Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/57586
Title: 3D QSAR analysis on quinoxaline derivatives as anti-malarial using K-nearest neighbour molecular field analysis
Authors: Mishra, Achal
Vaishnav, Yogesh
Jha, Arvind Kumar
Verma, Shekhar
Keywords: 3D-QSAR;kNN-MFA;Antimalarial;Quinoxaline derivatives;Sphere exclusion (SE) algorithm
Issue Date: May-2021
Publisher: NISCAIR-CSIR, India
Abstract: In the present article, k nearest neighbour molecular field analysis (kNN-MFA) method was used to develop a three dimensional quantitative structure activity relationship (3D-QSAR) model. In this study 37 derivatives of quinoxaline having antimalarial activity were used. Sphere exclusion (SE) algorithm was used to create the biological activity data set in to into training and test set. For model generation kNN-MFA method has coupled with stepwise, simulated annealing and genetic algorithm this method provides various models, in which the most significant model developed by stepwise backward-forward method with predictive internal q2=0.7589 and external predictivity (pred_r2 = 0.4752). In the presented model electrostatic descriptors play crucial role for activity. Electrostatic descriptor (E_137) indicates regions in which electron withdrawing groups are favourable and descriptor (E_939) represents electron rich or electron donating groups are advantageous in particular region. The counter map/ plot of this model further helps to understand the relationship of structural feature of derivative of quinoxaline and its biological activity this would be applied for designing of new potent antimalarial containing quinoxaline as lead.
Page(s): 727-731
URI: http://nopr.niscair.res.in/handle/123456789/57586
ISSN: 0975-0983(Online); 0376-4699(Print)
Appears in Collections:IJC-B Vol.60B(05) [May 2021]

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