QSAR Study on 5-Lipoxygenase Activating Protein (FLAP) Inhibitors: The Derivatives of 2,2-Bisaryl-Bicycloheptane

Author(s): Brij Kishore Sharma, Pradeep Pilania, Prithvi Singh

Journal Name: Letters in Drug Design & Discovery

Volume 8 , Issue 1 , 2011

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The FLAP inhibitory activity of 2,2-bisaryl-bicycloheptane derivatives has been quantitatively analyzed in terms of Dragon descriptors. The derived QSAR models have provided rationales to explain the FLAP inhibitory activity of 2,2-bisaryl-bicycloheptane derivatives. The presence of quinolinylmethoxy substituent at R2-position in a molecular structure is a crucial feature for the FLAP inhibitory activity. The occurrence of R-CR-X type structural fragment (descriptor C-028) and higher number of sulfur atoms (descriptor nS) in a molecular structure are prevalent to rationalize the FLAP actions of bicycloheptane derivatives. The topological charge indices (descriptors GGI3, 3rd order Galvez topological charge index; and JGI4, 4th order Galvez mean topological charge index), path/walk ratio 2 (Randics molecular shape descriptor PW2) and atomic polarizabilities at lag 2 (descriptor GATS2p, Geary autocorrelation of lag 2 weighted by atomic polarizabilities) are also important to explain the FLAP activity. The PLS analysis has also confirmed the dominance of information content of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high quality parameters with good fitting power and the capability of assessing external data, and all of the compounds were within the applicability domain of the proposed models and were evaluated correctly.

Keywords: 2,2-bisaryl-bicycloheptane derivatives, 5-lipoxygenase activating protein (FLAP) inhibitors, Combinatorial protocol in multiple linear regression (CP-MLR), Partial least square (PLS) analysis, leukotrienes, asthma, atherosclerosis, cardiovascular disease, MK-886, MK-0591, AM103, AM679, QSAR, CoMFA, H-bond, SYSTAT, DRAGON, CONST, TOPO, MWC, BCUT, GALVEZ, 2D-AUTO, ACF, PROP, CP-MLR, PLS, LOO, Validation, LOF, AIC, Y-Randomization, Applicability Domain, descriptor, Q2-index, PW2

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Article Details

Year: 2011
Page: [32 - 43]
Pages: 12
DOI: 10.2174/157018011793663903

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