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.     

Structural insights of JAK2 inhibitors: pharmacophore modeling and ligand-based 3D-QSAR studies of pyrido-indole derivatives

Abstract

In this study we have performed pharmacophore modeling and built a 3D QSAR model for pyrido-indole derivatives as Janus Kinase 2 inhibitors. An efficient pharmacophore has been identified from a data set of 51 molecules and the identified pharmacophore hypothesis consisted of one hydrogen bond acceptor, two hydrogen bond donors and three aromatic rings, i.e. ADDRRR. A powerful 3D-QSAR model has also been constructed by employing Partial Least Square regression analysis with a regression coefficient of 0.97 (R²) and Q² of 0.95, and Pearson-R of 0.98.     

Pharmacophore modeling,comprehensive 3D-QSAR,and binding mode analysis of TGR5 agonists

Takeda G-protein-coupled receptor 5 (TGR5) is emerging as an important and promising target for the development of anti-diabetic drugs. Pharmacophore modeling and atom-based 3D-QSAR studies were carried out on a new series of 5-phenoxy-1,3-dimethyl-1H-pyrazole-4-carboxamides as highly potent agonists of TGR5. The generated best six featured pharmacophore model AAHHRR consists of two hydrogen bond acceptors (A): two hydrophobic groups (H) and two aromatic rings (R). The constructed 3D-QSAR model acquired excellent correlation coefficient value (R^2?=^?0.9018), exhibited good predictive power (Q^2?=^?0.8494) and high Fisher ratio (F?=?61.2). The pharmacophore model was validated through Guner–Henry (GH) scoring method. The GH value of 0.5743 indicated that the AAHHRR model was statistically valuable and reliable in the identification of TGR5 agonists. Furthermore, the combined approach of molecular docking and binding free energy calculations were carried out for the 5-phenoxy-1,3-dimethyl-1H-pyrazole-4-carboxamides to explore the binding mode and interaction pattern. The generated contour maps revealed the important structural insights for the activity of the compounds. The results obtained from this study could be helpful in the development of novel and more potent agonists of TGR5.     

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.     

In silico studies on potential MCF-7 inhibitors: a combination of pharmacophore and 3D-QSAR modeling,virtual screening,molecular docking,and pharmacokinetic analysis

Gallic acid and its derivatives exhibit a diverse range of biological applications, including anti-cancer activity. In this work, a data-set of forty-six molecules containing the galloyl moiety, and known to show anticarcinogenic activity against the MCF-7 human cancer cell line, have been chosen for pharmacophore modeling and 3D-Quantitative Structure Activity Relationship (3D-QSAR) studies. A tree-based partitioning algorithm has been used to find common pharmacophore hypotheses. The QSAR model was generated for three, four, and five featured hypotheses with increasing PLS factors and analyzed. Results for five featured hypotheses with three acceptors and two aromatic rings were the best out of all the possible combinations. On analyzing the results, the most robust (R^2?=?.8990) hypothesis with a good predictive power (Q^2?=?.7049) was found to be AAARR.35. A good external validation (R² = .6109) was also obtained. In order to design new MCF-7 inhibitors, the QSAR model was further utilized in pharmacophore-based virtual screening of a large database. The predicted IC₅₀ values of the identified potential MCF-7 inhibitors were found to lie in the micromolar range. Molecular docking into the colchicine domain of tubulin was performed in order to examine one of the probable mechanisms. This revealed various interactions between the ligand and the active site protein residues. The present study is expected to provide an effective guide for methodical development of potent MCF-7 inhibitors.     

Pharmacophore modeling, 3D-QSAR,and in silico ADME prediction of N-pyridyl and pyrimidine benzamides as potent antiepileptic agents

Biological mechanism attributing mutations in KCNQ2/Q3 results in benign familial neonatal epilepsy (BFNE), a rare form of epilepsy and thus neglected. It offers a potential target for antiepileptic drug discovery. In the present work, a pharmacophore-based 3D-QSAR model was generated for a series of N-pyridyl and pyrimidine benzamides possessing KCNQ2/Q3 opening activity. The pharmacophore model generated contains one hydrogen bond donor (D), one hydrophobic (H), and two aromatic rings (R). They are the crucial molecular write-up detailing predicted binding efficacy of high affinity and low affinity ligands for KCNQ2/Q3 opening activity. Furthermore, it has been validated by using a biological correlation between pharmacophore hypothesis-based 3D-QSAR variables and functional fingerprints of openers responsible for the receptor binding and also by docking of these benzamides into the validated homology model. Excellent statistical computational tools of QSAR model such as good correlation coefficient (R^2?>^?0.80), higher F value (F?>?39), and excellent predictive power (Q²?>?0.7) with low standard deviation (SD <0.3) strongly suggest that the developed model could be used for prediction of antiepileptic activity of newer analogs. A preliminary pharmacokinetic profile of these derivatives was also performed on the basis of QikProp predictions.     

A combination of pharmacophore modeling,atom-based 3D-QSAR,molecular docking and molecular dynamics simulation studies on PDE4 enzyme inhibitors

Phosphodiesterases 4 enzyme is an attractive target for the design of anti-inflammatory and bronchodilator agents. In the present study, pharmacophore and atom-based 3D-QSAR studies were carried out for pyrazolopyridine and quinoline derivatives using Schrödinger suite 2014-3. A four-point pharmacophore model was developed using 74 molecules having pIC₅₀ ranging from 10.1 to 4.5. The best four feature model consists of one hydrogen bond acceptor, two aromatic rings, and one hydrophobic group. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a high correlation coefficient (R^2?=?.9949), cross validation coefficient (Q^2?=?.7291), and Pearson-r (.9107) at six component partial least square factor. The external validation indicated that our QSAR model possessed high predictive power with R² value of .88. The generated model was further validated by enrichment studies using the decoy test. Molecular docking, free energy calculation, and molecular dynamics (MD) simulation studies have been performed to explore the putative binding modes of these ligands. A 10-ns MD simulation confirmed the docking results of both stability of the 1XMU–ligand complex and the presumed active conformation. Outcomes of the present study provide insight in designing novel molecules with better PDE4 inhibitory activity.     

Pharmacophore generation,atom-based 3D-QSAR,molecular docking and molecular dynamics simulation studies on benzamide analogues as FtsZ inhibitors

FtsZ is an appealing target for the design of antimicrobial agent that can be used to defeat the multidrug-resistant bacterial pathogens. Pharmacophore modelling, molecular docking and molecular dynamics (MD) simulation studies were performed on a series of three-substituted benzamide derivatives. In the present study a five-featured pharmacophore model with one hydrogen bond acceptors, one hydrogen bond donors, one hydrophobic and two aromatic rings was developed using 97 molecules having MIC values ranging from .07 to 957 μM. A statistically significant 3D-QSAR model was obtained using this pharmacophore hypothesis with a good correlation coefficient (R² = .8319), cross validated coefficient (Q² = .6213) and a high Fisher ratio (F = 103.9) with three component PLS factor. A good correlation between experimental and predicted activity of the training (R² = .83) and test set (R² = .67) molecules were displayed by ADHRR.1682 model. The generated model was further validated by enrichment studies using the decoy test and MAE-based criteria to measure the efficiency of the model. The docking studies of all selected inhibitors in the active site of FtsZ protein showed crucial hydrogen bond interactions with Val 207, Asn 263, Leu 209, Gly 205 and Asn-299 residues. The binding free energies of these inhibitors were calculated by the molecular mechanics/generalized born surface area VSGB 2.0 method. Finally, a 15 ns MD simulation was done to confirm the stability of the 4DXD–ligand complex. On a wider scope, the prospect of present work provides insight in designing molecules with better selective FtsZ inhibitory potential.     

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.     

Reliable structural information for rational design of benzoxazole type potential cholesteryl ester transfer protein (CETP) inhibitors through multiple validated modeling techniques

Abstract

The drug design and discovery of lipid modulators is very demanding as no new molecule has entered into the market in the last 35 years. Cholesteryl ester transfer protein (CETP) is a promising target as lipid modulators. Inhibition of the CETP enzyme reduces the risk of cardiovascular events. The first CETP inhibitor torcetrapib and related drug candidates failed in the clinical trial due to the off-target effects leading to high toxicity. Thus, newer CETP inhibitors have now paramount importance to accelerate the drug discovery efforts in the field of cardiovascular disease (CVD). In the present study, 140 benzoxazole compounds were studied by using different chemometric techniques, for example, pharmacophore mapping, molecular docking, three-dimensional quantitative structure–activity relationship comparative molecular field analysis (3D-QSAR CoMFA), topomer CoMFA and Bayesian classification, in order to generate complete and reliable information regarding the structural requirements for the CETP inhibition. The best pharmacophore hypothesis was statistically significant (regression coefficient of 0.957 and a lower root mean square of 0.890). Molecular docking study revealed that cyano-substituted compounds form hydrogen bond with targeted macromolecule. The 3D-QSAR CoMFA model also produced a leave-one-out (LOO) cross-validated Q² of 0.527, an R² of 0.853 and an R²_Pred of 0.603. Similarly, two topomer CoMFA models were also statistically significant and reliable in terms of their Q², R² and R²_Pred values. The Bayesian classification study also provided the excellent ROC values of 0.919 and 0.939 for training and test sets, respectively. Overall, this study may help in the rational design of newer benzoxazole type compounds with higher CETP inhibition.

Communicated by Ramaswamy H. Sarma     

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.     

Design and development of topoisomerase inhibitors using molecular modelling studies

Topoisomerase inhibitors are used as anticancer and antibacterial agents. A series of novel 2,4,6-tri-substituted pyridine derivatives reported as topoisomerase inhibitors were used for quantitative structure–activity relationship (QSAR) study. In order to understand the structural requirement of these topoisomerase inhibitors, a ligand-based pharmacophore and atom-based 3D-QSAR model have been developed. A five-point pharmacophore with one hydrophobic group (H4), four aromatic rings (R5, R6, R7 and R8) was obtained. The pharmacophore hypothesis yielded a 3D-QSAR model with good partial least-square (PLS) statistic results. The training set correlation is characterized by PLS factors (r² = 0.7892, SD = 0.2948, F = 49.9, P = 1.379). The test set correlation is characterized by PLS factors (q² = 0.7776, root mean squared error = 0.2764, Pearson R = 0.8926). The docking study revealed the binding orientations of these inhibitors at active site amino acid residues of topoisomerases enzyme. The results of pharmacophore hypothesis and 3D-QSAR provided the detail structural insights as well as highlighted the important binding features of novel 2,4,6-tri-substituted pyridine derivatives and can be developed as potent topoisomerase inhibitors.

Figure

Open in a separate windowKey structural requirement for topoisomerase activity     

The synthesis of 4-arylamido-2-arylaminoprimidines as potent EGFR T790M/L858R inhibitors for NSCLC

A series of 4-arylamido-2-arylaminoprimidines bearing acrylamide pharmacophore were synthesized as potent EGFR^T790M/L858R inhibitors among which 9c (IC₅₀?=?0.5872?nM), 9d (IC₅₀?=?2.213?nM), or 9h (IC₅₀?=?12.57?nM) showed more potent anti-EGFR^T790M/L858R activity compared with AZD–9291 (IC₅₀?=?20.80?nM) and possessed high SI displaying 307.6, 56.5, or 12.5 for EGFR^T790M/L858R over the wild-type respectively. 9h also showed pretty good activity against H 1975 cells with an IC₅₀ of 1.664?μM and exhibited low toxicity against the normal HBE cells (IC₅₀?>?20?μΜ). 9h had moderate selectivity for H 1975 over A 431 (SI?=?7.0) and the other selected cell lines. Morphological staining results further indicated that 9h could promote apoptosis. Hence, 9h was a promising compound for further investigation as a potential EGFR^T790M/L858R inhibitor for the treatment of NSCLC.     

Unraveling the molecular mechanism of benzothiophene and benzofuran scaffold-merged compounds binding to anti-apoptotic Myeloid cell leukemia 1

Myeloid cell leukemia 1 (Mcl1), is an antiapoptotic member of the Bcl-2 family proteins, has gained considerable importance due to its overexpression activity prevents the oncogenic cells to undergo apoptosis. This overexpression activity of Mcl1 eventually develops strong resistance to a wide variety of anticancer agents. Therefore, designing novel inhibitors with potentials to elicit higher binding affinity and specificity to inhibit Mcl1 activity is of greater importance. Thus, Mcl1 acts as an attractive cancer target. Despite recent experimental advancement in the identification and characterization of benzothiophene and benzofuran scaffold-merged compounds, the molecular mechanisms of their binding to Mcl1 are yet to be explored. The current study demonstrates an integrated approach – pharmacophore-based 3D-QSAR, docking, molecular dynamics (MD) simulation and free-energy estimation – to access the precise and comprehensive effects of current inhibitors targeting Mcl1 together with its known activity values. The pharmacophore – ANRRR.240 – based 3D-QSAR model from the current study provided high confidence (R²=0.9154, Q²=0.8736 and RMSE?=?0.3533) values. Furthermore, the docking correctly predicted the binding mode of highly active compound 42. Additionally, the MD simulation for docked complex under explicit-solvent conditions together with free-energy estimation exhibited stable interaction and binding strength over the time period. Also, the decomposition analysis revealed potential energy contributing residues – M231, M250, V253, R265, L267 and F270 – to the complex stability. Overall, the current investigation might serve as a valuable insight, either to (i) improve the binding affinity of the current compounds or (ii) discover new generation anticancer agents that can effectively downregulate Mcl1 activity.

Communicated by Ramaswamy H. Sarma     

Potential CD34 signaling through phosphorylated-BAD in chemotherapy-resistant acute myeloid leukemia

Abstract

Acute myeloid leukemia (AML) constitutively express growth factors and cytokines for survival. Chemotherapy alters these signals to induce cell death. However, drug resistance in AML remains a major hindrance to successful treatment and early warning is unavailable. Modulation of signaling pathways during chemotherapy may provide a window to detect response and predict treatment outcome. Blood samples collected from AML patients before and at day-3 of induction therapy were compared for changes in expression of CD117, CD34, pro-inflammatory cytokines and mediators of Akt and MAPK pathways, using multi-color flow cytometry. Nine patients were diagnosed as drug-resistant and seven sensitive to chemotherapy. Twelve were paired. Average percentages of CD34 (66.8?±?11.7% vs. 26.2?±?5.8%, p?=?0.033) and pBAD (66.9?±?8.2% vs. 28.9?±?8.2%, p?=?0.016) were significantly increased in chemo-resistant (N?=?9) compared to chemo-sensitive (N?=?5) samples. Percentages of CD34 were strongly correlated with pBAD (R?=?0.785; p?=?0.001; N?=?14) and pFKHR (R?=?0.755; p?=?0.002; N?=?14) at day-3 induction. Chemo-sensitive cases expressed significantly higher percentages of IL-18Rα (71.9?±?9.6% vs. 29.8?±?5.8%, p?=?0.016). Though not significantly different in the outcome, IL-1β was strongly associated with activated Akt-S473, IL-6 with phosphorylated JNK and FKHR while TNF-α appeared to trigger Bim, in treated samples. These preliminary results suggested AML cells resistant to chemotherapy increased expression of CD34 and may signal through pBAD while cells sensitive to chemotherapy-induced IL18Rα expression. These were observed early during induction therapy. Identifying CD34 is interesting as it is a convenient marker to monitor drug-resistance in AML patients. Inhibition of CD34 and pBAD signaling may be important in treating drug-resistant AML.     

Identification of novel urease inhibitors: pharmacophore modeling,virtual screening and molecular docking studies

Abstract

Pharmacophore modeling and atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) have been developed on N-acylglycino- and hippurohydroxamic acid derivatives, which are known potential inhibitors of urease. This is followed by virtual screening and ADMET (absorption, distribution, metabolism, excretion and toxicity) studies on a large library of known drugs in order to get lead molecules as Helicobacter pylori urease inhibitors. A suitable three-featured pharmacophore model comprising one H-bond acceptor and two H-bond donor features (ADD.10) has been found to be the best QSAR model. An external library of compounds (～3000 molecules), pre-filtered using Lipinski’s rule of five, has been further screened using the pharmacophore model ADD.10. By analyzing the fitness of the hits with respect to the pharmacophore model and their binding interaction inside the urease active site, four molecules have been predicted to be extremely good urease inhibitors. Two of these have significant potential and should be taken up for further drug-designing process.     

In silico studies on p21-activated kinase 4 inhibitors: comprehensive application of 3D-QSAR analysis,molecular docking,molecular dynamics simulations,and MM-GBSA calculation

Abstract

P21-activated kinase 4 (PAK4) is a serine/threonine protein kinase, which is associated with many cancer diseases, and thus being considered as a potential drug target. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations were performed to explore the structure-activity relationship of a series of pyrropyrazole PAK4 inhibitors. The statistical parameters of comparative molecular field analysis (CoMFA, Q ² = 0.837, R ² = 0.990, and R ² _pred = 0.967) and comparative molecular similarity indices analysis (CoMSIA, Q ² = 0.720, R ² = 0.972, and R ² _pred = 0.946) were obtained from 3D-QSAR model, which exhibited good predictive ability and significant statistical reliability. The binding mode of PAK4 with its inhibitors was obtained through molecular docking study, which indicated that the residues of GLU396, LEU398, LYS350, and ASP458 were important for activity. Molecular mechanics generalized born surface area (MM-GBSA) method was performed to calculate the binding free energy, which indicated that the coulomb, lipophilic and van der Waals (vdW) interactions made major contributions to the binding affinity. Furthermore, through 100?ns MD simulations, we obtained the key amino acid residues and the types of interactions they participated in. Based on the constructed 3D-QSAR model, some novel pyrropyrazole derivatives targeting PAK4 were designed with improved predicted activities. Pharmacokinetic and toxicity predictions of the designed PAK4 inhibitors were obtained by the pkCSM, indicating these compounds had better absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. Above research provided a valuable insight for developing novel and effective pyrropyrazole compounds targeting PAK4.     

Circulating fatty acids as biomarkers of dairy fat intake: data from the lifelines biobank and cohort study

Background: C14:0, C15:0, C17:0 and trans-C16:1(n-7) are often used as biomarkers for dairy fat intake. Trans-C18:1(n-7) and CLA, two fatty acids which are also present in dairy, have hardly been explored. We investigated whether trans-C18:1(n-7) and CLA can enrich the existing biomarker portfolio.

Methods: Data were obtained from Lifelines (n?=?769). Dairy fat intake was determined by FFQ. Fatty acids were measured in fasting plasma triglycerides (TG), phospholipids (PL) and cholesterol esters (CE).

Results: Median (25th–75th percentile) intakes of dairy and dairy fat were 322(209–447) and 12.3(8.4–17.4) g/d respectively. A pilot study showed that trans-C18:1(n-7) and CLA were only detectable in TG and PL. Of the established markers, TG C15:0 was most strongly associated with dairy fat intake (standardized β (std.β)?=?0.286, R²?=?0.111). Of the less established markers, TG trans-C18:1(n-7) was most strongly associated with dairy fat intake (Std.β?=?0.292, R²?=?0.115), followed by PL CLA (Std.β?=?0.272, R²?=?0.103) and PL trans-C18:1(n-7) (Std.β?=?0.269, R²?=?0.099). In TG, a combination of C15:0 and trans-C18:1(n-7) performed best (R²?=?0.128). In PL, a combination of C14:0, C15:0, trans-C18:1(n-7) and CLA performed best (R²?=?0.143).

Conclusion: Trans-C18:1(n-7) and CLA can be used as biomarkers of dairy fat intake. Additionally, combining established with less established markers allowed even stronger predictions for dairy fat intake.