Chemical Information Bulletin

Periodic supplement for "the regular journals of the American Chemical Society," containing annotated bibliographies of chemical documentation literature as well as information about meetings, conferences, awards, scholarships, and other news from the American Chemical Society (ACS) Division of Chemical Literature

Computational Approaches To Anti-Toxin Therapies And Biomarker Identification

This work describes the fundamental study of two bacterial toxins with computational methods, the rational design of a potent inhibitor using molecular dynamics, as well as the development of two bioinformatic methods for mining genomic data. Clostridium difficile is an opportunistic bacillus which produces two large glucosylating toxins. These toxins, TcdA and TcdB cause severe intestinal damage. As Clostridium difficile harbors considerable antibiotic resistance, one treatment strategy is to prevent the tissue damage that the toxins cause. The catalytic glucosyltransferase domain of TcdA and TcdB was studied using molecular dynamics in the presence of both a protein-protein binding partner and several substrates. These experiments were combined with lead optimization techniques to create a potent irreversible inhibitor which protects 95% of cells in vitro. Dynamics studies on a TcdB cysteine protease domain were performed to an allosteric communication pathway. Comparative analysis of the static and dynamic properties of the TcdA and TcdB glucosyltransferase domains were carried out to determine the basis for the differential lethality of these toxins. Large scale biological data is readily available in the post-genomic era, but it can be difficult to effectively use that data. Two bioinformatics methods were developed to process whole-genome data. Software was developed to return all genes containing a motif in single genome. This provides a list of genes which may be within the same regulatory network or targeted by a specific DNA binding factor. A second bioinformatic method was created to link the data from genome-wide association studies (GWAS) to specific genes. GWAS studies are frequently subjected to statistical analysis, but mutations are rarely investigated structurally. HyDn-SNP-S allows a researcher to find mutations in a gene that correlate to a GWAS studied phenotype. Across human DNA polymerases, this resulted in strongly predictive haplotypes for breast and prostate cancer. Molecular dynamics applied to DNA Polymerase Lambda suggested a structural explanation for the decrease in polymerase fidelity with that mutant. When applied to Histone Deacetylases, mutations were found that alter substrate binding, and post-translational modification

Novel Chemotypes for Inhibition of Bacterial and Mammalian Carbohydrate-Binding Proteins

The carbohydrate-binding proteins (lectins) emerged as viable targets to combat viral as well as bacterial pathogens. Therefore, drugs targeting lectins are desired; however their identification and development is challenging and is currently primarily focused on carbohydrate−based inhibitors. Therefore, new strategies and sensitive methods are required. Fragment-based drug design (FBDD) has proven to be a promising strategy for approaching difficult targets such as lectins. To address the current limitations in design of drug-like inhibitors for lectins, non- and metal-dependent bacterial or mammalian lectins are used. First, bacterial lectins from the opportunistic human pathogens Pseudomonas aeruginosa (LecA (PA-IL) and LecB (PA-IIL)) and Burkholderia ambifaria (BambL) were employed as models to establish ligand- (F- glycan) and protein-observed 19F NMR (PrOF) methods for drug discovery. To demonstrate the utility of these methods for fragment-based drug discovery (FBDD), a druggable pocket in BambL was uncovered as a potential target site for allosteric inhibitors. Finally, these methods were employed as well as other biophysical (X-ray, SPR), computational and biochemical techniques to discover a novel class of drug-like molecules for targeting the carbohydrate-binding site of metal-dependent bacterial and mammalian lectins. Together, the 19F NMR-based methods and discovery of metal- binding pharmacophores (MBPs) as novel chemotypes will support the development of small molecule inhibitors for metal-dependent lectins and bacterial lectins as new therapeutic approaches against antibiotic-resistant pathogens

Anticancer Agents

This book is a printed edition of the Special Issue entitled “Anticancer Agents: Design, Synthesis and Evaluation” that was published in Molecules. Two review articles and thirty research papers are included in the Special Issue. Three second-generation androgen receptor antagonists that have been approved by the U.S. FDA for the treatment of prostate cancer have been reviewed. Identification of mimics of protein partners as protein-protein interaction inhibitors via virtual screening has been summarized and discussed. Anticancer agents targeting various protein targets, including IGF-1R, Src, protein kinase, aromatase, HDAC, PARP, Toll-Like receptor, c-Met, PI3Kdelta, topoisomerase II, p53, and indoleamine 2,3-dioxygenase, have been explored. The analogs of three well-known tubulin-interacting natural products, paclitaxel, zampanolide, and colchicine, have been designed, synthesized, and evaluated. Several anticancer agents representing diverse chemical scaffolds were assessed in different kinds of cancer cell models. The capability of some anticancer agents to overcome the resistance to currently available drugs was also studied. In addition to looking into the in vitro ability of the anticancer agents to inhibit cancer cell proliferation, apoptosis, and cell cycle, in vivo antitumor efficacy in animal models and DFT were also investigated in some papers