Peripheral arterial disease and systematic detection of circulating tumor cells: rationale and design of the DETECTOR prospective cohort study.

Background: Smoking is a strong risk factor for cancer and atherosclerosis. Cancer mortality, especially from lung cancer, overtakes cardiovascular (CV) death rate in patients with peripheral arterial disease (PAD). Only a few patients with lung cancer after PAD management may benefit from surgical excision.

Evaluation of a hypertension-based patient education program in a stroke center.

Background The benefits of educational programs are recognized in chronic diseases. An education program was designed in our hospital, for hypertensive patients after an acute episode of stroke to prevent stroke recurrence. Objective Evaluate the effects of such program on patient knowledge and blood pressure management.

Discriminating Agonist from Antagonist Ligands of the Nuclear Receptors Using Different Chemoinformatics Approaches.

Nuclear receptors (NRs) constitute an important class of therapeutic targets. During the last 4 years, we tackled the pharmacological profile assessment of NR ligands for which we constructed the NRLiSt BDB. We evaluated and compared the performance of different virtual screening approaches: mean of molecular descriptor distribution values, molecular docking and 3D pharmacophore models.

Identification of an in vivo orally active dual-binding protein-protein interaction inhibitor targeting TNFα through combined in silico/in vitro/in vivo screening.

TNFα is a homotrimeric pro-inflammatory cytokine, whose direct targeting by protein biotherapies has been an undeniable success for the treatment of chronic inflammatory diseases. Despite many efforts, no orally active drug targeting TNFα has been identified so far. In the present work, we identified through combined in silico/in vitro/in vivo approaches a TNFα direct inhibitor, compound 1, displaying nanomolar and micromolar range bindings to TNFα.

NRLiSt BDB, the manually curated nuclear receptors ligands and structures benchmarking database.

Nuclear receptors (NRs) constitute an important class of drug targets. We created the most exhaustive NR-focused benchmarking database to date, the NRLiSt BDB (NRs ligands and structures benchmarking database). The 9905 compounds and 339 structures of the NRLiSt BDB are ready for structure-based and ligand-based virtual screening.

Multiple structures for virtual ligand screening: defining binding site properties-based criteria to optimize the selection of the query.

Structure based virtual ligand screening (SBVLS) methods are widely used in drug discovery programs. When several structures of the target are available, protocols based either on single structure docking or on ensemble docking can be used. The performance of the methods depends on the structure(s) used as a reference, whose choice requires retrospective enrichment studies on benchmarking databases which consume additional resources.