Constrained NBMPR analogue synthesis, pharmacophore mapping and 3D-QSAR modeling of equilibrative nucleoside transporter 1 (ENT1) inhibitory activity

Conformationally constrained analogue synthesis was undertaken to aid in pharmacophore mapping and 3D-QSAR analysis of nitrobenzylmercaptopurine riboside (NBMPR) congeners as equilibriative nucleoside transporter 1 (ENT1) inhibitors. In our previous study [J. Med. Chem. 2003, 46, 831-837], novel regioisomeric nitro-1,2,3,4-tetrahydroisoquinoline conformationally constrained analogues of NBMPR were synthesized and evaluated as ENT1 ligands. 7-NO(2)-1,2,3,4-Tetrahydroisoquino-2-yl purine riboside was identified as the analogue with the nitro group in the best orientation at the NBMPR binding site of ENT1. In the present study, further conformational constraining was introduced by synthesizing 5'-O,8-cyclo derivatives. The flow cytometrically determined binding affinities indicated that the additional 5'-O,8-cyclo constraining was unfavorable for binding to the ENT1 transporter. The structure-activity relationship (SAR) acquired was applied to pharmacophore mapping using the PHASE program. The best pharmacophore hypothesis obtained embodied an anti-conformation with three hydrogen-bond acceptors, one hydrophobic center, and two aromatic rings involving the 3'-OH, 4'-oxygen, the NO(2) group, the benzyl phenyl and the imidazole and pyrimidine portions of the purine ring, respectively. A PHASE 3D-QSAR model derived with this pharmacophore yielded an r(2) of 0.916 for four (4) PLS components, and an excellent external test set predictive r(2) of 0.78 for 39 compounds. This pharmacophore was used for molecular alignment in a comparative molecular field analysis (CoMFA) 3D-QSAR study that also afforded a predictive model with external test set validation predictive r(2) of 0.73. Thus, although limited, this study suggests that the bioactive conformation for NBMPR at the ENT1 transporter could be anti. The study has also suggested an ENT1 inhibitory pharmacophore, and established a predictive CoMFA 3D-QSAR model that might be useful for novel ENT1 inhibitor discovery and optimization.     

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.     

Three-dimensional quantitative structure–activity relationship study on paullones as CDK inhibitors using CoMSIA and CoMFA

3D-QSAR studies were conducted on a series of paullones as CDK inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR) methods. Two methods were compared: the widely used comparative molecular field analysis (CoMFA) and the recently reported comparative molecular similarity indices analysis (CoMSIA). Systematic variations of some parameters in CoMSIA and CoMFA were performed to search for the best 3D-QSAR model. The computed results showed that the 3D-QSAR models from CoMSIA were clearly superior to those from CoMFA. Using the best model from CoMSIA analysis, a significant cross-validated q² was obtained and the predicted biological activities of the five compounds in the test set were in good agreement with the experimental values. The correlation results obtained from CoMSIA were graphically interpreted in terms of field contribution maps allowing physicochemical properties relevant for binding to be easily mapped back onto molecular structures. The features in the CoMSIA contour maps intuitively suggested where to modify a molecular structure in terms of physicochemical properties and functional groups in order to improve its binding affinity, which is very important for improving our understanding of the ligand-receptor interactions and in helping to design compounds with improved activity.     

The discovery of inhibitors of Fas-mediated cell death pathway using the combined computational method

In this study, pharmacophore and 3D-QSAR models were developed for analogues of 3-substituted-benzofuran-2-carboxylate as inhibitors of Fas-mediated cell death pathways. Our pharmacophore model has good correspondence with experimental results and can explain the variance in biological activities coherently with respect to the structure of the data set compounds. The predictive power for our synthesized compounds were 0.96 for the pharmacophore model, 0.58 for the comparative molecular field analysis (CoMFA) model, and 0.57 for the comparative molecular similarity analysis (CoMSIA) model.     

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.     

3D-QSAR studies on thieno[3,2-d]pyrimidines as phosphodiesterase IV inhibitors

Cyclic nucleotide phosphodiesterase IV (PDE IV) inhibitors find utility in asthma and Chronic Obstructive Pulmonary Disease (COPD) therapy. A series of 29 thieno[3,2-d]pyrimidines with affinity for PDE IV was subjected to three dimensional quantitative structure activity relationship (3D-QSAR) studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Both CoMFA and CoMSIA provided statistically valid models with good correlative and predictive power. The incorporation of hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields showed insignificant improvement in CoMSIA model. The 3D-QSAR models provide information for predicting the affinity of related compounds and designing more potent inhibitors.     

Tri- and tetrasubstituted imidazoles as p38α mitogen-activated protein kinase inhibitors

The synthesis of 2,4,5-trisubstituted and 1,2,4,5-tetrasubstituted imidazoles as potent p38α mitogen-activated protein kinase inhibitors is described. The trisubstituted imidazole series was found to be more potent than the tetrasubstituted imidazole series. Many of these compounds show low-nanomolar activities in the isolated p38α MAP kinase inhibition assay. The structure-activity relationships between these two series are different and not comparable.     

p38 Regulates Pigmentation via Proteasomal Degradation of Tyrosinase

The synthesis of melanin pigments, or melanogenesis, is regulated by the balance of a variety of signal transduction pathways. Among these pathways, p38 MAPK signaling was found to be involved in stress-induced melanogenesis and to be activated by α-melanocyte-stimulating hormone (α-MSH) and ultraviolet irradiation. Previous studies have shown that α-MSH-stimulated melanogenesis can be inhibited by blocking p38 MAPK activity with SB203580, a pyridinyl imidazole compound. Consistent with this, we observed that pyridinyl imidazoles (SB203580 and SB202190) inhibited both basal and α-MSH-induced melanogenesis in B16 melanoma cells. However, SB202474, which has no ability to inhibit p38 MAPK activity and is usually used as a negative control compound in p38 MAPK studies, also suppressed melanin synthesis induction. Furthermore, the independence of the p38 kinase pathway from the repression of melanogenesis by pyridinyl imidazole compounds was also confirmed by small interfering RNA experiments. Interfering with p38 MAPK expression surprisingly stimulated melanogenesis and tyrosinase family protein expression. Although the molecular mechanism(s) by which p38 promotes the degradation of melanogenic enzymes remain to be determined, the involvement of the ubiquitin-proteasome pathway was demonstrated by co-treatment with the proteasome-specific inhibitor MG132 and the relative decrease in the ubiquitination of tyrosinase in cells transfected with p38-specific small interfering RNA.     

3D-QSAR design of novel antiepileptic sulfamides

A three-dimensional quantitative structure-activity relationship method, the comparative molecular field analysis (CoMFA), was applied to design new anticonvulsant symmetric sulfamides. The training set (27 structures) was comprised by traditional and new-generation anticonvulsant (AC) ligands that exhibit a potent activity in MES test. Physicochemical determinants of binding, such as steric and electrostatic properties, were mapped onto the molecular structures of the set, in order to interpret graphically the CoMFA results in terms of field contribution maps. The 3D-QSAR models demonstrate a good ability to predict the activity of the designed compounds (r(2)=0.967, q(2)=0.756).     

Isolation,biological evaluation and 3D-QSAR studies of insecticidal/narcotic sesquiterpene polyol esters

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.     

The molecular basis for coxib inhibition of p38alpha MAP kinase

In this work, we present the results of two combined approaches, molecular docking and comparative molecular field analysis (CoMFA), to propose how the selective cyclooxygenase-2 inhibitor celecoxib could act as a p38 mitogen-activated protein (MAP) kinase inhibitor. The docking analysis revealed why celecoxib has a less favorable binding energy (DeltaG= -12.4kcal/mol) than the selective p38 MAP kinase (p38 MAPK) inhibitor, SB203580 (DeltaG= -22.2kcal/mol). The CoMFA results revealed unfavorable steric effects that can be related to the predicted lower p38 MAP kinase inhibitory activity of celecoxib. Additionally, FlexX and CoMFA results also suggested that etoricoxib, another selective COX-2 inhibitor, could inhibit p38 MAP kinase.     

QSAR and 3D-QSAR of phenothiazine type multidrug resistance modulators in P388/ADR cells

A series of 25 phenothiazines and structurally related compounds was investigated by QSAR (quantitative structure activity relationship) and 3D-QSAR methods with respect to their MDR (multidrug resistance) reversing activity in P388/ADR- murine leukemia cell line resistant to ADR (adriamycin). The objective was to outline structural properties important for the investigated activity. Different measures for MDR reversal were used and compared. Two 3D-QSAR approaches were applied-CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis). Both, neutral and protonated forms of the compounds were investigated. Molecular models with good predictive power were derived using a hydrophobic field alone and a combination of steric, hydrophobic, and hydrogen bond acceptor fields of the compounds. In the combined models highest contribution of the hydrogen bond acceptor field was noticed. Thus, the dominant role of the hydrophobic and hydrogen bond acceptor fields for MDR reversing activity of the investigated compounds was demonstrated. The structural regions responsible for the differences in anti-MDR activity were analyzed in respect to their hydrophobic, hydrogen bond acceptor and steric nature. The results may direct design of new phenothiazines and related compounds as MDR modulators.     

Molecular docking and 3D-QSAR studies on β-phenylalanine derivatives as dipeptidyl peptidase IV inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking studies were carried out to explore the binding of 73 inhibitors to dipeptidyl peptidase IV (DPP-IV), and to construct highly predictive 3D-QSAR models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The negative logarithm of IC₅₀ (pIC₅₀) was used as the biological activity in the 3D-QSAR study. The CoMFA model was developed by steric and electrostatic field methods, and leave-one-out cross-validated partial least squares analysis yielded a cross-validated value (r_cv² {\hbox{r}}_{{\rm{cv}}}^{\rm{2}} ) of 0.759. Three CoMSIA models developed by different combinations of steric, electrostatic, hydrophobic and hydrogen-bond fields yielded significant r_cv² {\hbox{r}}_{{\rm{cv}}}^{\rm{2}} values of 0.750, 0.708 and 0.694, respectively. The CoMFA and CoMSIA models were validated by a structurally diversified test set of 18 compounds. All of the test compounds were predicted accurately using these models. The mean and standard deviation of prediction errors were within 0.33 and 0.26 for all models. Analysis of CoMFA and CoMSIA contour maps helped identify the structural requirements of inhibitors, with implications for the design of the next generation of DPP-IV inhibitors for the treatment of type 2 diabetes.     

3D-QSAR of N-myristoyltransferase inhibiting antifungal agents by CoMFA and CoMSIA methods

A series of benzofuran antifungals was examined to determine the structural requirements of N-myristoyltransferase (Nmt) enzyme inhibition by three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Evaluation of 20 compounds (training set) served to establish the model, which was validated by evaluation of a set of 6 compounds (test set). The lowest energy conformer of the most active molecule obtained from systematic search was used as the template structure for the alignment. The best predictions were obtained with the CoMFA model from RMS fit, with r(2)(cv)=0.828, r(2)(conv)=0.989, r(2)(pred)=0.754 and with the CoMSIA model combining hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields with r(2)(cv)=0.821, r(2)(conv)=0.978 and r(2)(pred)=0.747. The models obtained from the present study can be useful for the development of new Nmt inhibitors as potential antifungals. The docking studies were also carried out wherein the active and inactive molecules were docked into the active site of the recently reported Candida albicans Nmt (CaNmt) crystal structure to analyze enzyme-inhibitor interactions. The results obtained from the present 3D-QSAR and docking studies were found complimentary.     

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.     

Molecular docking and 3D-QSAR studies of Yersinia protein tyrosine phosphatase YopH inhibitors

Three-dimensional quantitative structure-activity relationship (QSAR) studies were conducted on two classes of recently explored compounds with known YopH inhibitory activities. Docking studies were employed to position the inhibitors into the YopH active site to determine the probable binding conformation. Good correlations between the predicated binding free energies and the inhibitory activities were found for two subsets of phosphate mimetics: alpha-ketocarboxylic acid and squaric acid (R2=0.70 and 0.68, respectively). The docking results also provided a reliable conformational alignment scheme for 3D-QSAR modeling. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed based on the docking conformations, giving q2 of 0.734 and 0.754 for CoMFA and CoMSIA models, respectively. The 3D-QSAR models were significantly improved after removal of an outlier (q2=0.829 for CoMFA and q2=0.837 for CoMSIA). The predictive ability of the models was validated using a set of compounds that were not included in the training set. Mapping the 3D-QSAR models to the active site of YopH provides new insight into the protein-inhibitor interactions for this enzyme. These results should be applicable to the prediction of the activities of new YopH inhibitors, as well as providing structural implications for designing potent and selective YopH inhibitors as antiplague agents.     

3D-QSAR study of adamantyl N-benzylbenzamides as melanogenesis inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) of polyhydroxylated N-benzylbenzamide derivatives containing an adamantyl moiety were performed to understand the mechanism of action and structure–activity relationship of these compounds. Contour map analysis indicated that steric contributions of the adamantyl moiety and electrostatic contributions of the hydroxyl group at the 3-position are important in the activity. Activities of the training set and test sets predicted by CoMFA fit well with actual activities, demonstrating that CoMFA, along with the best calculated q² value, has the best predictive ability.     

3D-QSAR analysis on benzazole derivatives as eukaryotic topoisomerase II inhibitors by using comparative molecular field analysis method

Selective topoisomerase II inhibitors have created a great deal of interest in recent years for the design of new antitumoral compounds. 3D-QSAR analysis has been performed on a series of previously synthesized benzoxazole, benzimidazole, and oxazolo(4,5-b)pyridine derivatives, which are screened as eukaryotic topoisomerase II inhibitors, using comparative molecular field analysis (CoMFA) with partial least squares fit to predict the steric and electrostatic molecular field interactions for the activity. The CoMFA study was carried out using a training set of 16 compounds. The predictive ability of the model was assessed using a test set of 7 compounds. The analyzed 3D-QSAR CoMFA model has demonstrated a good fit, having r(2) value of 0.997 and cross-validated coefficient q(2) value as 0.435 for the model. The obtained model reveals that the electronegatively charged substituents such as NO(2) or COOCH(3) group on position R and/or R(1) at the heterocyclic ring system and positively charged atom and/or atom groups located between the benzazole moiety and 2-substituted phenyl ring as a bridge element improve the activity. On the other hand, a bulky substituent, such as methoxy group, attached to the ortho position of 2-phenyl-5-nitro-benzoxazole (1) enhances the activity similar to compound 13, which is both a meta and para substituent of the phenyl group attached to the 2-position of benzimidazole ring system, fit into the favored steric region to improve the activity.     

3D QSAR studies,pharmacophore modeling,and virtual screening of diarylpyrazole–benzenesulfonamide derivatives as a template to obtain new inhibitors,using human carbonic anhydrase II as a model protein

A 3D-QSAR modeling was performed on a series of diarylpyrazole-benzenesulfonamide derivatives acting as inhibitors of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1). The compounds were collected from two datasets with the same scaffold, and utilized as a template for a new pharmacophore model to screen the ZINC database of commercially available derivatives. The datasets were divided into training, test, and validation sets. As the first step, comparative molecular field analysis (CoMFA), CoMFA region focusing and comparative molecular similarity indices analysis (CoMSIA) in parallel with docking studies were applied to a set of 41 human (h) CA II inhibitors. The validity and the prediction capacity of the resulting models were evaluated by leave-one-out (LOO) cross-validation approach. The reliability of the model for the prediction of possibly new CA inhibitors was also tested.