Authors: Aarti Garg, Rupinder Tewari & Gajendra Raghava
A web server, KiDoQ, has been developed to serve scientific community working in the field of designing inhibitors against Dihydrodipicolinate synthase (DHDPS), a potential drug target enzyme of a unique bacterial DAP/Lysine pathway. The server has employed the molecular docking and ligand based QSAR strategies to predict inhibitory activity value (Ki) of small compounds for DHDPS enzyme. The algorithm behind the server includes the docking of compounds to the active binding site of enzyme followed by QSAR modeling where, docking generated energy based scoring values (for the best conformer) are cascaded as input variables to QSAR based SVM model for prediction of Ki value. The QSAR model implemented on the server has been trained on the dataset of 23 inhbitors of DHDPS and predict the Ki value with correlation R/q2 values of 0.93/0.80 and MAE of 1.89.
The server is available from http://crdd.osdd.net/raghava/kidoq.
The following steps are used to do prediction of Ki value for a submitted structure
KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials. Aarti Garg, Rupinder Tewari, and Gajendra PS Raghava. BMC Bioinformatics 11 (1) doi:10.1186/1471-2105-11-125
Aarti Garg, Institute of Microbial Technology, Sector-39A, Chandigarh, INDIA
Rupinder Tewari, Department of Biotechnology, Panjab University, Chandigarh, INDIA
Gajendra Raghava, Raghava's Group
Correspondence to: Gajendra Raghava ([email protected])
Source: Protocol Exchange (2010) doi:10.1038/protex.2010.206. Originally published online 10 December 2010.