Title : 
Designing hypothesis of some 2,4 -disubstituted-phenoxy acetic acid derivatives as a Crth2 receptor antagonist: A QSAR approach
         
        
            Author : 
Jain, Abhishek ; Agrawal, R.K.
         
        
            Author_Institution : 
Dept. of Pharm. Sci., Dr. Hari Singh Gour Univ., Sagar, India
         
        
        
        
        
        
            Abstract : 
In pursuit of better CRTh2 receptor antagonist agents, 2D-QSAR, 3D- QSAR studies were performed on a series of 2,4-disubstituted-phenoxy acetic acid derivatives. The best QSAR model was selected, having correlation coefficient R = 0.904, standard error of estimation SEE = 0.456 and cross validated squared correlation coefficient Q2 = 0.739. The predictive ability of the selected model was also confirmed by leave one out cross validation and by leave 33% out Q2 = 688. The QSAR model indicates that the descriptors (logP, SI3, LM, and DVZ). play an important role for the CRTh2 receptor antagonist activities. The kNN-MFA approach was used to generate models by all three different methods and predict the activity of test molecules through each of these models. The Q2, pred_r2, Vn and k value of kNN-MFA with SW, SA & GA were (0.8392, 0.7059, 2/2 ) (0.6725, 0.6716, 2/4 ) and (0.6832, 0.6716, 2/4 ) SW kNN-MFA method have better q2 (0.8392) and pred_r2 (0.7059) than other two methods, model validation correctly predicts activity 83.9% and 70.5% for the training and test set respectively. It uses 2 steric descriptors with 2 k nearest neighbor to evaluate activity of new molecule.
         
        
            Keywords : 
QSAR; biochemistry; biology computing; cellular biophysics; genetic algorithms; molecular biophysics; simulated annealing; 2,4-disubstituted-phenoxy acetic acid derivatives; 2D-QSAR; 3D-QSAR; Crth2 receptor antagonist; QSAR approach; T-helper-type-2 cells; genetic algorithm; kNN-MFA approach; molecule activity; nearest neighbor; simulated annealing; stepwise forward variable selection methods; steric descriptors; Algorithm design and analysis; Biological system modeling; Chemistry; Equations; Laboratories; Pharmaceuticals; Predictive models; Proteins; Software performance; Testing;
         
        
        
        
            Conference_Titel : 
Biomedical and Pharmaceutical Engineering, 2009. ICBPE '09. International Conference on
         
        
            Conference_Location : 
Singapore
         
        
            Print_ISBN : 
978-1-4244-4763-3
         
        
            Electronic_ISBN : 
978-1-4244-4764-0
         
        
        
            DOI : 
10.1109/ICBPE.2009.5384069