Discovery of FIXa inhibitors by combination of pharmacophore modeling,molecular docking,and 3D-QSAR modeling

Human Coagulation Factor IXa (FIXa), specifically inhibited at the initiation stage of the blood coagulation cascade, is an excellent target for developing selective and safe anticoagulants. To explore this inhibitory mechanism, 86 FIXa inhibitors were selected to generate pharmacophore models and subsequently SAR models. Both best pharmacophore model and ROC curve were built through the Receptor–Ligand Pharmacophore Generation module. CoMFA model based on molecular docking and PLS factor analysis methods were developed. Model propagations values are q²?=?0.709, r²?=?0.949, and r²_pred?=?0.905. The satisfactory q² value of 0.609, r² value of 0.962, and r²_pred value of 0.819 for CoMSIA indicated that the CoMFA and CoMSIA models are both available to predict the inhibitory activity on FIXa. On the basis of pharmacophore modeling, molecular docking, and 3D-QSAR modeling screening, six molecules are screened as potential FIXa inhibitors.     

Pharmacophore generation and atom-based 3D-QSAR of novel quinoline-3-carbonitrile derivatives as Tpl2 kinase inhibitors

Tumour progression locus-2 (Tpl2) is a serine/threonine kinase, which regulates the expression of tumour necrosis factor α. The article describes the development of a robust pharmacophore model and the investigation of structure-activity relationship analysis of quinoline-3-carbonitrile derivatives reported for Tpl2 kinase inhibition. A five point pharmacophore model (ADRRR) was developed and used to derive a predictive atom-based 3-dimensional quantitative structure activity relationship (3D-QSAR) model. The obtained 3D-QSAR model has an excellent correlation coefficient value (r²?=?0.96), Fisher ratio (F?=?131.9) and exhibited good predictive power (q²?=?0.79). The QSAR model suggests that the inclusion of hydrophobic substituents will enhance the Tpl2 kinase inhibition. In addition, H-bond donating groups, negative ionic groups and electron withdrawing groups positively contribute to the Tpl2 kinase inhibition. Further, pharmacophoric model was validated by the receiver operating characteristic curve analysis and was employed for virtual screening to identify six potential Tpl2 kinase inhibitors. The findings of this study provide a set of guidelines for designing compounds with better Tpl2 kinase inhibitory potency.     

Developing consensus 3D-QSAR and pharmacophore models for several beta-secretase,farnesyl transferase and histone deacetylase inhibitors

Three consensus 3D-QSAR (c-3D-QSAR) models were built for 38, 34, and 78 inhibitors of β-secretase, histone deacetylase, and farnesyltransferase, respectively. To build an individual 3D-QSAR model, the structures of an inhibitor series are aligned through docking of a protein receptor into the active site using the program GOLD. CoMFA, CoMSIA, and Catalyst are then performed for the training set of each structurally aligned inhibitor series to obtain a 3D-QSAR model. Since the consensus in features identified is high for the same pharmacophore features selected for building a 3D-QSAR model by a 3D-QSAR method, a c-3D-QSAR model for each inhibitor series is constructed by combining the pharmacophore features selected for building the 3D-QSAR model using the SYBYL spread sheet and PLS module. Each c-3D-QSAR pharmacophore model built was examined visually and compared with that obtained by simultaneous mapping of the corresponding 3D-QSAR pharmacophores built onto a selected inhibitor structure. It was found that the c-3D-QSAR model built for an inhibitor series improves not only the overall prediction statistics for both training and test sets but also the prediction accuracy for some less active inhibitors of the series.     

Pharmacophore modelling and atom-based 3D-QSAR studies on N-methyl pyrimidones as HIV-1 integrase inhibitors

Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to N-methyl pyrimidones as HIV-1 integrase inhibitors. Based on the ligand-based pharmacophore model, we got 5-point pharmacophore model AADDR, with two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R). The generated pharmacophore-based alignment was used to derive a predictive atom-based 3D-QSAR model for the training set (r²?=?0.92, SD?=?0.16, F?=?84.8, N?=?40) and for test set (Q²?=?0.71, RMSE?=?0.06, Pearson R?=?0.90, N?=?10). From these results, AADDR pharmacophore feature was selected as best common pharmacophore hypothesis, and atom-based 3D-QSAR results also support the outcome by means of favourable and unfavourable regions of hydrophobic and electron-withdrawing groups for the most potent compound 30. These results can be useful for further design of new and potent HIV-1 IN inhibitors.     

Insights into hERG K+ channel structure and function from NMR studies

The unique gating kinetics of hERG K⁺ channels are critical for normal cardiac repolarization, and patients with mutations in hERG have a markedly increased risk of cardiac arrhythmias and sudden cardiac arrest. HERG K⁺ channels are also remarkably promiscuous with respect to drug binding, which has been a very significant problem for the pharmaceutical industry. Here, we review the progress that has been made in understanding the structure and function of hERG K⁺ channels with a particular focus on nuclear magnetic resonance studies of the domains of the hERG K⁺ channel.     

Receptor based 3D-QSAR to identify putative binders of Mycobacterium tuberculosis Enoyl acyl carrier protein reductase

In the current study, the applicability and scope of 3D-QSAR models (CoMFA and CoMSIA) to complement virtual screening using 3D pharmacophore and molecular docking is examined and applied to identify potential hits against Mycobacterium tuberculosis Enoyl acyl carrier protein reductase (MtENR). Initially CoMFA and CoMSIA models were developed using series of structurally related arylamides as MtENR inhibitors. Docking studies were employed to position the inhibitors into MtENR active site to derive receptor based 3D-QSAR models. Both CoMFA and CoMSIA yielded significant cross validated q² values of 0.663 and 0.639 and r² values of 0.989 and 0.963, respectively. The statistically significant models were validated by a test set of eight compounds with predictive r² value of 0.882 and 0.875 for CoMFA and CoMSIA. The contour maps from 3D-QSAR models in combination with docked binding structures help to better interpret the structure activity relationship. Integrated with CoMFA and CoMSIA predictive models structure based (3D-pharmacophore and molecular docking) virtual screening have been employed to explore potential hits against MtENR. A representative set of 20 compounds with high predicted IC₅₀ values were sorted out in the present study.     

Structure of the pore-helix of the hERG K<Superscript>+</Superscript> channel

The hERG K⁺ channel undergoes rapid inactivation that is mediated by ‘collapse’ of the selectivity filter, thereby preventing ion conduction. Previous studies have suggested that the pore-helix of hERG may be up to seven residues longer than that predicted by homology with channels with known crystal structures. In the present work, we determined structural features of a peptide from the pore loop region of hERG (residues 600–642) in both sodium dodecyl sulfate (SDS) and dodecyl phosphocholine (DPC) micelles using NMR spectroscopy. A complete structure calculation was done for the peptide in DPC, and the localization of residues inside the micelles were analysed by using a water-soluble paramagnetic reagent with both DPC and SDS micelles. The pore-helix in the hERG peptide was only two–four residues longer at the N-terminus, compared with the pore helices seen in the crystal structures of other K⁺ channels, rather than the seven residues suggested from previous NMR studies. The helix in the peptide spanned the same residues in both micellar environments despite a difference in the localization inside the respective micelles. To determine if the extension of the length of the helix was affected by the hydrophobic environment in the two types of micelles, we compared NMR and X-ray crystallography results from a homologous peptide from the voltage gated potassium channel, KcsA.     

3D-QSAR studies on fluoropyrrolidine amides as dipeptidyl peptidase IV inhibitors by CoMFA and CoMSIA

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses using CoMFA and CoMSIA methods were conducted on a series of fluoropyrrolidine amides as dipeptidyl peptidase IV (DP-IV) inhibitors. The selected ligands were docked into the binding site of the 3D model of DP-IV using the GOLD software, and the possible interaction models between DP-IV and the inhibitors were obtained. Based on the binding conformations of these fluoropyrrolidine amides and their alignment inside the binding pocket of DP-IV, predictive 3D-QSAR models were established by CoMFA and CoMSIA analyses, which had conventional r ² and cross-validated coefficient values () up to 0.982 and 0.555 for CoMFA and 0.953 and 0.613 for CoMSIA, respectively. The predictive ability of these models was validated by six compounds that were in the testing set. Structure-based investigations and the final 3D-QSAR results provide the guide for designing new potent inhibitors.     

Pharmacophore modelling and atom-based 3D-QSAR studies on N-methyl pyrimidones as HIV-1 integrase inhibitors

Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to N-methyl pyrimidones as HIV-1 integrase inhibitors. Based on the ligand-based pharmacophore model, we got 5-point pharmacophore model AADDR, with two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R). The generated pharmacophore-based alignment was used to derive a predictive atom-based 3D-QSAR model for the training set (r(2)?=?0.92, SD?=?0.16, F?=?84.8, N?=?40) and for test set (Q(2)?=?0.71, RMSE?=?0.06, Pearson R?=?0.90, N?=?10). From these results, AADDR pharmacophore feature was selected as best common pharmacophore hypothesis, and atom-based 3D-QSAR results also support the outcome by means of favourable and unfavourable regions of hydrophobic and electron-withdrawing groups for the most potent compound 30. These results can be useful for further design of new and potent HIV-1 IN inhibitors.     

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.     

Pharmacophore generation and atom-based 3D-QSAR of novel quinoline-3-carbonitrile derivatives as Tpl2 kinase inhibitors

Tumour progression locus-2 (Tpl2) is a serine/threonine kinase, which regulates the expression of tumour necrosis factor α. The article describes the development of a robust pharmacophore model and the investigation of structure-activity relationship analysis of quinoline-3-carbonitrile derivatives reported for Tpl2 kinase inhibition. A five point pharmacophore model (ADRRR) was developed and used to derive a predictive atom-based 3-dimensional quantitative structure activity relationship (3D-QSAR) model. The obtained 3D-QSAR model has an excellent correlation coefficient value (r(2)= 0.96), Fisher ratio (F = 131.9) and exhibited good predictive power (q(2) = 0.79). The QSAR model suggests that the inclusion of hydrophobic substituents will enhance the Tpl2 kinase inhibition. In addition, H-bond donating groups, negative ionic groups and electron withdrawing groups positively contribute to the Tpl2 kinase inhibition. Further, pharmacophoric model was validated by the receiver operating characteristic curve analysis and was employed for virtual screening to identify six potential Tpl2 kinase inhibitors. The findings of this study provide a set of guidelines for designing compounds with better Tpl2 kinase inhibitory potency.     

3D-QSAR based pharmacophore modeling and virtual screening for identification of novel pteridine reductase inhibitors

Pteridine reductase is a promising target for development of novel therapeutic agents against Trypanosomatid parasites. A 3D-QSAR pharmacophore hypothesis has been generated for a series of L. major pteridine reductase inhibitors using Catalyst/HypoGen algorithm for identification of the chemical features that are responsible for the inhibitory activity. Four pharmacophore features, namely: two H-bond donors (D), one Hydrophobic aromatic (H) and one Ring aromatic (R) have been identified as key features involved in inhibitor-PTR1 interaction. These features are able to predict the activity of external test set of pteridine reductase inhibitors with a correlation coefficient (r) of 0.80. Based on the analysis of the best hypotheses, some potent Pteridine reductase inhibitors were screened out and predicted with anti-PTR1 activity. It turned out that the newly identified inhibitory molecules are at least 300 fold more potent than the current crop of existing inhibitors. Overall the current SAR study is an effort for elucidating quantitative structure-activity relationship for the PTR1 inhibitors. The results from the combined 3D-QSAR modeling and molecular docking approach have led to the prediction of new potent inhibitory scaffolds.     

Inhibitory mode of indole-2-carboxamide derivatives against HLGPa: molecular docking and 3D-QSAR analyses

The interaction of a series of indole-2-carboxamide compounds with human liver glycogen phosphorylase a (HLGPa) have been studied employing molecular docking and 3D-QSAR approaches. The Lamarckian Genetic Algorithm (LGA) of AutoDock 3.0 was employed to locate the binding orientations and conformations of the inhibitors interacting with HLGPa. The binding models were demonstrated in the aspects of inhibitor's conformation, subsite interaction, and hydrogen bonding. The very similar binding conformations of these inhibitors show that they interact with HLGPa in a very similar way. Good correlations between the calculated interaction free energies and experimental inhibitory activities suggest that the binding conformations of these inhibitors are reasonable. The structural and energetic differences in inhibitory potencies of indole-2-carboxamide compounds were reasonably explored. Using the binding conformations of indole-2-carboxamides, consistent and highly predictive 3D-QSAR models were developed by CoMFA and CoMSIA analyses. The q2 values are 0.697 and 0.622 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by four compounds that were not included in the training set. Mapping these models back to the topology of the active site of HLGPa leads to a better understanding of the vital indole-2-carboxamide-HLGPa interactions. Structure-based investigations and the final 3D-QSAR results provide clear guidelines and accurate activity predictions for novel inhibitor design.     

3D-QSAR studies of checkpoint kinase 1 inhibitors based on molecular docking and CoMFA

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q ² value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r ² value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r ² value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis.     

Molecular docking and 3D-QSAR studies on the binding mechanism of statine-based peptidomimetics with beta-secretase

beta-Secretase is an important protease in the pathogenesis of Alzheimer's disease. Some statine-based peptidomimetics show inhibitory activities to the beta-secretase. To explore the inhibitory mechanism, molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies on these analogues were performed. The Lamarckian Genetic Algorithm (LGA) was applied to locate the binding orientations and conformations of the peptidomimetics with the beta-secretase. A good correlation between the calculated binding free energies and the experimental inhibitory activities suggests that the identified binding conformations of these potential inhibitors are reliable. Based on the binding conformations, highly predictive 3D-QSAR models were developed with q(2) values of 0.582 and 0.622 for CoMFA and CoMSIA, respectively. The predictive abilities of these models were validated by some compounds that were not included in the training set. Furthermore, the 3D-QSAR models were mapped back to the binding site of the beta-secretase, to get a better understanding of vital interactions between the statine-based peptidomimetics and the protease. Both the CoMFA and the CoMSIA field distributions are in well agreement with the structural characteristics of the binding groove of the beta-secretase. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction would be useful in developing new drug leads against Alzheimer's disease.     

Probing the structural requirements of A-type Aurora kinase inhibitors using 3D-QSAR and molecular docking analysis

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 _cv² value of 0.404-0.582 and their predictive ability was validated using an independent test set, ending in r _pred² 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.     

3D-QSAR analysis of sialyltransferase inhibitors

A predictive 3D-QSAR model that correlates the biological activities with the chemical structures of a series of sialyltransferase inhibitors, exemplified by the sugar:nucleotide derivatives, was developed by means of comparative molecular field analysis (CoMFA). The resulting cross-validated value (q(2)=0.629), non-cross-validated value (r(2)=0.965) and standard error of estimate (SEE=0.288) indicate that the obtained pharmacophore model indeed mimics the steric and electrostatic environment where inhibitors bind to the enzyme. The developed model also possesses promising predictive ability as discerned by the testing on the external test set, and should be useful to further understand the molecular nature of inhibitor-enzyme interactions and to aid in the design of more potent sialyltransferase 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.     

Pharmacophore modeling, virtual screening and 3D-QSAR studies of 5-tetrahydroquinolinylidine aminoguanidine derivatives as sodium hydrogen exchanger inhibitors

Sodium hydrogen exchanger (SHE) inhibitor is one of the most important targets in treatment of myocardial ischemia. In the course of our research into new types of non-acylguanidine, SHE inhibitory activities of 5-tetrahydroquinolinylidine aminoguanidine derivatives were used to build pharmacophore and 3D-QSAR models. Genetic Algorithm Similarity Program (GASP) was used to derive a 3D pharmacophore model which was used in effective alignment of data set. Eight molecules were selected on the basis of structure diversity to build 10 different pharmacophore models. Model 1 was considered as the best model as it has highest fitness score compared to other nine models. The obtained model contained two acceptor sites, two donor atoms and one hydrophobic region. Pharmacophore modeling was followed by substructure searching and virtual screening. The best CoMFA model, representing steric and electrostatic fields, obtained for 30 training set molecules was statistically significant with cross-validated coefficient (q(2)) of 0.673 and conventional coefficient (r(2)) of 0.988. In addition to steric and electrostatic fields observed in CoMFA, CoMSIA also represents hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. CoMSIA model was also significant with cross-validated coefficient (q(2)) and conventional coefficient (r(2)) of 0.636 and 0.986, respectively. Both models were validated by an external test set of eight compounds and gave satisfactory prediction (r(pred)(2)) of 0.772 and 0.701 for CoMFA and CoMSIA models, respectively. This pharmacophore based 3D-QSAR approach provides significant insights that can be used to design novel, potent and selective SHE inhibitors.     

The Human Red Cell Voltage-regulated Cation Channel. The Interplay with the Chloride Conductance,the Ca<Superscript>2+</Superscript>-activated K<Superscript>+</Superscript> Channel and the Ca<Superscript>2+</Superscript> Pump

Electrocytes from the electric organ of Electrophorus electricus exhibited sodium action potentials that have been proposed to be repolarized by leak currents and not by outward voltage-gated potassium currents. However, patch-clamp recordings have suggested that electrocytes may contain a very low density of voltage-gated K⁺ channels. We report here the cloning of a K⁺ channel from an eel electric organ cDNA library, which, when expressed in mammalian tissue culture cells, displayed delayed-rectifier K⁺ channel characteristics. The amino-acid sequence of the eel K⁺ channel had the highest identity to Kv1.1 potassium channels. However, different important functional regions of eel Kv1.1 had higher amino-acid identity to other Kv1 members, for example, the eel Kv1.1 S4-S5 region was identical to Kv1.5 and Kv1.6. Northern blot analysis indicated that eel Kv1.1 mRNA was expressed at appreciable levels in the electric organ but it was not detected in eel brain, muscle, or cardiac tissue. Because electrocytes do not express robust outward voltage-gated potassium currents we speculate that eel Kv1.1 channels are chronically inhibited in the electric organ and may be functionally recruited by an unknown mechanism.