Self-organizing molecular field analysis on alpha(1a)-adrenoceptor dihydropyridine antagonists

Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies on α(1A)-adrenergic receptor antagonists based on pharmacophore molecular alignment

The α_1A-adrenergic receptor (α_1A-AR) antagonist is useful in treating benign prostatic hyperplasia, lower urinary tract symptoms, and cardiac arrhythmia. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a set of α_1A-AR antagonists of N-aryl and N-nitrogen class. Statistically significant models constructed from comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established based on a training set of 32 ligands using pharmacophore-based molecular alignment. The leave-oneout cross-validation correlation coefficients were q²_CoMFA = 0.840 and q²_CoMSIA = 0.840. The high correlation between the cross-validated/predicted and experimental activities of a test set of 12 ligands revealed that the CoMFA and CoMSIA models were robust (r²_pred/CoMFA = 0.694; r²_pred/CoMSIA = 0.671). The generated models suggested that electrostatic, hydrophobic, and hydrogen bonding interactions play important roles between ligands and receptors in the active site. Our study serves as a guide for further experimental investigations on the synthesis of new compounds. Structural modifications based on the present 3D-QSAR results may lead to the discovery of other α_1A-AR antagonists.

Self-organizing molecular field analysis on pregnane derivatives as human steroidal 5alpha-reductase inhibitors

Normal growth and development of human prostate is regulated by the androgens which balances cell proliferation and apoptosis. Testosterone (T) and dihydrotestosterone (DHT) are the two key androgens that stimulate most of the androgen action in prostate. Testosterone is converted to DHT by the membrane bound NADPH-dependent 5alpha-reductase enzyme. As a consequence of the important observation that progesterone and deoxycortisone inhibits the synthesis of DHT by competing with 4-en-3-one function of the testosterone for the 5alpha-reductase enzyme a number of pregnane derivatives were synthesized and have been reported as inhibitors of human 5alpha-reductase enzyme. Due to lack of information on the crystal structure of human 5alpha-reductase, ligand-based 3D-QSAR study has been performed on pregnane derivatives using self-organizing molecular field analysis (SOMFA) for rationalizing the molecular properties and human 5alpha-reductase inhibitory activities. The statistical results having good cross-validated r(cv)(2) (0.881), non-cross-validated r(2) (0.893) and F-test value (175.527), showed satisfied predictive ability r(pred)(2) (0.777). Analysis of SOMFA models through electrostatic and shape grids provide useful information for the design and optimization of steroidal structure as novel human 5alpha-reductase inhibitors.

Computational studies of the binding site of alpha1A-adrenoceptor antagonists

Aimed at achieving a good understanding of the 3-dimensional structures of human alpha1A-adrenoceptor (alpha1A-AR), we have successfully developed its homology model based on the crystal structure of beta2-AR. Subsequent structural refinements were performed to mimic the receptor's natural membrane environment by using molecular mechanics (MM) and molecular dynamics (MD) simulations in the GBSW implicit membrane model. Through molecular docking and further simulations, possible binding modes of subtype-selective alpha1A-AR antagonists, Silodosin, RWJ-69736 and (+)SNAP-7915, were examined. Results of the modeling and docking studies are qualitatively consistent with available experimental data from mutagenesis studies. The homology model built should be very useful for designing more potent subtype-selective alpha1A-AR antagonists and for guiding further mutagenesis studies.

Improving the performance of SOMFA by use of standard multivariate methods

Self-Organizing Molecular Field Analysis (SOMFA) comes with a built-in regression methodology, the Self-Organizing Regression (SOR), instead of relying on external methods such as PLS. In this article we present a proof of the equivalence between SOR and SIMPLS with one principal component. Thus, the modest performance of SOMFA on complex datasets can be primarily attributed to the low performance of the SOMFA regression methodology. A multi-component extension of the original SOR methodology (MCSOR) is introduced, and the performances of SOR, MCSOR and SIMPLS are compared using several datasets. The results indicate that in general the performance of SOMFA models is greatly improved if SOR is replaced with a more sophisticated regression method. The results obtained for the Cramer (CBG) dataset further underline the fact that it is a very poor benchmark dataset and should not be used to evaluate the performance of QSAR techniques.

Pharmacophore-based design, synthesis, biological evaluation, and 3D-QSAR studies of aryl-piperazines as α1-adrenoceptor antagonists

Phenyl-piperazines were designed and synthesized based on pharmacophore for uro-selective alpha(1)-adrenoceptor antagonists and 3D chemical database searching. Within this series, three compounds, 2, 3, and 13, showed similar or better alpha(1)-AR antagonistic activity compared with prazosin. The 3D-QSAR study of these compounds may provide useful information for the development of novel aryl-piperazines as uro-selective alpha(1)-adrenoceptor antagonists, which can be used for the treatment of BPH with fewer side effects.