Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations.

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs.

Human Interactomics: Comparative Analysis of Different Protein Interaction Resources and Construction of a Cancer Protein-Drug Bipartite Network.

Unraveling the protein interaction wiring that occurs in human cells as a scaffold of biological processes requires the identification of all elements that constitute such molecular interaction networks. Proteome-wide experimental studies and bioinformatic comprehensive efforts have provided reliable and updated compendiums of the human protein interactome. In this work, we present a current view of available databases of human protein-protein interactions (PPIs) that allow building protein interaction networks. We also investigate human proteins as targets of specific drugs to analyze how chemicals interact with different target proteins, placing also the study in a network relational space. Hence, we undertake a description of several major drug-target resources to provide a present perspective of the associations between human proteins and specific chemicals. The identification of molecular targets for specific drugs is a critical step to improve disease therapy. As different diseases have different biomolecular scenarios, we addressed the identification of drug-targeted genes focusing our investigations on cancer and cancer genes. So, a description of resources that provide curated compendiums of human cancer genes is presented. Cancer is a complex disease where multiple genetic changes rewire cellular networks during carcinogenesis. This indicates that cancer drug therapy needs the implementation of network-driven studies to reveal multiplex interactions between cancer genes and drugs. To make progress in this direction, in the last part of this work we provide a bipartite network of cancer genes and their drugs shown in a graph landscape that disclose the existence of specific drug-target modules.

NMR solution structure of the angiostatic peptide anginex.

Anginex, a designed peptide 33mer, is known to function both as an antiangiogenic and bactericidal agent. Solving the NMR solution structure of the peptide is key to understand better its structure-activity relationships and to design more bioactive peptides and peptide mimetics. However, structure elucidation of anginex has been elusive due to subunit exchange-induced resonance broadening. Here, we found that performing NMR structural studies in a micellar environment abolishes exchange broadening and allows the structure of anginex to be determined. Anginex folds in an amphipathic, three-stranded antiparallel beta-sheet conformation with functionally key hydrophobic residues lying on one face of the beta-sheet and positively charged, mostly lysine residues, lying on the opposite face. Structural comparison is made with a homologous, yet relatively inactive peptide, betapep-28. These results contribute to the design of peptidomimetics of anginex for therapeutic use against angiogenically-related diseases like cancer, as well as infectious diseases.

Beta-sheet is the bioactive conformation of the anti-angiogenic anginex peptide.

Anginex is a designed peptide 33mer that functions as a cytokine-like agent to inhibit angiogenesis. Although this short linear peptide has been shown by NMR and CD to form a nascent beta-sheet conformation in solution, the actual bioactive structure formed upon binding to its receptor on the surface of endothelial cells could be quite different. By using a series of double-cysteine disulphide-bridged analogues, we provide evidence in the present study that the beta-sheet is in fact the bioactive conformation of anginex. CD and NMR spectral analysis of the analogues indicate formation of a beta-sheet conformation. Three functional assays, endothelial cell proliferation, apoptosis and in vitro angiogenesis, were performed on all analogues. As long as the placement of disulphide bonds preserved the beta-strand alignment, as in the proposed bioactive conformation, bioactivities were preserved. Knowledge of the bioactive conformation of anginex will aid in the design of smaller molecule mimetics of this potent anti-angiogenic peptide.