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1.
J Mol Model ; 18(3): 1107-22, 2012 Mar.
Article in English | MEDLINE | ID: mdl-21670994

ABSTRACT

Aurora-A, the most widely studied isoform of Aurora kinase overexpressed aberrantly in a wide variety of tumors, has been implicated in early mitotic entry, degradation of natural tumor suppressor p53 and centrosome maturation and separation; hence, potent inhibitors of Aurora-A may be therapeutically useful drugs in the treatment of various forms of cancer. Here, we report an in silico study on a group of 220 reported Aurora-A inhibitors with six different substructures. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques on this series of molecules. The resultant optimum 3D-QSAR models exhibited an r (cv) (2) value of 0.404-0.582 and their predictive ability was validated using an independent test set, ending in r (pred) (2) 0.512-0.985. In addition, docking studies were employed to explore these protein-inhibitor interactions at the molecular level. The results of 3D-QSAR and docking analyses validated each other, and the key structural requirements affecting Aurora-A inhibitory activities, and the influential amino acids involved were identified. To the best of our knowledge, this is the first report on 3D-QSAR modeling of Aurora-A inhibitors, and the results can be used to accurately predict the binding affinity of related analogues and also facilitate the rational design of novel inhibitors with more potent biological activities.


Subject(s)
Protein Kinase Inhibitors/chemistry , Protein Serine-Threonine Kinases/antagonists & inhibitors , Quantitative Structure-Activity Relationship , Aurora Kinases , Computer Simulation , Humans , Models, Molecular , Protein Binding , Protein Serine-Threonine Kinases/chemistry
2.
J Mol Model ; 18(3): 991-1001, 2012 Mar.
Article in English | MEDLINE | ID: mdl-21647664

ABSTRACT

Three-dimensional quantitative structure-activity relationship studies were performed on a series of 88 histamine receptor 4 (H4R) antagonists in an attempt to elucidate the 3D structural features required for activity. Several in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), molecular docking, and molecular dynamics (MD), were carried out. The results show that both the ligand-based CoMFA model (Q (2) = 0.548, R (ncv) (2) = 0.870, R (pre) (2) = 0.879, SEE = 0.410, SEP = 0.386) and the CoMSIA model (Q (2) = 0.526, R (ncv) (2) =0.866, R (pre) (2) = 0.848, SEE = 0.416, SEP = 0.413) are acceptable, as they show good predictive capabilities. Furthermore, a combined analysis incorporating CoMFA, CoMSIA contour maps and MD results shows that (1) compounds with bulky or hydrophobic substituents at positions 4-6 in ring A (R2 substituent), positively charged or hydrogen-bonding (HB) donor groups in the R1 substituent, and hydrophilic or HB acceptor groups in ring C show enhanced biological activities, and (2) the key amino acids in the binding pocket are TRP67, LEU71, ASP94, TYR95, PHE263 and GLN266. To our best knowledge, this work is the first to report the 3D-QSAR modeling of these H4R antagonists. The conclusions of this work may lead to a better understanding of the mechanism of antagonism and aid in the design of new, more potent H4R antagonists.


Subject(s)
Histamine Antagonists/chemistry , Quantitative Structure-Activity Relationship , Receptors, G-Protein-Coupled/antagonists & inhibitors , Computer Simulation , Humans , Molecular Dynamics Simulation , Protein Binding , Receptors, Histamine , Receptors, Histamine H4
3.
J Mol Model ; 17(4): 681-93, 2011 Apr.
Article in English | MEDLINE | ID: mdl-20532805

ABSTRACT

For the first time, a set of (43) natural sesquiterpene polyol esters isolated from the root bark of Celastrus angulatus Maxim and Euonymus japonicus Thunb were subjected to 3D-QSAR comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies, with the aim of proposing novel sesquiterpene-based compounds with optimal narcotic or insecticidal activities. The established 3D-QSAR models exhibit reasonable statistical quality and prediction capabilities, with internal cross-validated Q (2) values of ∼ 0.5 and external predicted R (2) values of >0.9, respectively. The relative contributions of the steric/electrostatic fields of the 3D-QSAR models show that the electronic effect governs the narcotic activities of the molecules, but the hybrid effect of the electrostatic and hydrophobic interactions is more influential in the insecticidal activities of the compounds. These findings may have valuable implications for the development of novel natural insecticides.


Subject(s)
Insecticides/chemistry , Models, Molecular , Quantitative Structure-Activity Relationship , Animals , Esters , Insecticides/isolation & purification , Larva , Lethal Dose 50 , Moths , Polymers/chemistry , Polymers/isolation & purification , Reproducibility of Results , Sesquiterpenes/chemistry , Sesquiterpenes/isolation & purification
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