<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Three-dimensional quantitative structure activity relationship (3D QSAR) analysis was carried out on a et of 56 <italic>N,N’</italic>-diarylsquaramides, <italic>N,N’</italic>-diarylureas and diaminocyclobutenediones in order to understand their antagonistic activities against CXCR2. The studies included comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Models with good predictive abilities were generated with CoMFA <italic>q2 </italic>0.709, <italic>r2 </italic>(non-cross-validated square of correlation coefficient) = 0.951, <italic>F </italic>value = 139.903, <italic>r2 </italic>bs = 0.978 with five components, standard error of estimate = 0.144 and the CoMSIA <italic>q2 </italic>= 0.592, <italic>r2 </italic>= 0.955, <italic>F </italic>value = 122.399, <italic>r2 </italic>bs = 0.973 with six components, standard error of estimate = 0.141. In addition, a homology model of CXCR2 was used for docking based alignment of the compounds. The most active compound then served as a template for alignment of the remaining structures. Further, mapping of contours onto the active site validated each other in terms of residues involved with reference to the respective contours. This integrated molecular docking based alignment followed by 3D QSAR studies provided a further insight to support the structure-based design of CXCR2 antagonistic agents with improved activity profiles. Furthermore, <italic>in silico </italic>screening was adapted to the QSAR model in order to predict the structures of new, potentially active compounds.</p></abstract>

Three-dimensional quantitative structure activity relationship (3D QSAR) analysis was carried out on a et of 56 N,N’-diarylsquaramides, N,N’-diarylureas and diaminocyclobutenediones in order to understand their antagonistic activities against CXCR2. The studies included comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Models with good predictive abilities were generated with CoMFA q2 0.709, r2 (non-cross-validated square of correlation coefficient) = 0.951, F value = 139.903, r2 bs = 0.978 with five components, standard error of estimate = 0.144 and the CoMSIA q2 = 0.592, r2 = 0.955, F value = 122.399, r2 bs = 0.973 with six components, standard error of estimate = 0.141. In addition, a homology model of CXCR2 was used for docking based alignment of the compounds. The most active compound then served as a template for alignment of the remaining structures. Further, mapping of contours onto the active site validated each other in terms of residues involved with reference to the respective contours. This integrated molecular docking based alignment followed by 3D QSAR studies provided a further insight to support the structure-based design of CXCR2 antagonistic agents with improved activity profiles. Furthermore, in silico screening was adapted to the QSAR model in order to predict the structures of new, potentially active compounds.

Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies

Bioinformatics Division, Osmania University, Hyderabad-500007 Andhra Pradesh, India

Acta Pharmaceutica

Three-dimensional quantitative structure activity relationship (3D QSAR) analysis was carried out on a et of 56 N,N’-diarylsquaramides, N,N’-diarylureas and...

Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies

Published Online: Nov 06, 2012

Page range: 287 - 304

DOI: https://doi.org/10.2478/v10007-012-0029-7

Keywords
CXCR2, homology modeling, CoMFA, CoMSIA, PLS, docking

This content is open access.

Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies

Published Online: Nov 06, 2012

Page range: 287 - 304

DOI: https://doi.org/10.2478/v10007-012-0029-7

KeywordsCXCR2, homology modeling, CoMFA, CoMSIA, PLS, docking

This content is open access.

Keywords
CXCR2, homology modeling, CoMFA, CoMSIA, PLS, docking