CYP19 (aromatase): exploring the scaffold flexibility for novel selective inhibitors

Several derivatives out of a series of antifungal agents exhibited a good inhibitory potency against aromatase as well as a fairly good selectivity toward CYP17, even if lacking H-bond accepting substituents. Their common structural feature is a flexible backbone that did not fit into previously reported CYP19 models. Thus, a ligand-based approach was exploited to develop a novel statistically robust, self-consistent and predictive 3D-QSAR model herein proposed as a helpful tool to design new aromatase inhibitors.     

3D-QSAR and docking studies of aldehyde inhibitors of human cathepsin K

In order to better understand the structural and chemical features of human cathepsin K (CatK), which is an important cysteine protease in the pathogenesis of osteoporosis, the 3D-QSAR (CoMFA) studies were conducted on recently explored aldehyde compounds with known CatK inhibitory activities. The genetic algorithm of GOLD2.2 has been employed to position 59 aldehyde compounds into the active sites of CatK to determine the probable binding conformation. Good correlations between the predicted binding free energies and the experimental inhibitory activities suggested that the identified binding conformations of these potential inhibitors are reliable. The docking results also provided a reliable conformational alignment scheme for 3D-QSAR model. Based on the docking conformations, highly predictive comparative molecular field analysis (CoMFA) was performed with q2 value of 0.723. The predictive ability was validated by some compounds that were not included in the training set. Furthermore, the CoMFA model was mapped back to the binding sites of CatK, to get a better understanding of vital interactions between the aldehyde compounds and the protease. The CoMFA field distributions are in good agreement with the structural characteristics of the binding groove of the CatK, which suggested that the n-Bu in R4 position is the favor group substitute at P1 and moderate groups in R2 group are required on P2 substitute. In addition, 3D-QSAR results also demonstrated that aldehyde is an important pharmacophore because of electrostatic effect. These results, together with the good correlations between the inhibitory activities and the binding free energies predicted by GOLD2.2, demonstrated the power of combining docking/QSAR approach to explore the probable binding conformations of compounds at the active sites of the protein target, and further provided useful information in understanding the structural and chemical features of CatK in designing and finding new potential inhibitors.     

Docking and 3D-QSAR modeling of cyclin-dependent kinase 5/p25 inhibitors

Structure-based 3D-QSAR approaches (CoMFA and CoMSIA) were applied to understand the structural requirements of the Cyclin-dependent kinase 5/p25 inhibitors. Cyclin-dependent kinase 5 (CDK5) is believed to play an important role in the development of the central nervous system during the process of mammalian embryogenesis. Genetic algorithm based docking program (GOLD) was successfully utilized to orient the compounds inside the binding pocket of the CDK5/p25 structure. The adapted alignment method with the suitable parameters resulted in a reliable model. Furthermore, the final model was robust enough to forecast the activities of test compounds, satisfactorily. The contour maps were produced around the functional groups to understand the SAR requirements. Moreover, we also investigate the structural attributes of the inhibitors which make them selective toward CDK5/p25 over its close counterpart, i.e., CDK2. The study could be helpful to rationalize the new compounds with better inhibition and selectivity profiles against CDK5/p25.     

Docking studies of piperine - iron conjugate with human CYP450 3A4

Piperine, a major constituent of Piper nigrum (Black pepper), is one of the well known components in many Ayurvedic formulations. Piperine is most studied bioenhancer because it inhibits drug metabolizing enzymes in rodents and increases plasma concentrations of several drugs, including P-glycoprotein substrates. However, there areno evidences on piperine-iron conjugate to inhibit human CYP450 3A4. We therefore investigated the influence of piperine-Fe conjugate to study the metabolism of iron with CYP450 3A4. Our in silico results showed that Piperine when conjugated with iron, inhibited activity of CYP450 3A4. This improved the binding of piperine-Fe conjugate with CYP450 3A4 and increased bioavailability.     

3D-QSAR studies on malonyl coenzyme A decarboxylase inhibitors

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of Malonyl Co-A decarboxylase (MCD) inhibitors (Cheng et al. J. Med. Chem.2006, 49, 1517-1525 and Cheng et al. Bioorg. Med. Chem. Lett.2006, 16, 695-700). These inhibitors have shown protective action on the ischemic heart by inhibiting fatty acid oxidation. The CoMFA model produced statistically significant results, with the cross-validated and conventional correlation coefficients being 0.544 and 0.986, respectively. The best results were obtained by combining steric, electrostatic, hydrophobic, and H-bond acceptor fields in CoMSIA, in which case the respective cross-validated and conventional correlation coefficients were 0.551 and 0.918. The predictive ability of CoMFA and CoMSIA, determined using a test set of 24 compounds, gave predictive correlation coefficients of 0.718 and 0.725, respectively. The information obtained from CoMFA and CoMSIA 3D contour maps may be of utility in the design of more potent MCD inhibitors.     

Computational studies of COX-2 inhibitors: 3D-QSAR and docking

The 3D-QSAR (three-dimensional quantitative structure-activity relationships) studies for 88 selective COX-2 (cyclooxygenase-2) inhibitors belonging to three chemical classes (triaryl rings, diaryl cycloalkanopyrazoles, and diphenyl hydrazides) were conducted using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Partial least squares analysis produced statistically significant models with q(2) values of 0.84 and 0.79 for CoMFA and CoMSIA, respectively. The binding energies calculated from flexible docking were correlated with inhibitory activities by the least-squares fit method. The three chemical classes of inhibitors showed reasonable internal predictability (r(2)=0.51, 0.49, and 0.54), but the sulfonyl-containing inhibitors demonstrated distinctively low binding energy compared to the others. The electrostatic interaction energy between the Arg513 of the COX-2 active site and sulfonyl group of the triaryl rings seemed to have the responsibility for difference in binding energy. Comparative binding energy (COMBINE) analyses gave q(2) values of 0.64, 0.63, and 0.50 for triaryl rings, diaryl cycloalkanopyrazoles, and diphenyl hydrazides, respectively. In this COMBINE model, some protein residues were highlighted as particularly important for inhibitory activity. The combination of ligand-based and structure-based models provided an improved understanding in the interaction between the three chemical classes and the COX-2.     

Molecular docking and 3D-QSAR studies of HIV-1 protease inhibitors

HIV-1 protease is an obligatory enzyme in the replication process of the HIV virus. The abundance of structural information on HIV-1PR has made the enzyme an attractive target for computer-aided drug design strategies. The daunting ability of the virus to rapidly generate resistant mutants suggests that there is an ongoing need for new HIV-1PR inhibitors with better efficacy profiles and reduced toxicity. In the present investigation, molecular modeling studies were performed on a series of 54 cyclic urea analogs with symmetric P2/P2′ substituents. The binding modes of these inhibitors were determined by docking. The docking results also provided a reliable conformational superimposition scheme for the 3D-QSAR studies. To gain insight into the steric, electrostatic, hydrophobic and hydrogen-bonding properties of these molecules and their influence on the inhibitory activity, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed. Two different alignment schemes viz. receptor-based and atom-fit alignment, were used in this study to build the QSAR models. The derived 3D-QSAR models were found to be robust with statistically significant r ² and r ² _pred values and have led to the identification of regions important for steric, hydrophobic and electronic interactions. The predictive ability of the models was assessed on a set of molecules that were not included in the training set. Superimposition of the 3D-contour maps generated from these models onto the active site of enzyme provided additional insight into the structural requirements of these inhibitors. The CoMFA and CoMSIA models were used to design some new inhibitors with improved binding affinity. Pharmacokinetic and toxicity predictions were also carried out for these molecules to gauge their ADME and safety profile. The computational results may open up new avenues for synthesis of potent HIV-1 protease inhibitors.     

3D-QSAR studies on 4-hydroxyphenylpyruvate dioxygenase inhibitors by comparative molecular field analysis (CoMFA)

A comparative molecular field analysis (CoMFA) of alkanoic acid 3-oxo-cyclohex-1-enyl ester and 2-acylcyclohexane-1,3-dione derivatives of 4-hydroxyphenylpyruvate dioxygenase inhibitors has been performed to determine the factors required for the activity of these compounds. The substrate's conformation abstracted from dynamic modeling of the enzyme-substrate complex was used to build the initial structures of the inhibitors. Satisfactory results were obtained after an all-space searching procedure, performing a leave-one out (LOO) cross-validation study with cross-validation q(2) and conventional r(2) values of 0.779 and 0.989, respectively. The results provide the tools for predicting the affinity of related compounds, and for guiding the design and synthesis of new HPPD ligands with predetermined affinities.     

Expression of human aromatase (CYP19) in Escherichia coli by N-terminal replacement and induction of cold stress response

CYP19 (P450arom) catalyzes the aromatization reaction of C19 steroids leading to estrogens. While readily expressed in insect cells, the human P450arom has been a difficult P450 to express in Escherichia coli at useful levels. In the present study, we replaced the N-terminal sequence in human CYP19 with the corresponding sequences of other microsomal P450s (CYP2C11 and CYP17) that are efficiently expressed in E. coli. Although the N-terminal replacement alone was not sufficient for the expression, human P450arom was successfully expressed up to the level of 240nmol/l culture by the combination of the N-terminal replacement and the induction of cold stress response by 1 microg/ml chloramphenicol. Membrane fractions containing the expressed P450arom catalyzed aromatization of androstenedione with a specific activity of 4.9 nmol/min/nmol P450. Our results are important to provide large quantities of human P450arom as an active form for structure-function studies.     

3D-QSAR studies on fluroquinolones derivatives as inhibitors for tuberculosis

A quantitative structure activity relationship (QSAR) study was performed on the fluroquinolones known to have anti-tuberculosis activity. The 3D-QSAR models were generated using stepwise variable selection of the four methods - multiple regression (MR), partial least square regression (PLSR), principal component regression (PCR) and artificial neural networks (kNN-MFA). The statistical result showed a significant correlation coefficient q(2) (90%) for MR model and an external test set of (pred_r(2)) -1.7535, though the external predictivity showed to improve using kNN-MFA method with pred_r(2) of -0.4644. Contour maps showed that steric effects dominantly determine the binding affinities. The QSAR models may lead to a better understanding of the structural requirements of anti-tuberculosis compounds and also help in the design of novel molecules.     

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r2, q2(loo) and r2(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r2(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.