Zanamivir and Oseltamivir are both sialic acid analog inhibitors of Neuraminidase (NA), which is an important target in influenza A virus treatment. Quantitative Structure-Activity Relationships (QSAR) is a common computational method for correlating the structural properties of compounds (or inhibitors) with their biological activities. The pharmcophore model easily and quickly recognises related inhibitors and also fits the binding site interaction features of a protein structure. The Comparative Molecular Similarity Index Analysis (CoMSIA) model easily optimises molecular structures and describes the limit range of molecule weights. This study proposes a combination approach that integrates these two models based on the same training set inhibitors in order to screen and optimize NA inhibitor candidates during drug design.
|Number of pages||16|
|Journal||International Journal of Data Mining and Bioinformatics|
|Publication status||Published - 2014|
All Science Journal Classification (ASJC) codes
- Information Systems
- Biochemistry, Genetics and Molecular Biology(all)
- Library and Information Sciences