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. Sphingosine kinase 1 (SPHK-1) was used as case study. SPHK-1 is a lipid kinase that plays pivotal role in the regulation of a variety of biological processes including, cell growth, apoptosis, and inflammation. The new approach proved to yield pharmacophore and ML models of comparable accuracies to established ligand-based and structure-based pharmacophores. The resulting pharmacophores and ML models were used to capture hits from the national cancer institute list of compounds and predict their bioactivity categories. Two hits of novel chemotypes showed selective and low micromolar inhibitory IC50 values against SPHK-1.

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. METHODS: This was a cross-sectional study that enrolled 941 randomly selected adults in Amman, Jordan. A four-section questionnaire was used which included questions about the sociodemographic characteristics, knowledge about influenza and the factors that affect seasonal influenza vaccine acceptance and refusal. RESULTS: Only 47.3% of the participants were considered knowledgeable. About half of the participants (51.9%) correctly identified the main influenza preventative measures. Lack of knowledge about the important role of seasonal influenza vaccine in disease prevention was observed. Low vaccination rate (20% of adults) was reported. The most critical barrier against vaccination in adults and children was the concern about the safety and the efficacy of the vaccine, while the most important predictors for future vaccination in adults and children were physician recommendation and government role. In children, the inclusion of the vaccine within the national immunization program was an important determinant of vaccine acceptance. CONCLUSION: Formulating new strategies to improve the population's level of knowledge, assuring the population about the safety and the efficacy of the vaccine and the inclusion of the vaccine within the national immunization program are the essential factors to enhance vaccination coverage in Jordan.