METHOD FOR PREDICTING AND MODELING ANTI-PSYCHOTIC ACTIVITY USING VIRTUAL SCREENING MODEL

摘要

The present invention relates to the development of a virtual screening model for predicting antipsychotic activity using quantitative structure activity relationship (QSAR), molecular docking, oral bioavailability, ADME and Toxicity studies. The present invention also relates to the development of QSAR model using forward stepwise method of multiple linear regression with leave-one-out validation approach. QSAR model showed activity-descriptors relationship correlating measure (r²) 0.87 (87%) and predictive accuracy of 81% (rCV²=0.81). The present invention specifically showed strong binding affinity of the untested (unknown) novel compounds against anti-psychotic targets viz., Dopamine D2 and Serotonin (5HT_2A) receptors through molecular docking approach. Theoretical results were in accord with the in vitro and in vivo experimental data. The present invention further showed compliance of Lipinski's rule of five for oral bioavailability and toxicity risk assessment for all the active Yohimbine derivatives. Therefore, use of developed virtual screening model will definitely facilitate the screening of more effective antipsychotic leads/drugs with improved antipsychotic activity and also reduced the drug discovery cost and duration.