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.     

Construction of a three-dimensional pharmacophore for Bcl-2 inhibitors by flexible docking and the multiple copy simultaneous search method

B-Cell lymphoma-2 (Bcl-2) protein is a new promising target for anticancer drugs. A number of anticancer Bcl-2 inhibitors with diverse chemical structures have been discovered in recent years. In this paper, the flexible docking was performed to determine the binding modes of the representative inhibitors from different structural types. Subsequently, the binding modes of inhibitor were used to construct a primary three- dimensional (3D) pharmacophore model. It proved that this model can effectively disrupt the binding of the BH3 domain of proapoptotic Bcl-2 family members to Bcl-2, and match the structural requirement of a new type of Bcl-2 inhibitors. However, these distances between pharmacophoric points are not optimal due to the fact that not all of individual functional groups are located in the ideal position when inhibitors bind to its receptor. In this paper, we proposed a new idea to improve the quality of the pharmacophore model: the multiple copy simultaneous search (MCSS) method was performed to determine the energetically favorable distribution of functional groups with similar features to these pharmacophoric points in the active site of Bcl-2 first. Then their most energetically favorable minima in the positions near the pharmacophoric points were used to optimize the distances between pharmacophoric points. By examining the binding modes of several inhibitors from the same structural type, it was found that the more potent the inhibitor was, the closer it was to the optimized distances between pharmacophoric points. The optimized 3D pharmacophore model obtained in this paper may provide a good starting point for further rational design of Bcl-2 inhibitors.     

Insight into the structural requirements of thiophene-3-carbonitriles-based MurF inhibitors by 3D-QSAR,molecular docking and molecular dynamics study

The discovery of clinically relevant inhibitors against MurF enzyme has proven to be a challenging task. In order to get further insight into the structural features required for the MurF inhibitory activity, we performed pharmacophore and atom-based three-dimensional quantitative structure–activity relationship studies for novel thiophene-3-carbonitriles based MurF inhibitors. The five-feature pharmacophore model was generated using 48 inhibitors having IC₅₀ values ranging from 0.18 to 663?μm. The best-fitted model showed a higher coefficient of determination (R²?=?0.978), cross-validation coefficient (Q²?=?0.8835) and Pearson coefficient (0.9406) at four component partial least-squares factor. The model was validated with external data set and enrichment study. The effectiveness of the docking protocol was validated by docking the co-crystallized ligand into the catalytic pocket of MurF enzyme. Further, binding free energy calculated by the molecular mechanics generalized Born surface area approach showed that van der Waals and non-polar solvation energy terms are the main contributors to ligand binding in the active site of MurF enzyme. A 10-ns molecular dynamic simulation was performed to confirm the stability of the 3ZM6-ligand complex. Four new molecules are also designed as potent MurF inhibitors. These results provide insights regarding the development of novel MurF inhibitors with better binding affinity.     

QSAR studies and pharmacophore identification for arylsubstituted cycloalkenecarboxylic acid methyl esters with affinity for the human dopamine transporter

Data from a series of 29 monoamine transport inhibitors were used to generate 2D and 3D QSAR models for their binding affinity to the human dopamine transporter (hDAT). Among the inhibitors were many non-nitrogen containing compounds. The 2D QSAR analysis resulted in the equation -logK(i)=4.00-3.93E(LUMO)-0.67E(HOMO)-3.24sigma(p), which predicted the importance of electron withdrawing groups in the aromatic moiety. However, the model failed to predict the observed poor binding of nitro-substituted compounds. In contrast, a derived 3D QSAR model was capable of predicting these more correctly.     

QSAR studies for the inhibition of the transmembrane isozymes XII and XIV of human carbonic anhydrase with a series of sulfonamides

A diverse series of aromatic/heterocyclic sulfonamides possessing inhibitory action against the human transmembrane isoforms XII (cancer-associated) and XIV of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1) has been used to develop QSAR models. Including all the 55 investigated sulfonamides in the calibration set, the predictive qualities of the QSAR equations were weak (r(2)=0.1771, F=5.70) for CA XII and good for CA XIV inhibition (r(2)=0.8222, F=57.04 before eliminating the outliers, and r(2)=0.8911, F=67.07 after eliminating them). The obtained models suggest a slightly different inhibition mechanism for the two isoforms. 3-Halogeno-4-amino-benzenesulfonamides were outliers for scaffold hopping for the inhibition of CA XIV. CA XIV inhibitory activity was proportional to the degree of molecular surface rugosity. For compounds of the type X-Ar-SO(2)NH(2) and Ar'-Ar-SO(2)NH(2) type, best inhibitors were detected when Ar/Ar' incorporates a heterocyclic moiety. These studies may be helpful for the design of more specific CA XII/XIV inhibitors, since this is the first QSAR model investigating them.     

3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.     

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using ‘Receptor-Ligand Pharmacophore Generation’ method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r² of 0.996; for the test set, the correlation coefficient r² was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.     

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.     

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r?=?0.96) and Fisher’s randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski’s rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.     

Quantitative structure-activity relationship analysis of a series of 2,3-diaryl benzopyran analogues as novel selective cyclooxygenase-2 inhibitors

A series of recently synthesized 2,3-diaryl benzopyrans reported as novel selective cycloxygenase-2 inhibitors was subjected to quantitative structure-activity relationship (QSAR) analysis. Our attempt in correlating the derived physicochemical properties with the COX-2 inhibitory activity resulted in some statistically significant QSAR models with good predictive ability. The QSAR results and the probable pharmacophore features investigated through our study explored some interesting findings for the design of potent new class of selective COX-2 inhibitors.     

In silico modelling and molecular dynamics simulation studies of thiazolidine based PTP1B inhibitors

Protein tyrosine phosphatase 1B (PTP1B) has been identified as a negative regulator of insulin and leptin signalling pathway; hence, it can be considered as a new therapeutic target of intervention for the treatment of type 2 diabetes. Inhibition of this molecular target takes care of both diabetes and obesity, i.e. diabestiy. In order to get more information on identification and optimization of lead, pharmacophore modelling, atom-based 3D QSAR, docking and molecular dynamics studies were carried out on a set of ligands containing thiazolidine scaffold. A six-point pharmacophore model consisting of three hydrogen bond acceptor (A), one negative ionic (N) and two aromatic rings (R) with discrete geometries as pharmacophoric features were developed for a predictive 3D QSAR model. The probable binding conformation of the ligands within the active site was studied through molecular docking. The molecular interactions and the structural features responsible for PTP1B inhibition and selectivity were further supplemented by molecular dynamics simulation study for a time scale of 30 ns. The present investigation has identified some of the indispensible structural features of thiazolidine analogues which can further be explored to optimize PTP1B inhibitors.     

2D Quantitative structure-activity relationship studies on a series of cholesteryl ester transfer protein inhibitors

Coronary heart disease (CHD) is one of the major causes of human death. The most successful therapeutic approach available is based on the reduction of low density-lipoprotein cholesterol (LDL-C). However, it is believed that the next paradigm in CHD treatment will rely on increased HDL-C levels. One of the most promising strategies for this goal is the inhibition of cholesteryl ester transfer protein (CETP). In the present work, robust classical 2D QSAR (r(2)=0.76, q(2)=0.72) and hologram QSAR (r(2)=0.88, q(2)=0.70) models were developed for a series of 85 CETP inhibitors (N-N-disubstituted trifluoro-3-amino-2-propanol derivatives). These models are complementary in nature and highlight important structural features for the design of novel CETP inhibitors with improved potency.