[6]  Zhijun Li,et al.  Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins. , 2009, Biopolymers.

[7]  Victoria A. Higman,et al.  Uncovering network systems within protein structures. , 2003, Journal of molecular biology.

[8]  Gil Amitai,et al.  Network analysis of protein structures identifies functional residues. , 2004, Journal of molecular biology.

[9]  Jaime Prilusky,et al.  Automated analysis of interatomic contacts in proteins , 1999, Bioinform..

[10]  Usha K Muppirala,et al.  A simple approach for protein structure discrimination based on the network pattern of conserved hydrophobic residues. , 2006, Protein engineering, design & selection : PEDS.

[11]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[12]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[13]  Peter J. Meek,et al.  Application of Network Theory in Understanding and Predicting Protein Structure and Function , 2008 .