AMMOS software: method and application.

Recent advances in computational sciences enabled extensive use of in silico methods in projects at the interface between chemistry and biology. Among them virtual ligand screening, a modern set of approaches, facilitates hit identification and lead optimization in drug discovery programs. Most of these approaches require the preparation of the libraries containing small organic molecules to be screened or a refinement of the virtual screening results. Here we present an overview of the open source AMMOS software, which is a platform performing an automatic procedure that allows for a structural generation and optimization of drug-like molecules in compound collections, as well as a structural refinement of protein-ligand complexes to assist in silico screening exercises.

Identification of human cancer-related genes by naturally occurring Hepatitis B Virus DNA tagging.

Proviral tagging has been used in animals as a powerful tool for cancer genetics. We show that a similar approach is possible in patients with hepatocellular carcinoma (HCC) infected by Hepatitis B Virus (HBV), a human pararetrovirus which may act by insertional mutagenesis. In this work, the HBV genome is used as a probe to identify cancer-related genes. By using HBV-Alu-PCR, we obtained 21 HBV/cellular DNA junctions from 18 different patients. In six of 21, we found the HBV DNA integrated into a cellular gene: (1) Sarco/Endoplasmic Reticulum Calcium ATPase1 Gene; (2) Thyroid Hormone Receptor Associated Protein 150 alpha Gene; (3) Human Telomerase Reverse Transcriptase Gene; (4) Minichromosome Maintenance Protein (MCM)-Related Gene; (5) FR7, a new gene expressed in human liver and cancer tissues; and (6) Nuclear Matrix Protein p84 Gene. Seven junctions contained unique cellular sequences. In the remaining eight, the HBV DNA was next to repetitive sequences, five of them of LINE1 type. The cellular genes targeted by HBV are key regulators of cell proliferation and viability. Our results show that studies on HBV-related HCCs allow to identify cellular genes involved in cancer. We therefore propose this approach as a valuable tool for functional cancer genomic studies in humans.