title: Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies.
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.
authors.affiliation: Bioinformatics Division, Osmania University, Hyderabad-500007, Andhra Pradesh, India.
authors.forename: Shravan Kumar
authors.initials: SK
authors.lastname: Gunda
authors.forename: Rohith Kumar
authors.initials: RK
authors.lastname: Anugolu
authors.forename: Sri Ramya
authors.initials: SR
authors.lastname: Tata
authors.forename: Saikh
authors.initials: S
authors.lastname: Mahmood
mesh_terms: D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000737:chemistry* / Q000494:pharmacology; D001185:Artificial Intelligence; D020134:Catalytic Domain; D019295:Computational Biology; D003503:Cyclobutanes / Q000737:chemistry* / Q000494:pharmacology; D030562:Databases, Protein; D005103:Expert Systems; D006801:Humans; D007700:Kinetics; D008958:Models, Molecular; D008968:Molecular Conformation; D062105:Molecular Docking Simulation; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D023063:Receptors, Interleukin-8B / Q000037:antagonists & inhibitors* / Q000737:chemistry*; D013449:Sulfonamides / Q000737:chemistry* / Q000494:pharmacology; D014508:Urea / Q000031:analogs & derivatives* / Q000737:chemistry / Q000494:pharmacology
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal; D003503:Cyclobutanes; D023063:Receptors, Interleukin-8B; D013449:Sulfonamides; C527748:squaric acid amide; D014508:Urea