3D QSAR studies of dioxins and dioxin-like compounds using CoMFA and CoMSIA

Ali Ashek, Cheolju Lee, Hyunsung Park, Seung Joo Cho

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


In the present study we have performed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) on structurally diverse ligands of Ah (dioxin) receptor to explore the physico-chemical requirements for binding. All CoMFA and CoMSIA models have given q2 value of more than 0.5 and r2 value of more than 0.84. The predictive ability of the models was validated by an external test set, which gave satisfactory predictive r2 values. Best predictions were obtained with CoMFA model of combined modified training set (q2 = 0.631, r2 = 0.900), giving predictive residual value = 0.02 log unit for the test compound. Addition of CoMSIA study has elucidated the role of hydrophobicity and hydrogen bonding along with the effect of steric and electrostatic properties revealed by CoMFA. We have suggested a model comprises of four structurally different compounds, which offers a good predictability for various ligands. Our QSAR model is consistent with all previously established QSAR models with less structurally diverse ligands.

Original languageEnglish
Pages (from-to)521-529
Number of pages9
Issue number3
StatePublished - Oct 2006


  • 3D-QSAR dioxin CoMFA CoMSIA


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