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Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans and the average 5-year survival rate is one of the lowest among aggressive cancers. Protein kinase C zeta (PKCZ) is highly expressed in head and neck tumors, and the inhibition of PKCZ reduces MAPK activation in five of seven head and neck tumors cell lines. Considering the world-wide HNSCC problems, there is an urgent need to develop new drugs to treat this disease, that present low toxicity, effective results and that are relatively inexpensive. Methods: A unified approach involving homology modeling, docking and molecular dynamics simulations studies on PKCZ are presented. The in silico study on this enzyme was undertaken using 10 compounds from latex of Euphorbia tirucalli L. (aveloz). Results: The binding free energies highlight that the main contribution in energetic terms for the compounds-PKCZ interactions is based on van der Waals. The per-residue decomposition free energy from the PKCZ revealed that the compounds binding were favorably stabilized by residues Glu300, Ileu383 and Asp394. Based on the docking, Xscore and molecular dynamics results, euphol, ß-sitosterol and taraxasterol were confirmed as the promising lead compounds. Conclusion: The present study should therefore play a guiding role in the experimental design and development of euphol, ß-sitosterol and taraxasterol as anticancer agents in head and neck tumors. They are potential lead compounds, better than other ligands based on the best values of docking and MM-PBSA energy.

Diphtheria is an acute and highly infectious disease, previously regarded as endemic in nature but vaccine-preventable, is caused by Corynebacterium diphtheriae (Cd). In this work, we used an in silico approach along the 13 complete genome sequences of C. diphtheriae followed by a computational assessment of structural information of the binding sites to characterize the “pocketome druggability.” To this end, we first computed the “modelome” (3D structures of a complete genome) of a randomly selected reference strain Cd NCTC13129; that had 13,763 open reading frames (ORFs) and resulted in 1,253 (∼9%) structure models. The amino acid sequences of these modeled structures were compared with the remaining 12 genomes and consequently, 438 conserved protein sequences were obtained. The RCSB-PDB database was consulted to check the template structures for these conserved proteins and as a result, 401 adequate 3D models were obtained. We subsequently predicted the protein pockets for the obtained set of models and kept only the conserved pockets that had highly druggable (HD) values (137 across all strains). Later, an off-target host homology analyses was performed considering the human proteome using NCBI database. Furthermore, the gene essentiality analysis was carried out that gave a final set of 10-conserved targets possessing highly druggable protein pockets. To check the target identification robustness of the pipeline used in this work, we crosschecked the final target list with another in-house target identification approach for C. diphtheriae thereby obtaining three common targets, these were; hisE-phosphoribosyl-ATP pyrophosphatase, glpX-fructose 1,6-bisphosphatase II, and rpsH-30S ribosomal protein S8. Our predicted results suggest that the in silico approach used could potentially aid in experimental polypharmacological target determination in C. diphtheriae and other pathogens, thereby, might complement the existing and new drug-discovery pipelines.

Background Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. Results Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. Conclusions The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0346-4) contains supplementary material, which is available to authorized users.

In this work, we describe a set of features of Corynebacterium auriscanis CIP 106629 and details of the draft genome sequence and annotation. The genome comprises a 2.5-Mbp-long single circular genome with 1,797 protein-coding genes, 5 rRNA, 50 tRNA, and 403 pseudogenes, with a G+C content of 58.50%.