CODESSA PRO software

Katritzky et al. (2008PNAS7359) successfully developed classification ANN QSAR for 200 compounds used as repellents against mosquitoes. Mosquito repellent activities from USDA archives of N-acylpiperidines were extracted and modeled using molecular descriptors calculated by CODESSA PRO software. The ANN model was used for the correlation of these archival repellent activities and used to predict the activities of novel compounds of similar structures. The outcome of this QSAR led to a selection of 34 promising mosquito N-acylpiperidine repellent candidates which were synthesized by reactions of acylbenzotriazoles with piperidines. These synthesized compounds were screened as topical mosquito repellents by... 

Researchers have used 3D quantitative structural activity relationship (QSAR) of deet and related analogs to construct pharmacophores to better understand the structural basis that leads to repellency by these amide compounds."- Their model was constructed primarily from the protection time data of Suryanarayana and others. Ma and others" showed that one could predict repellent duration based on compound structure and specifically that the amide group and attached substituents played a significant role in the experimentally determined repellent efficacy. Using the same data set, Katritzky and others applied Codessa Pro software to develop a QSAR model for the prediction of complete protection time (CPT) from descriptors related to the structural and electronic properties of deet analogs. This work is the foundation for current projects that involve the examination of repellency and toxicity data for subsets of compounds within the U.S. Department of Agriculture (USDA) archive. 

---