Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study.

Activity cliffs (ACs) are defined as closely analogous compounds of significant affinity discrepancies against certain biotarget. In this paper we propose to use AC pair(s) for extracting valid binding pharmacophores through exposing corresponding protein complexes to stochastic deformation/relaxation followed by applying genetic algorithm/machine learning (GA-ML) for selecting optimal pharmacophore(s) that best classify a long list of inhibitors. We compared the performances of ligand-based and structure-based pharmacophores with counterparts generated by this newly introduced technique.

Knowledge, awareness and practices towards seasonal influenza and its vaccine: implications for future vaccination campaigns in Jordan.

Background: Influenza is an underestimated contributor to morbidity and mortality. Population knowledge regarding influenza and its vaccination has a key role in enhancing vaccination coverage.

Objectives: This study aimed to identify the gaps of knowledge among Jordanian population towards influenza and its vaccine, and to identify the major determinants of accepting seasonal influenza vaccine in adults and children in Jordan.