The target ligand association data is a rich source of information which is not exploited enough for drug design
efforts in virtual screening. A java based open-source toolkit for Protein Ligand Network Extraction (J-ProLiNE) focused
on protein-ligand complex analysis with several features integrated in a distributed computing network has been
developed. Sequence alignment and similarity search components have been automated to yield local, global alignment
scores along with similarity and distance scores. 10000 proteins with co-crystallized ligands from pdb and MOAD
databases were extracted and analyzed for revealing relationships between targets, ligands and scaffolds. Through this
analysis, we could generate a protein ligand network to identify the promiscuous and selective scaffolds for multiple
classes of proteins targets. Using J-ProLiNE we created a 507 x 507 matrix of protein targets and native ligands belonging
to six enzyme classes and analyzed the results to elucidate the protein-protein, protein-ligand and ligand-ligand
interactions. In yet another application of the J-ProLiNE software, we were able to process kinase related information
stored in US patents to construct disease-gene-ligand-scaffold networks. It is hoped that the studies presented here will
enable target ligand knowledge based virtual screening for inhibitor design.
Keywords: Complexes, protein, ligand, scaffolds, sequences, similarity score, virtual screening.
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