Structure-activity relationships for mosquito repellent aminoamides using the hierarchical QSAR method based on calculated molecular descriptors

Subhash C Basak, Natarajan Ramanathan, Denise Mills

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In the quest to find alternatives for the most popular topical repellant, N,N Diethyl-3-methylbenzamide (DEET), development of QSAR models plays a very important role because these models can be used to tailor the similarity space and select compounds from large data sets in the identification of leads. Mosquito repellency data of carboxamides for Aedes aegypti and Anopheles quadrimaculatus are modeled by the Hierarchical Quantitative Structure- Activity Relationship (HiQSAR) technique using topostructural, topochemical, geometrical and quantum mechanical parameters. Three types of multiple regression methods namely, ridge regression, principle components regression, and partial least square regression models were applied. For Aedes aegypti data, in all three regression methods the topostructural parameters are found to correlate well with the time of protection, and there was no improvement in the model quality on adding topochemical, geometrical and quantum chemical parameters. This indicates that the size of the repellent is the primary factor that governs the repellency of the carboxamides. However, in the case of the Anopheles quadrimaculatus the chemical nature, presence of a double bond, also seems to have a role. HiQSAR is able to bring out a possible difference in the mode or mechanism of action of the repellent amides for the two mosquito species.

Original languageEnglish (US)
Pages (from-to)958-963
Number of pages6
JournalWSEAS Transactions on Information Science and Applications
Volume2
Issue number7
StatePublished - Jul 1 2005

Keywords

  • Amides
  • DEET
  • Molecular descriptors
  • Mosquito repellency
  • QSAR

Fingerprint Dive into the research topics of 'Structure-activity relationships for mosquito repellent aminoamides using the hierarchical QSAR method based on calculated molecular descriptors'. Together they form a unique fingerprint.

Cite this