Pharmacophore modeling, 3D-QSAR and docking study of 2-phenylpyrimidine analogues as selective PDE4B inhibitors

Discovery of polymethoxyflavones as potential cyclooxygenase-2 (COX-2), 5-lipoxygenase (5-LOX) and phosphodiesterase 4B (PDE4B) inhibitors

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely prescribed to treat inflammatory-related diseases, pain and fever. However, the prolong use of traditional NSAIDs leads to undesirable side effects such as gastric, ulceration, and renal toxicity due to lack of selectivity toward respective targets for COX-2, 5-LOX, and PDE4B. Thus, targeting multiple sites can reduce these adverse effects of the drugs and increase its potency. A series of methoxyflavones (F1-F5) were synthesized and investigated for their anti-inflammatory properties through molecular docking and inhibition assays. Among these flavones, only F2 exhibited selectivity toward COX-2 (Selectivity Index, SI: 3.90, COX-2 inhibition: 98.96 ± 1.47%) in comparison with celecoxib (SI: 7.54, COX-2 inhibition: 98.20 ± 2.55%). For PDEs, F3 possessed better selectivity to PDE4B (SI: 4.67) than rolipram (SI: 0.78). F5 had the best 5-LOX inhibitory activity among the flavones (33.65 ± 4.74%) but less than zileuton (90.81 ± 0.19%). Docking analysis indicated that the position of methoxy group and the substitution of halogen play role in determining the bioactivities of flavones. Interestingly, F1-F5 displayed favorable pharmacokinetic profiles and acceptable range of toxicity (IC₅₀>70 µM) in cell lines with the exception for F1 (IC₅₀: 16.02 ± 1.165 µM). This study generated valuable insight in designing new anti-inflammatory drug based on flavone scaffold. The newly synthesized flavones can be further developed as future therapeutic agents against inflammation.

Pyrazole Substituted 9-Anilinoacridines as HER2 Inhibitors Targeting Breast Cancer - An In-Silico Approach

BACKGROUND

Breast cancer is one of the malignant tumours which mainly affect the female population. Total 20% of the cases of breast cancer are due to overexpression of Human epidermal growth factor receptor-2 (HER2), which is the dominant tyrosine kinase receptor. In general, 9-anilinoacridine derivatives play an important role as antitumor agents due to their DNA-intercalating properties.

OBJECTIVE

Some novel 9-anilinoacridines substituted with pyrazole moiety(1a-z) were designed, and their HER2enzyme (PDB id-3PP0) inhibition activity was evaluated by molecular docking studies using the Glide module of Schrodinger suite 2019-4.

METHODS

Glide module of the Schrodinger suite was used to perform docking studies, qikprop module was used for in-silico ADMET screening, and the Prime-MM-GBSA module was used for free binding energy calculations. Using GLIDE scoring functions, we can determine the binding affinity of ligands (1a-z) towards HER2.

RESULTS

The inhibitory activity of ligands against HER2 was mainly due to the strong hydrophobic and hydrogen bonding interactions. Almost all the compounds 1a-z have a good binding affinity with Glide scores in the range of -4.9 to -9.75 compared to the standard drugs CK0403(-4.105) and Tamoxifen (-3.78). From the results of in-silico ADMET properties, most of the compounds fall within the recommended values. MM-GBSA binding calculations of the most potent inhibitors are more favourable.

CONCLUSION

The results of in-silico studies provide strong evidence for the consideration of valuable ligands in pyrazole substituted 9-anilinoacridines as potential HER2 inhibitors, and the compounds, 1v,s,r,d, a,o with significant Glide scores may produce significant anti-breast cancer activity for further development.

Docking based screening and molecular dynamics simulations to identify potential selective PDE4B inhibitor

Inhibition of phosphodiesterase 4 (PDE4) is a promising therapeutic approach for the treatment of inflammatory pulmonary disorders, i.e. asthma and chronic obstructive pulmonary disease. However, the treatment with non-selective PDE4 inhibitors is associated with side effects such as nausea and vomiting. Among the subtypes of PDE4 inhibited by these inhibitors, PDE4B is expressed in immune, inflammatory and airway smooth muscle cells, whereas, PDE4D is expressed in the area postrema and nucleus of the solitary tract. Thus, PDE4D inhibition is responsible for the emetic response. In this regard, a selective PDE4B inhibitor is expected to be a potential drug candidate for the treatment of inflammatory pulmonary disorders. Therefore, a shared feature pharmacophore model was developed and used as a query for the virtual screening of Maybridge and SPECS databases. A number of filters were applied to ensure only compounds with drug-like properties were selected. Accordingly, nine compounds have been identified as final hits, where HTS04529 showed the highest affinity and selectivity for PDE4B over PDE4D in molecular docking. The docked complexes of HTS04529 with PDE4B and PDE4D were subjected to molecular dynamics simulations for 100ns to assess their binding stability. The results showed that HTS04529 was bound tightly to PDE4B and formed a more stable complex with it than with PDE4D.

Computational Approaches for Elucidating Protein-Protein Interactions in Cation Channel Signaling

BACKGROUND

The lipid bilayer of the plasma membrane is impermeable to ions, yet changes in the flux of ions across the cell membrane are critical regulatory events in cells. Because of their regulatory roles in a range of physiological processes, such as electrical signaling in muscles and neurons, to name a few, these proteins are one of the most important drug targets.

OBJECTIVE

This review mainly focused on the computational approaches for elucidating proteinprotein interactions in cation channel signaling.

DISCUSSION

Due to continuously advanced facilities and technologies in computer sciences, the physical contacts of macromolecules of channel structures have been virtually visualized. Indeed, techniques like protein-protein docking, homology modeling, and molecular dynamics simulation are valuable tools for predicting the protein complex and refining channels with unreleased structures. Undoubtedly, these approaches will greatly expand the cation channel signaling research, thereby speeding up structure-based drug design and discovery.

CONCLUSION

We introduced a series of valuable computational tools for elucidating protein-protein interactions in cation channel signaling, including molecular graphics, protein-protein docking, homology modeling, and molecular dynamics simulation.

Dibenzepinones, dibenzoxepines and benzosuberones based p38α MAP kinase inhibitors: Their pharmacophore modelling, 3D-QSAR and docking studies

In the present study, a series of dibenzepinones, dibenzoxepines, and benzosuberones targeting p38α MAP kinase were subjected to pharmacophore modelling, 3D-QSAR and molecular docking studies. The IC₅₀ values for these 67 compounds ranged between 0.003 and 6.80 μM. A five-point model (DDHHR.8) was generated using these compounds. This model was found to be statistically significant and was found to have high correlation (R² = 0.98), cross-validation coefficient (Q² = 0.95) and F (330) values at six component PLS factor. Tests were performed to ascertain the efficacy of the generated model. These tests included external validation, Tropsha's test for predictive ability, Y-randomisation test and domain of applicability (APD). In order to check the restrictivity of the model, enrichment studies were performed with inactive compounds by using decoy set molecules. To evaluate the effectiveness of the docking protocol, the co-crystallised ligand was extracted from the ligand-binding domain of the protein and was re-docked into the same position. Both the conformers were then superimposed, suggesting satisfactory docking parameters with an RMSD value of less than 1.0 Å (0.853 Å). A 10 ns molecular dynamics simulation confirmed the docking results of the 3UVP-ligand complex and the presumed active conformation. The outcome of the present study provides insight into the molecular features that promote bioactivity and can be exploited for the prediction of novel potent p38α MAP kinase inhibitors before carrying out their synthesis and anticancer evaluation.

In-silico Design, ADMET Screening, MM-GBSA Binding Free Energy of Some Novel Isoxazole Substituted 9-Anilinoacridines as HER2 Inhibitors Targeting Breast Cancer

BACKGROUND

Human Epidermal development factor Receptor-2 (HER2) is a membrane tyrosine kinase which is overexpressed and gene amplified in human breast cancers. HER2 amplification and overexpression have been linked to important tumor cell proliferation and survival pathways for 20% of instances of breast cancer. 9-aminoacridines are significant DNA-intercalating agents because of their antiproliferative properties.

OBJECTIVE

Some novel isoxazole substituted 9-anilinoacridines(1a-z) were designed by in-silico technique for their HER2 inhibitory activity. Docking investigations of compounds 1a-z are performed against HER2 (PDB id-3PP0) by using Schrodinger suit 2016-2.

METHODS

Molecular docking study for the designed molecules 1a-z are performed by Glide module, in-silico ADMET screening by QikProp module and binding free energy by Prime-MMGBSA module of Schrodinger suit. The binding affinity of designed molecules 1a-z towards HER2 was chosen based on GLIDE score.

RESULTS

Many compounds showed good hydrophobic communications and hydrogen bonding associations to hinder HER2. The compounds 1a-z, aside from 1z have significant Glide scores in the scope of - 4.91 to - 10.59 when compared with the standard Ethacridine (- 4.23) and Tamoxifen (- 3.78). The in-silico ADMET properties are inside the suggested about drug likeness. MM-GBSA binding of the most intense inhibitor is positive.

CONCLUSION

The outcomes reveal that this study provides evidence for the consideration of isoxazole substituted 9-aminoacridine derivatives as potential HER2 inhibitors. The compounds, 1s,x,v,a,j,r with significant Glide scores may produce significant anti breast cancer activity and further in vitro and in vivo investigations may prove their therapeutic potential.

Computational insights into factor affecting the potency of diaryl sulfone analogs as Escherichia coli dihydropteroate synthase inhibitors

Dihydropteroate synthase (DHPS) is an alluring target for designing novel drug candidates to prevent infections caused by pathogenic Escherichia coli strains. Diaryl Sulfone (SO) compounds are found to inhibit DHPS competitively with respect to the substrate pABA (p-aminobenzoate). The extra aromatic ring of diaryl sulfone compounds found to stabilize them in highly flexible pABA binding loops. In this present study, a statistically significant 3D-QSAR model was developed using a data set of diaryl sulfone compounds. The favourable and unfavourable contributions of substitutions in sulfone compounds were illustrated by contour plot obtained from the developed 3D-QSAR model. Molecular docking calculations were performed to investigate the putative binding mode of diaryl sulfone compounds at the catalytic pocket. DFT calculations were carried out using SCF approach, B3LYP- 6-31 G (d) basis set to compute the HOMO, LUMO energies and their respective location at pABA binding pocket. Further, the developed model was validated by FEP (Free Energy Perturbation) calculations. The calculated relative free energy of binding between the highly potent and less potent sulfone compound was found to be -3.78 kcal/ mol which is comparable to the experimental value of -5.85 kcal/mol. A 10 ns molecular dynamics simulation of inhibitor and DHPS confirmed its stability at pABA catalytic site. Outcomes of the present work provide deeper insight in designing novel drug candidates for pathogenic Escherichia coli strains.

Simulation Strategies for Characterizing Phosphodiesterase-5 Inhibitors in Botanical Dietary Supplements

A novel "Prediction and Confirmation" (PC) strategy was proposed for characterizing phosphodiesterase-5 inhibitor (PDE-5) derivatives in botanical dietary supplements (BDSs) for on-site detection. Discovery Studio (DS) and density functional theory (DFT) calculations were used for the "Prediction" step in order to estimate PDE-5 derivative structures and theoretical Raman shifts without synthesizing the derivatives. After 11 potentially bioactive sildenafil derivatives were acquired through DS, 32 common calculated Raman shifts were obtained through DFT. The mean absolute wavenumber deviation (δ, peak range) of the major bands and the minimum number (τ) of Raman spectral peaks matching the calculated common shifts were optimized, so that a positive result of an unknown sample could be reasonably produced. In this study, δ was set at ±10 cm^-1 and the corresponding τ was set at 4-5 after optimization. Surface plasmon resonance (SPR) biosensor and surface-enhanced Raman scattering (SERS) detection were the "Confirmation" step to validate the reliability and accuracy of DS and DFT in the "Prediction" step, respectively. The optimized δ and τ criteria were used as indexes for on-site SERS detection after thin-layer chromatographic (TLC) separation of six real-world samples, one of which was preliminarily identified as "suspected positive samples." This strategy allows for a quick determination of the BDSs adulterated with sildenafil or its derivatives, independent of any standard materials.

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease (AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.