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.     

Atom-based 3D-QSAR,induced fit docking,and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5

Atom-based three dimensional-quantitative structure–activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R²?=?0.84, SD?=?0.26, F?=?45.8, N?=?29) and test set (Q²?=?0.74, RMSE?=?0.235, Pearson-R?=?0.94, N?=?9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100?ns were performed to depict the protein–ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).     

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.     

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     

Pharmacophore mapping of a series of pyrrolopyrimidines,indolopyrimidines and their congeners as multidrug-resistance-associated protein (MRP1) modulators

Pharmacophore mapping studies were undertaken for a series of molecules belonging to pyrrolopyrimidines, indolopyrimidines and their congeners as multidrug resistance-associated protein (MRP1) modulators. A five-point pharmacophore with two hydrogen bond acceptors (A), one lipophilic/hydrophobic group (H), one positive ionic feature (P) and one aromatic ring (R) as pharmacophoric features was developed. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of r ² = 0.799 for training set molecules. The model generated showed excellent predictive power, with a correlation coefficient Q ² = 0.679 for an external test set of 20 molecules. The pharmacophore was further validated using four structurally diverse compounds with MRP1 modulatory activity. These compounds mapped well onto four of the five features of the pharmacophore. The pharmacophore proposed here was then utilised for the successful retrieval of active molecules with diverse chemotypes from database search. The geometry and features of pharmacophore are expected to be useful for the design of selective MRP1 inhibitors. Figure Alignment of multidrug resistance-associated protein (MRP1) inhibitors with the developed pharmacophore. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

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.     

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 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.     

Pharmacophore based 3D-QSAR modeling and free energy analysis of VEGFR-2 inhibitors

VEGFR-2, a transmembrane tyrosine kinase receptor is responsible for angiogenesis and has been an attractive target in treating cancers. The inhibition mechanism of structurally diverse urea derivatives, reported as VEGFR-2 inhibitors, was explored by pharmacophore modeling, QSAR, and molecular dynamics based free energy analysis.The pharmacophore hypothesis AADRR, resulted in a highly significant atom based 3D-QSAR model (r² = 0.94 and q² = 0.84). Binding free energy analysis of the docked complexes of highly active and inactive compounds, after 7 ns MD simulation, revealed the importance of van der Waals interaction in VEGFR-2 inhibition. The decomposition of binding free energy on a per residue basis disclosed that the residues in hinge region and hydrophobic pocket play a role in discriminating the active and inactive inhibitors. Thus, the present study proposes a pharmacophore hypothesis representing the identified interactions pattern and its further application as a template in screening databases to identify novel VEGFR-2 inhibitor scaffolds.     

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     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

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 and 3D-QSAR analysis of phosphoinositide 3-kinase p110α inhibitors

Pharmacophore modeling studies were undertaken for a series of compounds belonging several groups of phosphoinositide 3-kinase (PI3K) p110α inhibitors: 4-morpholino-2-phenylquinazolines derivatives, pyrido[3′,2′:4,5]furo-[3,2-d]pyrimidine derivatives, imidazo[1,2-a]pyridine derivatives, sulfonylhydrazone substituted imidazo[1,2-a]pyridines, and LY294002. A five-point pharmacophore with three hydrogen bond acceptors (A), one hydrophobic group (H), and one aromatic ring (R) as pharmacophore features was developed. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of R ² = 0.95 for training set compounds. The model generated showed excellent predictive power, with a correlation coefficient of Q ² = 0.88 and r _pret² = 0.95 for a test set of 14 compounds. Furthermore, the structure–activity relationships of PI3K p110α inhibitors were elucidated and the activity differences between them discussed. Docking studies were also carried out wherein active and inactive compounds were docked into the active site of the PI3K p110α crystal structure to analyze PI3K p110α–inhibitor interactions. The results provide insights that will aid optimization of these classes of PI3K p110α inhibitors for better activity, and may prove helpful for further lead optimization and virtual screening.     

Deciphering the crucial molecular properties of a series of Benzothiazole Hydrazone inhibitors that targets anti-apoptotic Bcl-xL protein

The Bcl-2 family proteins are the central regulators of apoptosis. Due to its predominant role in cancer progression, the Bcl-2 family proteins act as attractive therapeutic targets. Recently, molecular series of Benzothiazole Hydrazone (BH) inhibitors that exhibits drug-likeness characteristics, which selectively targets Bcl-xL have been reported. In the present study, docking was used to explore the plausible binding mode of the highly active BH inhibitor with Bcl-xL; and Molecular Dynamics (MD) simulation was applied to investigate the stability of predicted conformation over time. Furthermore, the molecular properties of the series of BH inhibitors were extensively investigated by pharmacophore based 3D-QSAR model. The docking correctly predicted the binding mode of the inhibitor inside the Bcl-xL hydrophobic groove, whereas the MD-based free energy calculation exhibited the binding strength of the complex over the time period. Furthermore, the residue decomposition analysis revealed the major energy contributing residues – F105, L108, L130, N136, and R139 – involved in complex stability. Additionally, a six-featured pharmacophore model – AAADHR.89 – was developed using the series of BH inhibitors that exhibited high survival score. The statistically significant 3D-QSAR model exhibited high correlation co-efficient (R² = .9666) and cross validation co-efficient (Q² = .9015) values obtained from PLS regression analysis. The results obtained from the current investigation might provide valuable insights for rational drug design of Bcl-xL inhibitor synthesis.     

Heterozygous loss of epilepsy gene KCNQ2 alters social,repetitive and exploratory behaviors

KCNQ/K_v7 channels conduct voltage‐dependent outward potassium currents that potently decrease neuronal excitability. Heterozygous inherited mutations in their principle subunits K_v7.2/KCNQ2 and K_v7.3/KCNQ3 cause benign familial neonatal epilepsy whereas patients with de novo heterozygous K_v7.2 mutations are associated with early‐onset epileptic encephalopathy and neurodevelopmental disorders characterized by intellectual disability, developmental delay and autism. However, the role of K_v7.2‐containing K_v7 channels in behaviors especially autism‐associated behaviors has not been described. Because pathogenic K_v7.2 mutations in patients are typically heterozygous loss‐of‐function mutations, we investigated the contributions of K_v7.2 to exploratory, social, repetitive and compulsive‐like behaviors by behavioral phenotyping of both male and female KCNQ2^+/? mice that were heterozygous null for the KCNQ2 gene. Compared with their wild‐type littermates, male and female KCNQ2^+/? mice displayed increased locomotor activity in their home cage during the light phase but not the dark phase and showed no difference in motor coordination, suggesting hyperactivity during the inactive light phase. In the dark phase, KCNQ2^+/? group showed enhanced exploratory behaviors, and repetitive grooming but decreased sociability with sex differences in the degree of these behaviors. While male KCNQ2^+/? mice displayed enhanced compulsive‐like behavior and social dominance, female KCNQ2^+/? mice did not. In addition to elevated seizure susceptibility, our findings together indicate that heterozygous loss of K_v7.2 induces behavioral abnormalities including autism‐associated behaviors such as reduced sociability and enhanced repetitive behaviors. Therefore, our study is the first to provide a tangible link between loss‐of‐function K_v7.2 mutations and the behavioral comorbidities of K_v7.2‐associated epilepsy.