Molecular modeling studies of quinoline derivatives as VEGFR-2 tyrosine kinase inhibitors using pharmacophore based 3D QSAR and docking approach

Molecular dynamics simulation, 3D-pharmacophore and scaffold hopping analysis in the design of multi-target drugs to inhibit potential targets of COVID-19

SARS-CoV-2 has posed serious threat to the health and has inflicted huge costs in the world. Discovering potent compounds is a critical step to inhibit coronavirus. 3CL^pro and RdRp are the most conserved targets associated with COVID-19. In this study, three-dimensional pharmacophore modeling, scaffold hopping, molecular docking, structure-based virtual screening, QSAR-based ADMET predictions and molecular dynamics analysis were used to identify inhibitors for these targets. Binding free energies estimated by molecular docking for each ligand in different binding sites of RdRp were used to predict the active site. Previously reported active 3CL^pro and RdRp inhibitors were used to build a pharmacophore model to develop different scaffolds. Structure-based simulations and pharmacophore modeling based on Hip Hop algorithm converged in a state that suggest hydrogen bond acceptor and donor features have a critical role in the two binding sites. Further validations indicated that the best pharmacophore model has fairly good correlation values compared with approved inhibitors. Structure-based simulation results approved that GLu166 and Gln189 in 3CL^pro and Lys551 and Glu811 in RdRp, are critical residues for dual activities. Ten compounds were extracted from pharmacophore-based virtual screening in six databases. The results, gained by repurposing approach, suggest the effectiveness of these ten compounds with different scaffolds as possible inhibitors of the two targets. Some quinoline-based hybrid derivatives also were designed. QSAR descriptors plot predicted that the scaffolds have had accepted pharmacokinetic profiles. Multiple molecular dynamics simulations in 100 ns and MM/PBSA studies of some reference inhibitors and the novel compounds in complex with both targets demonstrated stable complexes and confirmed the interaction modes. Based on different computational methods, COVID-19 multi-target inhibitors are proposed. Communicated by Ramaswamy H. Sarma.

Comparison of various methods for validity evaluation of QSAR models

BACKGROUND

Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature.

METHODS

In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed.

RESULTS

The findings revealed that employing the coefficient of determination (r²) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies.

CONCLUSION

This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.

A Study on the Effect of the Substituent against PAK4 Inhibition Using In Silico Methods

The intrinsic inductive properties of atoms or functional groups depend on the chemical properties of either electron-withdrawing groups (EWGs) or electron-donating groups (EDGs). This study aimed to evaluate in silico methods to determine whether changes in chemical properties of the compound by single atomic substitution affect the biological activity of target proteins and whether the results depend on the properties of the functional groups. We found an imidazo[4,5-b]pyridine-based PAK4 inhibitor, compound 1, as an initial hit compound with the well-defined binding mode for PAK4. In this study, we used both experimental and in silico methods to investigate the effect of atomic substitution on biological activity to optimize the initial hit compound. In biological assays, in the case of EWG, as the size of the halogen atom became smaller and the electronegativity increased, the biological activity IC₅₀ value ranged from 5150 nM to inactive; in the case of EDG, biological activity was inactive. Furthermore, we analyzed the interactions of PAK4 with compounds, focusing on the hinge region residues, L398 and E399, and gatekeeper residues, M395 and K350, of the PAK4 protein using molecular docking studies and fragment molecular orbital (FMO) methods to determine the differences between the effect of EWG and EDG on the activity of target proteins. These results of the docking score and binding energy did not explain the differences in biological activity. However, the pair-interaction energy obtained from the results of the FMO method indicated that there was a difference in the interaction energy between the EWG and EDG in the hinge region residues, L398 and E399, as well as in M395 and K350. The two groups with different properties exhibited opposite electrostatic energy and charge transfer energy between L398 and E399. Additionally, we investigated the electron distribution of the parts interacting with the hinge region by visualizing the molecular electrostatic potential (MEP) surface of the compounds. In conclusion, we described the properties of functional groups that affect biological activity using an in silico method, FMO.

Computational identification of 2,4-disubstituted amino-pyrimidines as L858R/T790M-EGFR double mutant inhibitors using pharmacophore mapping, molecular docking, binding free energy calculation, DFT study and molecular dynamic simulation

Pharmacophore modelling studies have been performed for a series of 2,4-disubstituted-pyrimidines derivatives as EGFR L858R/T790M tyrosine kinase inhibitors. The high scoring AARR.15 hypothesis was selected as the best pharmacophore model with the highest survival score of 3.436 having two hydrogen bond acceptors and two aromatic ring features. Pharmacophore-based virtual screening followed by structure-based yielded the six molecules (ZINC17013227, ZINC17013215, ZINC9573324, ZINC9573445, ZINC24023331 and ZINC17013503) from the ZINC database with significant in silico predicted activity and strong binding affinity towords the EGFR L858R/T790M tyrosine kinase. In silico toxicity and cytochrome profiling indicates that all the 06 virtually screened compounds were substrate/inhibitors of the CYP-3A4 metabolizing enzyme and were non-carcinogenic and devoid of Ames mutagenesis. Density functional theory (DFT) and molecular dynamic (MD) simulation further validated the obtained hits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00113-x.

Quinoline Antimalarials Increase the Antibacterial Activity of Ampicillin

Bacterial and malaria co-infections are common in malaria endemic countries and thus necessitate co-administration of antibiotics and antimalarials. There have long been anecdotal clinical reports of interactions between penicillins and antimalarial agents, but the nature and mechanisms of these interactions remain to be investigated. In this study, we employed antimicrobial interaction testing methods to study the effect of two antimalarials on the antibacterial activity of ampicillin in vitro. Paper strip diffusion, a modified disc diffusion and checkerboard methods were used to determine the nature of interactions between ampicillin and quinoline antimalarials, chloroquine and quinine, against Gram-positive and Gram-negative bacteria. The impact of antimalarials and ampicillin-antimalarial drug combinations on cell integrity of test bacteria were determined by measuring potassium release. The tested antimalarials did not show substantial antibacterial activity but quinine was bactericidal at high concentrations. Chloroquine and quinine increased ampicillin activity, with increasing concentrations extending the antibacterial’s inhibition zones by 2.7-4.4 mm and from 1.1 to over 60 mm, respectively. Observed interactions were largely additive with Fractional Inhibitory Concentration Indices of >0.5-1 for all ampicillin-antimalarial combinations. Quinine and, to a lesser extent, chloroquine increase the activity of ampicillin and potentially other β-lactams, which has implications for combined clinical use.

Anti-Angiogenic Effect of Cantharellus cibarius Extracts, its Correlation with Lipoxygenase Inhibition, and Role of the Bioactives Therein

Angiogenesis is a complex physiological process that cannot be treated with single agent therapy. Several edible fungi have been known to encompass bioactive compounds, and are promising sources of multi-component drugs. One such widely consumed edible fungi is Cantharellus cibarius, which has been explored for its biological activities. The present study focused on assessing the anti-angiogenic activity of petroleum ether and ethanol extracts of C. cibarius using chick chorioallantoic membrane (CAM) assay. Both the extracts showed a dose-dependent response which was compared with the anti-angiogenic activity of the positive controls silibinin, and lenalidomide. The extracts were also studied for their lipoxygenase (LOX) inhibitory potential and compared to ascorbic acid as the positive control. The IC₅₀ values of the petroleum ether extract, ethanol extract, and ascorbic acid for LOX inhibition assay were 135.4, 113.1, and 41.5 µg/mL, respectively. Although both the extracts showed similar responses in CAM assay, ethanol extract proved to be more potent in LOX inhibition assay. Finally, the extracts were investigated for their chemical composition using GC-MS. A correlation between LOX inhibition and anti-angiogenic potential was established at the molecular level. A meticulous literature search was carried out to correlate the biochemical composition of the extracts to their anti-angiogenic activity.

Introducing a pyrazolopyrimidine as a multi-tyrosine kinase inhibitor, using multi-QSAR and docking methods

In cancer disease, which is one of the problems of today's human societies, the expression of some tyrosine kinase receptors that are effective in the growth and proliferation of cancerous cells rises. Therefore, it is essential to develop and propose new drugs to target the receptors. Performing modeling calculations such as QSAR and docking makes the drug discovery process more efficient. Thus, backpropagation artificial neural network was used for multidimensional quantitative structure-activity relationship (QSAR) to identify essential features of pyrazolopyrimidine moiety, responsible for anticancer activity. The statistical parameters of the model show that multi-QSAR has sufficient validity and accuracy. According to the QSAR modeling, among 26 compounds, the interaction of eight candidates with EGFR, FGFR4, PDGFRA, and VEGFR2 was analyzed by docking modeling. The results showed that 1u compound binds to proteins in a more appropriate area (except FGFR4) with acceptable energy. The results of docking for VEGFR2 binding showed that 1u binds to the active site and binding site of receptor, and it was in the interaction with ten residues in the sites. Although the binding site of 1u molecule in the FGFR4 was not suitable, the binding free energy was excellent (- 9.22 kcal mol^-1), which was less than those two anticancer drugs of gefitinib and regorafenib. Furthermore, the values of binding free energy were - 8.69, - 9.64, and - 9.19 kcal mol^-1 for EGFR, PDGFRA, and VEGFR2, respectively. Therefore, this study introduces 1u as an anticancer agent that can inhibit the tyrosine kinase receptors.

Pharmacophore Modeling, Synthesis, Scaffold Hopping and Biological β- Hematin Inhibition Interaction Studies for Anti-malaria Compounds

Backgound:

Exploring potent compounds is critical to generating multi-target drug discovery. Hematin crystallization is an important mechanism of malaria.

Methods:

A series of chloroquine analogues were designed using a repositioning approach to develop new anticancer compounds. Protein-ligand interaction fingerprints and ADMET descriptors were used to assess docking performance in virtual screenings to design chloroquine hybrid β-hematin inhibitors. A PLS algorithm was applied to correlate the molecular descriptors to IC50 values. The modeling presented excellent predictive power with correlation coefficients for calibration and cross-validation of r2 = 0.93 and q2 = 0.72. Using the model, a series of 4-aminoquinlin hybrids were synthesized and evaluated for their biological activity as an external test series. These compounds were evaluated for cytotoxic cell lines and β-hematin inhibition.

Results:

The target compounds exhibited high β-hematin inhibition activity and were 3-9 times more active than the positive control. Furthermore, all the compounds exhibited moderate to high cytotoxic activity. The most potent compound in the dataset was docked with hemoglobin and its pharmacophore features were generated. These features were used as input to the Pharmit server for screening of six databases.

Conclusion:

The compound with the best score from ChEMBL was 2016904, previously reported as a VEGFR-2 inhibitor. The 11 compounds selected presented the best Gold scores with drug-like properties and can be used for drug development.

Molecular Design and Synthesis of New 3,4-Dihydropyrimidin-2(1H)-Ones as Potential Anticancer Agents with VEGFR-2 Inhibiting Activity

BACKGROUND

Two series of 3,4-dihydropyrimidin-2(1H)-one derivatives were designed based on the main structural features characterizing reported anticancer compounds with potent VEGFR-2 inhibiting activity.

METHODS

All the target compounds were synthesized and investigated for their in vitro anticancer activity using MTT assay and NCI protocol. The most active compounds were further investigated for the VEGFR-2 inhibiting activity using enzyme inhibition assay.

RESULT

Of these derivatives, compound 8b possessed significant activity against Caco-2 (IC50 of 24.9 µM) and MCF7 (IC50 of 29.4 µM), compound 10 showed excellent potency against HCT-116 (IC50 of 32.6 µM), HEPG2 (IC50 of 16.4 µM) and MCF7 (IC50 of 32.8 µM), while compound 11b exhibited moderate anticancer activity towards MCF7 (IC50 of 41.7µM). Both 8b and 10 exhibited good potency regarding the inhibition of vascular endothelial growth factor receptor 2 (VEGFR-2), with an IC50 of 14.00 and 21.62 nM, respectively.

CONCLUSION

The activity was rationalized based on molecular docking study that supported their VEGFR-2 inhibitory activity; as indicated by their favorable binding with the active site.