Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor

To study the pharmacophore properties of quinazolinone derivatives as 5HT₇ inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT₇ inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q² (cross validated correlation coefficient) of 0.642, 0.602 and r² (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT₇ antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r² obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.     

Screening from TCM Database@Taiwan and QSAR model for identifying HER2 inhibitors

Human epidermal growth factor receptor type 2 (HER2) overexpression, which has been reported to increase the malignancy of human ovarian cancer cells and the metastatic potential of human breast cancer cells, is an important factor in tumour formation and tumour growth. However, currently available HER2 inhibitors, such as Lapatinib, for cancer therapy cause adverse side effects including diarrhoea, rash and possible liver toxicity. We hoped to find novel agents that cause less adverse side effects by performing virtual screening process on the world's largest traditional Chinese medicine compound database. The results thus obtained were then validated using 3D quantitative structure–activity relationship model. Top three candidates were selected from the docking results. The top three candidates and the control both formed a hydrogen bond with the key residue, Lys724. This showed that the candidates and the control have similar binding effects to HER2. These candidates were investigated using comparative molecular field analysis and comparative molecular similarity indices analysis models. The results from these models showed high correlation coefficients (r ²) of 0.9547 and 0.9226, respectively. All top three candidates had high docking scores, favourable pharmacophores and functional groups forming stable hydrogen bonds with HER2. These properties suggested stable binding affinities and favourable interaction with HER2. We concluded that these candidates may be further investigated as potential HER2 inhibitors.     

3D QSAR pharmacophore-based virtual screening for the identification of potential inhibitors of tyrosinase

Abstract

Tyrosinase plays an important role in melanin biosynthesis and protects skin against ultraviolet radiations. Functional deficiency of tyrosinase results in serious dermatological diseases. Tyrosinase also participates in neuromelanin formation in the human brain, which leads to neurodegeneration resulting in Parkinson’s disease. In fruits and vegetables, tyrosinase plays a critical role in senescence, causing undesired browning that results in faster deterioration and shorter shelf lines. The only commercially available tyrosinase is mushroom tyrosinase and it shows the highest homology to the mammalian tyrosinase. Although kojic acid is currently used as a tyrosinase inhibitor, they have serious side effects such as dermatitis, carcinogenesis and hepatotoxicity. Therefore, in order to develop a more active and safer tyrosinase inhibitor, 3D QSAR pharmacophore models were generated based on experimentally known inhibitors. The pharmacophore model, Hypo1, was developed with a large cost difference, high correlation coefficient and low RMS deviation. Hypo1 showed a good spatial arrangement; consisting of five-point features including two hydrogen bond acceptor, one hydrogen bond donor and two hydrophobic features. Hypo1 was further validated by cost analysis, test set and Fisher’s randomisation method. Hypo1 was used as a 3D query for screening the in-house drug-like databases, and the hits were further selected by applying ADMET, Lipinski’s rule of five and fit value criteria. To identify binding conformations, the obtained hits were subjected to molecular docking. Finally, molecular dynamics simulations revealed the appropriate binding modes of hit compounds. To conclude, we propose the final three hit compounds with new structural scaffolds as a virtual candidate as tyrosinase inhibitors.

Communicated by Ramaswamy H. Sarma     

Molecular docking, 3D-QSAR,molecular dynamics,synthesis and anticancer activity of tyrosine kinase 2 (TYK 2) inhibitors

Abstract

A therapeutic rationale is proposed by selectively targeting tyrosine kinase 2 (TYK 2) to obtain potent TYK 2 inhibitors by molecular modeling studies. In the present study, we have taken tyrosine kinase (TYK 2) inhibitors and carried out molecular docking, 3?D quantitative structure–activity relationship (3D-QSAR) analysis and molecular dynamics (MD). Based on the 3D-QSAR results thirteen new compounds (R-1 to R-13) were designed and synthesized in good yields. The synthesized molecules were evaluated for their in vitro anticancer activity against LnCap and A549 cell lines. The molecules R-1, R-3, R-5, R-7, and R-10 exhibited considerable anti cancer activity.     

3D-QSAR studies on fluroquinolones derivatives as inhibitors for tuberculosis

A quantitative structure activity relationship (QSAR) study was performed on the fluroquinolones known to have anti-tuberculosis activity. The 3D-QSAR models were generated using stepwise variable selection of the four methods - multiple regression (MR), partial least square regression (PLSR), principal component regression (PCR) and artificial neural networks (kNN-MFA). The statistical result showed a significant correlation coefficient q(2) (90%) for MR model and an external test set of (pred_r(2)) -1.7535, though the external predictivity showed to improve using kNN-MFA method with pred_r(2) of -0.4644. Contour maps showed that steric effects dominantly determine the binding affinities. The QSAR models may lead to a better understanding of the structural requirements of anti-tuberculosis compounds and also help in the design of novel molecules.     

In silico design of potent EGFR kinase inhibitors using combinatorial libraries

This paper is an attempt to design 4-anilinoquinazoline compounds having promising anticancer activities against epidermal growth factor (EGFR) kinase inhibition, using virtual combinatorial library approach. Partial least squares method has been applied for the development of a quantitative structure–activity relationship (QSAR) model based on training and test set approaches. The partial least squares model showed some interesting results in terms of internal and external predictability against EGFR kinase inhibition for such type of anilinoquinazoline derivatives. In virtual screening study, out of 4860 compounds in chemical library, 158 compounds were screened and finally, 10 compounds were selected as promising EGFR kinase inhibitors based on their predicted activities from the QSAR model. These derivatives were subjected to molecular docking study to investigate the mode of binding with the EGFR kinase, and the two compounds (ID 3639 and 3399) showing similar type of docking score and binding patterns with that of the existing drug molecules like erlotinib were finally reported.     

Design and bio-evaluation of indole derivatives as potent Kv1.5 inhibitors

Atrial fibrillation (AF) is one of the common arrhythmias that threaten human health. Kv1.5 potassium channel is reported as an efficacious and safe target for the treatment of AF. In this paper, we designed and synthesized three series of compounds through modifying the lead compound RH01617 that was screened out by the pharmacophore model we reported earlier. All of the compounds were evaluated by the whole-patch lamp technology and most of them possessed potent inhibitory activities against Kv1.5. Compounds IIIi and IIIl were evaluated for the target selectivity as well as the pharmacodynamic effects in an isolated rat model. Due to the promising pharmacological behavior, compound IIIl deserves further pharmacodynamic and pharmacokinetic evaluations.     

Pharmacophore mapping,molecular docking and QSAR studies of structurally diverse compounds as CYP2B6 inhibitors

Pharmacophore mapping, molecular docking and quantitative structure–activity relationship (QSAR) studies were carried out for a structurally diverse set of 48 compounds as CYP2B6 inhibitors. The generated best pharmacophore hypotheses from the three methods of conformer generation (FAST, BEST and conformer algorithm based on energy screening and recursive buildup) indicate the importance of two features, namely, hydrogen bond acceptor [electron-rich centre] and ring aromaticity. The distance between the two centres of the important features for ideal inhibitors varied from 5.82 to 6.03 Å. The chemometric tools used for the QSAR analysis were genetic function approximation (GFA) and genetic partial least squares. The developed QSAR models indicate the importance of an electron-rich centre, size of molecule, impact of branching and ring system and distribution of charges in the molecular surface. The docking study confirms the importance of an electron-rich centre for binding with the iron atom of the cytochrome enzyme. A GFA model with spline option was found to be the best model based on internal validation as well as the r ² _{m (overall)} criterion (Q ² = 0.772, r ² _{m (overall)} = 0.774). According to the external prediction statistics (R ² _pred = 0.876), another GFA-derived model with spline option outperforms the remaining models.     

Synthesis,crystal structure and biological evaluation of new phosphoramide derivatives as urease inhibitors using docking,QSAR and kinetic studies

In an attempt to achieve a new class of phosphoramide inhibitors with high potency and resistance to the hydrolysis process against urease enzyme, we synthesized a series of bisphosphoramide derivatives (01–43) and characterized them by various spectroscopic techniques. The crystal structures of compounds 22 and 26 were investigated using X-ray crystallography. The inhibitory activities of the compounds were evaluated against the jack bean urease and were compared to monophosphoramide derivatives and other known standard inhibitors. The compounds containing aromatic amines and their substituted derivatives exhibited very high inhibitory activity in the range of IC₅₀ = 3.4–1.91 × 10⁻¹⁰ nM compared with monophosphoramides, thiourea, and acetohydroxamic acid. It was also found that derivatives with PO functional groups have higher anti-urease activity than those with PS functional groups. Kinetics and docking studies were carried out to explore the binding mechanism that showed these compounds follow a mixed-type mechanism and, due to their extended structures, can cover the entire binding pocket of the enzyme, reducing the formation of the enzyme-substrate complex. The quantitative structure-activity relationship (QSAR) analysis also revealed that the interaction between the enzyme and inhibitor is significantly influenced by aromatic rings and PO functional groups. Collectively, the data obtained from experimental and theoretical studies indicated that these compounds can be developed as appropriate candidates for urease inhibitors in this field.     

Design,biological evaluation and 3D QSAR studies of novel dioxin-containing triaryl pyrazoline derivatives as potential B-Raf inhibitors

A series of novel dioxin-containing triaryl pyrazoline derivatives C1–C20 have been synthesized. Their B-Raf inhibitory and anti-proliferation activities were evaluated. Compound C6 displayed the most potent biological activity against B-Raf^V600E and WM266.4 human melanoma cell line with corresponding IC₅₀ value of 0.04 μM and GI₅₀ value of 0.87 μM, being comparable with the positive controls and more potent than our previous best compounds. Moreover, C6 was selective for B-Raf^V600E from B-Raf^WT, C-Raf and EGFR and low toxic. The docking simulation suggested the potent bioactivity might be caused by breaking the limit of previous binding pattern. A new 3D QSAR model was built with the activity data and binding conformations to conduct visualized SAR discussion as well as to introduce new directions. Stretching the backbone to outer space or totally reversing the backbone are both potential orientations for future researches.     

Production of new amilorides as potent inhibitors of mitochondrial respiratory complex I

Amilorides, well-known inhibitors of Na⁺/H⁺ antiporters, have also shown to inhibit bacterial and mitochondrial NADH-quinone oxidoreductase (complex I). Since the membrane subunits ND2, ND4, and ND5 of bovine mitochondrial complex I are homologous to Na⁺/H⁺ antiporters, amilorides have been thought to bind to any or all of the antiporter-like subunits; however, there is no direct experimental evidence in support of this notion. Photoaffinity labeling is a powerful technique to identify the binding site of amilorides in bovine complex I. Commercially available amilorides such as 5-(N-ethyl-N-isopropyl)amiloride are not suitable as design templates to synthesize photoreactive amilorides because of their low binding affinities to bovine complex I. Thereby, we attempted to modify the structures of commercially available amilorides in order to obtain more potent derivatives. We successfully produced two photoreactive amilorides (PRA1 and PRA2) with a photolabile azido group at opposite ends of the molecule.