CoMFA and CoMSIA 3D-QSAR analysis of diaryloxy-methano-phenanthrene derivatives as anti-tubercular agents

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (44 compounds) of diaryloxy-methano-phenanthrene derivatives as potent antitubercular agents. The best predictions were obtained with a CoMFA standard model (q (2)=0.625, r (2)=0.994) and with CoMSIA combined steric, electrostatic, and hydrophobic fields (q (2)=0.486, r (2)=0.986). Both models were validated by a test set of seven compounds and gave satisfactory predictive r (2) values of 0.999 and 0.745, respectively. CoMFA and CoMSIA contour maps were used to analyze the structural features of the ligands to account for the activity in terms of positively contributing physicochemical properties: steric, electrostatic, and hydrophobic fields. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for further design of phenanthrene-based analogs as anti-TB agents. The resulting contour maps, produced by the best CoMFA and CoMSIA models, were used to identify the structural features relevant to the biological activity in this series of analogs. Further analysis of these interaction-field contour maps also showed a high level of internal consistency. This study suggests that introduction of bulky and highly electronegative groups on the basic amino side chain along with decreasing steric bulk and electronegativity on the phenanthrene ring might be suitable for designing better antitubercular agents.     

CoMFA and CoMSIA 3D-QSAR analysis of DMDP derivatives as anti-cancer agents

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (78 compounds) of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as potent anticancer agents. The best prediction were obtained with a CoMFA standard model (q(2) = 0.530, r(2) = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q(2) = 0.548, r(2) = 0.909). Both models were validated by a test set of ten compounds producing very good predictive r(2) values of 0.935 and 0.842, respectively. CoMFA and CoMSIA contour maps were then used to analyze the structural features of ligands to account for the activity in terms of positively contributing physiochemical properties such as steric, electrostatic, hydrophobic and hydrogen bond donor fields. The resulting contour maps produced by the best CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series of analogs. This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for the design of deazapteridine-based analogs as anticancer agents.     

Evaluation of hydrogen bonds of ecdysteroids in the ligand–receptor interactions using a protein modeling system

The insect molting hormone, 20-hydroxyecdysone (20E) and its analogs (ecdysteroids) specifically bind to the ecdysone receptor. Previously, we synthesized various ecdysteroids containing the side chain moiety of ponasterone A (PonA), and measured the binding activity against Drosophila Kc cells to study the structure–activity relationship. Here we quantitatively analyzed the structure–activity relationship for the ligand binding of ecdysteroids including 20E and PonA. Since the hydrogen bonding (HB) is one of the important physicochemical properties for ligand binding to the ecdysteroid receptor, the number of possible HBs between the ligand molecule and the receptor was manually counted in the modeled ligand–receptor complex for all compounds. The construction of the ligand–receptor model was executed by the full-automatic modeling system (FAMS) in which calculation was done by simulated annealing. The binding potency of 15 ecdysteroids to Kc-cells were linearly correlated (r² = 0.63) with the number of HBs which are observed between ligand and receptor molecule. Contribution of steric and electrostatic effects on the ligand–receptor binding was also examined using a three-dimensional quantitative structure–activity relationship (3-D QSAR), comparative molecular field analysis (CoMFA).     

Comparative quantitative structure-activity study of radical scavengers

Classic and three-dimensional (3-D) QSAR analyses of 13 radical scavengers (1-13) were performed to derive two classic, two Apex-3-D and one comparative field analysis (CoMFA) models. Two classical models with predictive cross-validated r2 (Q2) over 0.96 indicated that the activity was attributed to the electronic COH and ELUMO, steric molar refractivity (MR) and lipophilic log P. Three-dimensional quantitative structure-activity relationship (3-D-QSAR) studies were performed by 3-D pharmacophore generation (Apex-3-D) and CoMFA techniques. For Apex-3-D studies, two best models with high Q2 (0.94 and 0.97) were yielded. Structural properties contributing to the activity were not only lipophilic but also the optimum steric property and geometry of side-chain composition. For CoMFA studies, the sp3 C(+1) probe provided the best Q2 of 0.79 with steric and electrostatic contributions of 42.3 and 57.7%, respectively. The activity of four new compounds (14-17) not included in the derivation were predicted with these models. Although the derived models were from limited data, the statistic relation was predictive. The linear correlations between the experimental IC50 values and the predicted values from classical and Apex-3-D models were found to be high and significant. The predicted activity of 17 from CoMFA was much lower than the experimental value; this deviation occurred according to the missing of hydrophobic field in standard CoMFA study. In vitro and ex vivo antilipid peroxidation in mouse brain and ESR studies of 14-17 were investigated for the radical-scavenging ability. The difference between the in vitro results, antilipid peroxidation and electron spin resonance (ESR) and ex vivo results in coumarin series was found. Thus, other properties for good bioavailability besides log P should also be taken into consideration.     

Classical and three-dimensional QSAR for the inhibition of [3H]ponasterone A binding by diacylhydrazine-type ecdysone agonists to insect Sf-9 cells

The activity of 52 diacylhydrazine congeners was evaluated by measuring the inhibition of the incorporation of [3H]ponasterone A into intact Sf-9 cells. Eleven compounds were newly synthesized in this study. Results showed that the substitution of the 2-CH3 or 3-OCH3 moiety of methoxyfenozide with other groups or the removal of either group was unfavorable to the activity. The activity was quantitatively analyzed using both classical QSAR (Hansch-Fujita) and three-dimensional QSAR methods (comparative molecular field analysis, CoMFA). Sterically favorable fields were observed at the 3- and 4-positions of the benzene ring opposite from the t-butyl group (B-ring), and a sterically unfavorable field was evidenced at the 2-position. Another sterically unfavorable field developed surrounding the favorable field observed at the 4-position of the B-ring. Electrostatically negative fields were observed near the CO moiety, above the benzene ring, and at the 4-position of the B-ring. The optimum hydrophobicity of compounds in terms of their logP values was calculated to be approximately 4.1. Results of the three dimensional structure-activity relationship analyses were consistent with those obtained from the previously reported classical QSAR for 2-chlorobenzoyl analogs containing various para-substituents. The high activity of potent insecticides such as tebufenozide and chromafenozide were rationalized by CoMFA. Thus, this CoMFA result will be useful in the design of new compounds and in understanding the molecular mechanism of the ligand-receptor interactions.     

Inhibition of [3H]ponasterone A binding by ecdysone agonists in the intact Kc cell line.

Inhibition of the binding of [3H]ponasterone A ([3H]PoA) by ecdysone agonists including diacylhydrazines such as RH-5849, tebufenozide (RH-5992) and methoxyfenozide (RH-2485) was examined in intact Drosophila Kc cells. The reciprocal logarithm of the concentration at which there is 50% inhibition of [3H]PoA binding, pIC(50) (M), was determined as the binding activity for all compounds from each concentration-response curve. The order of the activity was PoA>20-hydroxyecdysone>cyasterone>inokosterone>or=makisterone A>methoxyfenozide>or=tebufenozide>ecdysone>RH-5849. The ranking of steroidal ecdysone analogs is consistent with that obtained against Spodoptera Sf-9 cells. Furthermore, in terms of pIC(50), all binding activity for ecdysone analogs, except ecdysone, estimated in the Kc cell line system was significantly higher than that for the Sf-9 cell line system. However, the activity of ecdysone was comparable between Kc and Sf-9 cells. The activity of diacylhydrazine analogs against Kc cells was significantly low compared with that against Sf-9 cells. The potency of methoxyfenozide was 1/200 that of PoA, which showed the highest activity in the Kc cell line system among all compounds tested. The activity of tebufenozide analogs having an n-pentyl or n-hexyl group instead of a 4-ethylphenyl group was similar to that of RH-5849.     

3D-QSAR studies of farnesyltransferase inhibitors: a comparative molecular field analysis approach

3D-QSAR analysis has been performed on a series of previously synthesized benzonitrile derivatives, which were screened as farnesyltransferase inhibitors, using comparative molecular field analysis (CoMFA) with partial least-square fit to predict the steric and electrostatic molecular field interactions for the activity. The CoMFA study was carried out using a training set of 34 compounds. The predictive ability of the model developed was assessed using a test set of eight compounds (r(pred)(2) as high as 0.770). The analyzed 3D-QSAR CoMFA model has demonstrated a good fit, having r(2) value of 0.991 and cross-validated coefficient q(2) value as 0.619. The analysis of CoMFA contour maps provided insight into the possible modification of the molecules for better activity.     

Comparative molecular field analysis of flavonoid inhibitors of the PIM-1 kinase

The PIM-1 protein, the product of the pim-1 oncogene, is a serine/threonine kinase. Dysregulation of the PIM-1 kinase has been implicated in the development of human malignancies including lymphomas, leukemias, and prostate cancer. Comparative molecular field analysis (CoMFA) is a 3-D QSAR technique that has been widely used, with notable success, to correlate biological activity with the steric and electrostatic properties of ligands. We have used a set of 15 flavonoid inhibitors of the PIM-1 kinase, aligned de novo by common substructure, to generate a CoMFA model for the purpose of elucidating the steric and electrostatic properties involved in flavonoid binding to the PIM-1 kinase. Partial least squares correlation between observed and predicted inhibitor potency (expressed as -logIC50), using a non-cross-validated partial least squares analysis, generated a non-cross-validated q2=0.805 for the training set (n=15) of flavonoids. The CoMFA generated steric map indicated that the PIM-1-binding site was sterically hindered, leading to more efficient binding of planar molecules over (R) or (S) compounds. The electrostatic map identified that positive charges near the flavonoid atom C8 and negative charges near C4' increased flavonoid binding. The CoMFA model accurately predicted the potency of a test set of flavonoids (n=6), generating a correlation between observed and predicted potency of q2=0.825. CoMFA models generated from additional alignment rules, which were guided by co-crystal structure ligand orientations, did not improve the correlative value of the model. Superimposing the PIM-1 kinase crystal structure onto the CoMFA contours validated the steric and electrostatic maps, elucidating the amino acid residues that potentially contribute to the CoMFA fields. Thus we have generated the first predictive model that may be used for the rational design of small-molecule inhibitors of the PIM-1 kinase.     

CoMFA and CoMSIA 3D-QSAR analysis on hydroxamic acid derivatives as urease inhibitors

Urease (EC 3.5.1.5) serves as a virulence factor in pathogens that are responsible for the development of many diseases in humans and animals. Urease allows soil microorganisms to use urea as a source of nitrogen and aid in the rapid break down of urea-based fertilizers resulting in phytopathicity. It has been well established that hydroxamic acids are the potent inhibitors of urease activity. The 3D-QSAR studies on thirty five hydroxamic acid derivatives as known urease inhibitors were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The CoMFA model produced statistically significant results with cross-validated (q(2)) 0.532 and conventional (r(2)) correlation coefficients 0.969.The model indicated that the steric field (70.0%) has greater influence on hydroxamic acid inhibitors than the electrostatic field (30.0%). Furthermore, five different fields: steric, electrostatic, hydrophobic, H-bond donor and H-bond acceptor assumed to generate the CoMSIA model, which gave q(2) 0.665 and r(2) 0.976.This model showed that steric (43.0%), electrostatic (26.4%) and hydrophobic (20.3%) properties played a major role in urease inhibition. The analysis of CoMFA and CoMSIA contour maps provided insight into the possible modification of the hydroxamic acid derivatives for improved activity.     

Synthesis, antiplatelet activity and comparative molecular field analysis of substituted 2-amino-4H-pyrido[1,2-a]pyrimidin-4-ones, their congeners and isosteric analogues

2-(1-Piperazinyl)-4H-pyrido[1,2-a]pyrimidin-4-one (5a) is a recently described in vitro inhibitor of human platelet aggregation which specifically inhibits the activity of high affinity cAMP phosphodiesterase. A number of substitution derivatives, isosteres, and analogues of 5a were now synthesized and tested in vitro for their inhibitory activity on human platelet aggregation induced in platelet-rich plasma by ADP, collagen, or the Ca2+ ionophore A23187. Among the most effective compounds, the 6-methyl, 8-methyl and 6,8-dimethyl derivatives of 5a resulted nearly as active as the lead when platelet aggregation was induced by ADP or A23187, but less active when collagen was the inducer. On the basis of present results and those previously obtained by us in this and 2-aminochromone structural fields, we have developed a statistically significant 3-D QSAR model, using comparative molecular field analysis (CoMFA), describing the variation of the antiplatelet activity in terms of molecular steric and electrostatic potential changes.     

CoMFA and HQSAR studies on 6,7-dimethoxy-4-pyrrolidylquinazoline derivatives as phosphodiesterase10A inhibitors

Phosphodiesterase10A (PDE10A) is an important enzyme with diverse biological actions in intracellular signaling systems, making it an emerging target for diseases such as schizophrenia, Huntington's disease, and diabetes mellitus. The objective of the current 3D QSAR study is to uncover some of the structural parameters which govern PDE10A inhibitory activity over PDE3A/B. Thus, comparative molecular field analysis (CoMFA) and hologram quantitative structure-activity relationship (HQSAR) studies were carried out on recently reported 6,7-dimethoxy-4-pyrrolidylquinazoline derivatives as PDE10A inhibitors. The best CoMFA model using atom-fit alignment approach with the bound conformation of compound 21 as the template yielded the steric parameter as a major contributor (nearly 70%) to the observed variations in biological activity. The best CoMFA model produced statistically significant results, with the cross-validated (r(cv)(2)) and conventional correlation (r(ncv)(2)) coefficients being 0.557 and 0.991, respectively, for the 21 training set compounds. Validation of the model by external set of six compounds yielded a high (0.919) predictive value. The CoMFA models of PDE10A and PDE3A/B activity were compared in order to address the selectivity issue of these inhibitors. The best HQSAR model for PDE10A was obtained with an r(cv)(2) of 0.704 and r(ncv)(2) of 0.902 using atoms, bonds, connections, chirality, donor, and acceptor as fragment distinction and default fragment size of 4-7 with three components for the 21 compounds. The HQSAR model predicted the external test-set of compounds well since a good agreement between the experimental and predicted values was verified. Taken together, the present QSAR models were found to accurately predict the PDE10A inhibitory activity of the test-set compounds and to yield reliable clues for further optimization of the quinazoline derivatives in the dataset.     

3D QSAR studies on GSK-3 inhibition by aloisines

GSK-3 is involved in various physiological processes and its inhibitors have been evaluated as promising drug candidates for a lot of unmet pathologies. In this paper, inhibition of GSK-3 by aloisines is investigated by 3D QSAR studies. Two alignment rules were applied to check the influence of spatial alignment of the compounds. Both the CoMFA and CoMSIA techniques were carried out and ASS procedure was applied for CoMFA to find a satisfactory model. The best QSAR model obtained is a CoMSIA model characterized with r(2) of 0.938 and q(2) of 0.673 including steric, electrostatic and hydrophobic fields, possessing good predicting ability. To get a better understanding of the relationship between chemical structure and biological activity, a complex structure of aloisine with GSK-3 was obtained by superimposing GSK-3 into the known cocrystal structure of aloisine-CDK2, and then factors that affect the inhibition activity were investigated further, combining the QSAR study with the complex structure, the results of which are in good accordance and complementary to each other.     

DAT/SERT selectivity of flexible GBR 12909 analogs modeled using 3D-QSAR methods

The dopamine reuptake inhibitor GBR 12909 (1-{2-[bis(4-fluorophenyl)methoxy]ethyl}-4-(3-phenylpropyl)piperazine, 1) and its analogs have been developed as tools to test the hypothesis that selective dopamine transporter (DAT) inhibitors will be useful therapeutics for cocaine addiction. This 3D-QSAR study focuses on the effect of substitutions in the phenylpropyl region of 1. CoMFA and CoMSIA techniques were used to determine a predictive and stable model for the DAT/serotonin transporter (SERT) selectivity (represented by pK(i) (DAT/SERT)) of a set of flexible analogs of 1, most of which have eight rotatable bonds. In the absence of a rigid analog to use as a 3D-QSAR template, six conformational families of analogs were constructed from six pairs of piperazine and piperidine template conformers identified by hierarchical clustering as representative molecular conformations. Three models stable to y-value scrambling were identified after a comprehensive CoMFA and CoMSIA survey with Region Focusing. Test set correlation validation led to an acceptable model, with q(2)=0.508, standard error of prediction=0.601, two components, r(2)=0.685, standard error of estimate=0.481, F value=39, percent steric contribution=65, and percent electrostatic contribution=35. A CoMFA contour map identified areas of the molecule that affect pK(i) (DAT/SERT). This work outlines a protocol for deriving a stable and predictive model of the biological activity of a set of very flexible molecules.     

Optimization of alpha-acylaminoketone ecdysone agonists for control of gene expression

Fifteen new alpha-acylaminoketones were prepared by four different routes in an initial effort to optimize the potency of these compounds as ecdysone agonists. The compounds were assayed in mammalian cells expressing the ecdysone receptors from Bombyx mori (BmEcR) and Choristoneura fumiferana (CfEcR) for their ability to cause expression of a reporter gene downstream of an ecdysone response element. A new alpha-acylaminoketone was identified which had activity equal to that of the standard dibenzoylhydrazine ecdysone agonist GS()-E in the assay based on CfEcR.     

Structure-activity relationships of a series of tariquidar analogs as multidrug resistance modulators

Tariquidar (XR9576) analogs, modulators of cancer multidrug resistance (MDR), were subjected to QSAR and 3D-QSAR analyses. The structural features contributing to anti-MDR activity were identified by the Free-Wilson analysis and pharmacophore search using Hoechst 33342 as a template. 3D-QSAR CoMFA and CoMSIA models were derived and tested. The best models yielded an external predictivity of 0.66-0.75 squared correlation coefficient and outlined HB-acceptor, steric, and hydrophobic fields as the most important 3D properties. On the basis of the QSAR and 3D-QSAR analyses it was suggested that the strong inhibitory potency of the compounds studied is related to the presence of a bulky aromatic ring system with a 3rd positioned heteroatom toward the anthranilamide nucleus in the opposite end of the tetrahydroquinoline group. The results can help in directing the rational design of new generations of potent P-glycoprotein MDR modulators.     

Predicting anti-HIV activity of PETT derivatives: CoMFA approach

HIV-1 (Human Immunodeficiency Virus Type-1) is the pathogenic retrovirus and causative agent of AIDS. HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as NNRTIs and NRTIs. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTIs category, there is a set of inhibitors commonly referred to as phenyl ethyl thiazolyl thiourea (PETT) derivatives. The present 3D QSAR study attempts to explore the structural requirements of phenyl ethyl thiazolyl thiourea (PETT) derivatives for anti-HIV activity. Based on the structures and biodata of previous PETT analogs, 3D-QSAR (CoMFA) study has been performed with a training set consisting of 60 molecules, which resulted in a reliable computational model with q(2)=0.657, S(PRESS)=0.957, r(2)=0.938, and standard error of estimation (SEE)=0.270 with the number of partial least square (PLS) components being 5. It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the anti-HIV activity. The predictive ability of the resultant model was evaluated using a test set comprised of 11 molecules and the predicted r(2)=0.893. This model is a more significant guide to trace the features that really matter especially with respect to the design of novel compounds.