ChemTextMiner: An open source tool kit for mining medical literature abstracts

Text mining involves recognizing patterns from a wealth of information hidden latent in unstructured text and deducing explicit relationships among data entities by using data mining tools. Text mining of Biomedical literature is essential for building biological network connecting genes, proteins, drugs, therapeutic categories, side effects etc. related to diseases of interest. We present an approach for textmining biomedical literature mostly in terms of not so obvious hidden relationships and build biological network applied for the textmining of important human diseases like MTB, Malaria, Alzheimer and Diabetes. The methods, tools and data used for building biological networks using a distributed computing environment previously used for ChemXtreme[1] and ChemStar[2] applications are also described

Designing Novel Lead Molecules For Human Ribosomal Protein S6 Kinase Beta-1 Involved In Cancers: Ligand Based Virtual Screening Approach

Protein kinases are clinically relevant and attractive drug targets for most of the cancerous diseases. Ribosomal protein s6 kinase (P70s6 kinase) is a mitogen activated Ser/Thr protein kinase, essential for cell growth, G1 cell cycle progression and cell survival. Human P70s6 kinase is involved in different signaling pathways and phosphorylates the downstream S6 protein of the 40S ribosomal subunit there by controlling the translational activity. Over expression of human P70s6 or rapid amplification of gene (RPS6KB1) leads to rapid cell proliferation causing cancer in various organs of humans like colon, breast, ovary, etc. The over expression is principally due to activation of some phosphorylating sites or ATP binding sites in the domain regions. In the present study, we identified new leads that can show inhibitory activity against cancer causing human P70s6 kinase through ligand based virtual screening. Proteomic analysis of human P70s6 kinase was performed by using Prosite, Pfam, BLOCKS databases to know the functional aspects like patterns, domains, and motifs; simultaneously, phylogeny of the protein was analyzed to delineate its relationship with other protein kinases involved in cancer. The initial virtual screening was performed to search structural analogs for published inhibitors (Staurosporine; 4-(Benzimidazol-2-yl)-1, 2, 5-oxadiazol-3-ylamine derivative; 4-{4-[4-(3-Trifluoromethyl-phenyl)-1H-imidazol-2-yl]-1H-pyrazolo-[3, 4-d] pyrimidine hydrochloride) from Ligand.Info database. Consequently, an initial ligand dataset of 1171 compounds were compiled and prepared using LigPrep. Human P70s6 kinase crystal structure was explored using Glide to set grid around centroid of catalytic domain residues. Flexible Glide computational docking methods of Maestro9.0 were applied subsequently to put forward 9 lead molecules with strong binding affinity towards human P70s6 kinase catalytic domain. Binding affinity and orientation of the proposed 10 leads were better or par with the existing inhibitors and had no ADME violation or reactive functional group. The top ranked compounds (lead 1) had shown XP Gscore of -12.99 kcal/mol and three hydrogen bonds with human P70s6 kinase catalytic domain residues Gly100, Glu173 and Leu175. Comparative analysis of the published inhibitors and Lead 1 had revealed that the binding mode of the docking complexes corroborating well, at the same time, Lead 1 interaction was stronger with less XP Gscore, more number of hydrogen bonds and good Van der Waals contacts. In view of the analysis Lead 1 would be considered for designing potential inhibitor for cancer therapy