Animal Models of Barrett's Esophagus and Esophageal Adenocarcinoma–Past,Present, and Future

Esophageal adenocarcinoma is the fastest rising cancer in the United States. It develops from long‐standing gastroesophageal reflux disease which affects >20% of the general population. It carries a very poor prognosis with 5‐year survival <20%. The disease is known to sequentially progress from reflux esophagitis to a metaplastic precursor, Barrett''s esophagus and then onto dysplasia and esophageal adenocarcinoma. However, only few patients with reflux develop Barrett''s esophagus and only a minority of these turn malignant. The reason for this heterogeneity in clinical progression is unknown. To improve patient management, molecular changes which facilitate disease progression must be identified. Animal models can provide a comprehensive functional and anatomic platform for such a study. Rats and mice have been the most widely studied but disease homology with humans has been questioned. No animal model naturally simulates the inflammation to adenocarcinoma progression as in humans, with all models requiring surgical bypass or destruction of existing antireflux mechanisms. Valuable properties of individual models could be utilized to holistically evaluate disease progression. In this review paper, we critically examined the current animal models of Barrett''s esophagus, their differences and homologies with human disease and how they have shaped our current understanding of Barrett''s carcinogenesis.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.