Title

Authors

Affiliation

¹Bioinformatics Division, School of Biosciences and Technology, VIT University; ²Department of General Surgery, Stanley Medical College and Hospital, Chennai.

Email

mohanapriyaa@vit.ac.in; *Corresponding author

Article Type

Hypothesis

Date

Received March 01, 2012; Accepted April 16, 2012; Published April 30, 2012

Cyclo-oxygenase 2 (COX2) inhibiting drugs were subjected to comparative quantitative structure activity relationship (QSAR) analysis with an attempt to derive and to understand the relationship between the biological activity and molecular descriptors by multiple regression analysis. The different drugs that inhibit cyclo-oxygenase 2 enzyme were compared instead of subjecting one drug and its derivatives to QSAR analysis. The study was conducted to look for the common structural features between the drugs which confer to a good biological activity. Based on the regression analysis the following descriptors were finalized as the components fitting best in the regression equations: Ss, SCBO, RBN, nN, SIC0, IC1, and H-055. These descriptors belong to constitution (Ss, SCBO, RBN, nN), information indices (SIC0, IC1) and atom centered fragments (H-055) category. Based on these descriptors QSAR models were generated and evaluated for best structure-activity correlation. The model generated from constitution and information indices descriptors corresponds to the essential structural features of the drugs and are found to have significant correlation with COX2 inhibiting activity. This study shall help in rational drug design and synthesis of new selective cyclo-oxygenase 2 inhibitors with predetermined affinity and activity.

Keywords

COX2, QSAR, biological activity, descriptors.

Citation

Mohanapriya & Achuthan, Bioinformation 8(8): 353-358 (2012)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.