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dc.contributor.authorMishra, Achal-
dc.contributor.authorVaishnav, Yogesh-
dc.contributor.authorJha, Arvind Kumar-
dc.contributor.authorVerma, Shekhar-
dc.identifier.issn0975-0983(Online); 0376-4699(Print)-
dc.description.abstractIn 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.en_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJC-B Vol.60B(05) [May 2021]en_US
dc.subjectQuinoxaline derivativesen_US
dc.subjectSphere exclusion (SE) algorithmen_US
dc.title3D QSAR analysis on quinoxaline derivatives as anti-malarial using K-nearest neighbour molecular field analysisen_US
Appears in Collections:IJC-B Vol.60B(05) [May 2021]

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