The aim of this study was to investigate the feasibility of detecting promoter hypermethylation as a diagnostic tool with using liquid-based cytology samples for differentiating between malignant and benign effusions. Methods : A multiplex, nested,
methylation-specific polymerase chain reaction analysis was used to examine promoter methylation of 4 genes (retinoic acid receptor-beta, [RAR-beta], adenomatous polyposis coli [APC], Twist and high in normal-1 [HIN-1]) in malignant (n = 85) and benign (n = 31) liquid-based cytology samples. Results : The frequencies of hypermethylation of RAR-beta, APC, Twist and HIN-1 were significantly higher in the malignant effusions than in the benign effusions (p < 0.001 for each). On the receiver-operating characteristic analysis, the area under the curve (AUC) for APC was the greatest. The AUC for the best two-gene combination NU7441 chemical structure (APC/HIN-1) was not statistically different from the AUC for the best individual tumor suppressor gene (APC). Conclusions : This study suggests
that promoter methylation analysis on residual liquid-based effusion samples may be a feasible approach to detect malignant effusions, and that APC is the best marker for differentiating between malignant and benign effusions.”
“Fragment-based drug discovery using NMR and x-ray crystallographic methods has proven utility Salubrinal nmr but also non-trivial time, materials, and labor costs. Current computational fragment-based approaches circumvent these issues but suffer from limited representations of protein flexibility and solvation
effects, leading to difficulties with rigorous ranking of fragment affinities. To overcome these limitations we describe an explicit solvent all-atom molecular dynamics methodology (SILCS: Site Identification by Ligand Competitive Saturation) that uses small aliphatic and aromatic molecules plus water molecules to map the affinity pattern of a protein for hydrophobic groups, aromatic groups, hydrogen bond donors, and hydrogen GSK2879552 purchase bond acceptors. By simultaneously incorporating ligands representative of all these functionalities, the method is an in silico free energy-based competition assay that generates three-dimensional probability maps of fragment binding (FragMaps) indicating favorable fragment: protein interactions. Applied to the two-fold symmetric oncoprotein BCL-6, the SILCS method yields two-fold symmetric FragMaps that recapitulate the crystallographic binding modes of the SMRT and BCOR peptides. These FragMaps account both for important sequence and structure differences in the C-terminal halves of the two peptides and also the high mobility of the BCL-6 His116 sidechain in the peptide-binding groove. Such SILCS FragMaps can be used to qualitatively inform the design of small-molecule inhibitors or as scoring grids for high-throughput in silico docking that incorporate both an atomic-level description of solvation and protein flexibility.