K-means clustering analysis, ADME/pharmacokinetic prediction, MEP, and molecular docking studies of potential cytotoxic agents

Investigation of dual inhibition of antibacterial and antiarthritic drug candidates using combined approach including molecular dynamics, docking and quantum chemical methods

Emerging antibiotic resistance in bacteria threatens immune efficacy and increases susceptibility to bone degradation and arthritic disorders. In our current study, we utilized a three-layer in-silico screening approach, employing quantum chemical methods, molecular docking, and molecular dynamic methods to explore the novel drug candidates similar in structure to floroquinolone (ciprofloxacin). We investigated the interaction of novel similar compounds of ciprofloxacin with both a bacterial protein S. aureus TyrRS (1JIJ) and a protein associated with gout arthritis Neutrophil collagenase (3DPE). UTIs and gout are interconnected through the elevation of uric acid levels. We aimed to identify compounds with dual functionality: antibacterial activity against UTIs and antirheumatic properties. Our screening based on several methods, sorted out six promising ligands. Four of these (L1, L2, L3, and L6) demonstrated favorable hydrogen bonding with both proteins and were selected for further analysis. These ligands showed binding affinities of -8.3 to -9.1 kcal/mol with both proteins, indicating strong interaction potential. Notably, L6 exhibited highest binding energies of -9.10 and -9.01 kcal/mol with S. aureus TyrRS and Neutrophil collagenase respectively. Additionally, the pkCSM online database conducted ADMET analysis on all lead ligand suggested that L6 might exhibit the highest intestinal absorption and justified total clearance rate. Moreover, L6 showed a best predicted inhibition constant with both proteins. The average RMSF values for all complex systems, namely L1, L2, L3 and L6 are 0.43 Å, 0.57 Å, 0.55 Å, and 0.51 Å, respectively where the ligand residues show maximum stability. The smaller energy gap of 3.85 eV between the HOMO and LUMO of the optimized molecule L1 and L6 suggests that these are biologically active compound. All the selected four drugs show considerable stabilization energy ranging from 44.78 to 103.87 kcal/mol, which means all four compounds are chemically and physically stable. Overall, this research opens exciting avenues for the development of new therapeutic agents with dual functionalities for antibacterial and antiarthritic drug designing.

Molecular docking/dynamics simulations, MEP analysis, bioisosteric replacement and ADME/T prediction for identification of dual targets inhibitors of Parkinson's disease with novel scaffold

Monoamine oxidase B and Adenosine A2A receptors are used as key targets for Parkinson's disease. Recently, hMAO-B and hA2AR Dual-targets inhibitory potential of a novel series of Phenylxanthine derivatives has been established in experimental findings. Hence, the current study examines the interactions between 38 compounds of this series with hMAO-B and hA2AR targets using different molecular modeling techniques to investigate the binding mode and stability of the formed complexes. A molecular docking study revealed that the compounds L24 ((E)-3-(3-Chlorophenyl)-N-(4-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl) phenyl) acrylamide and L32 ((E)-3-(3-Chlorophenyl)-N-(3-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl)phenyl)acrylamide) had a high affinity (S-score: -10.160 and -7.344 kcal/mol) with the pocket of hMAO-B and hA2AR targets respectively, and the stability of the studied complexes was confirmed during MD simulations. Also, the MEP maps of compounds 24 and 32 were used to identify the nucleophilic and electrophilic attack regions. Moreover, the bioisosteric replacement approach was successfully applied to design two new analogs of each compound with similar biological activities and low energy scores. Furthermore, ADME-T and Drug-likeness results revealed the promising pharmacokinetic properties and oral bioavailability of these compounds. Thus, compounds L24, L32, and their analogs can undergo further analysis and optimization in order to design new lead compounds with higher efficacy toward Parkinson's disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00139-3.

Investigation of [3H]diazepam derivatives as allosteric modulators of GABAA receptor α1β2γ2 subtypes: combination of molecular docking/dynamic simulations, pharmacokinetics/drug-likeness prediction, and QSAR analysis

In this paper, a data set of [³H] diazepam derivatives was analyzed using various computational methods: molecular docking/dynamic simulations, and QSAR analysis. The main aims of these studies are to understand the binding mechanisms by which benzodiazepines allosterically modulate GABA_A receptor α₁β₂γ₂ subtypes, from inducing neuronal inhibition at lower doses to the anesthetic effect at higher doses, and also, to define the structural requirements that contribute to improving the response of GABA_A/α₁β₂γ₂ receptor to benzodiazepine drugs. The results of the molecular docking study allowed selecting Ro12-6377 and proflazepam as the best modulators for the four binding sites simultaneously. Subsequently, the stability of the selected complexes was investigated by performing molecular dynamics simulation. The latter confirmed the features of both modulators to exert direct effects on the chloride-channel lining residues. Pharmacokinetics and drug-likeness profile were assessed through in silico tool. Furthermore, a QSAR analysis was conducted using an improved vemolecular dynamics simulations proposed byrsion of PLS regression. The goodness of fit and the predictive power of the resulting PLS model were estimated according to internal and external validation parameters: R² = 0.632, R²_adj = 0.584, F = 12.806; p-value = 6.2050e − 07, Q²_loo = 0.639, and Q²_F3 = 0.813. Clearly, the obtained results ensure the predictive ability of the developed QSAR model for the design of new high-potency benzodiazepine drugs.

Efficient Synthesis of 2-Aminopyridine Derivatives: Antibacterial Activity Assessment and Molecular Docking Studies

A new and suitable multicomponent one-pot reaction was developed for the synthesis of 2-amino-3-cyanopyridine derivatives.

BACKGROUND

This synthesis was demonstrated by the efficient and easy access to a variety of substituted 2-aminopyridines using enaminones as key precursors under solvent-free conditions.

METHODS

A range of spectroscopic techniques was used to determine and confirm the chemical structures (FTIR, 1H NMR, 13C NMR). The antimicrobial potency of synthesized compounds (2a-d) was tested using disk diffusion assays, and the Minimum Inhibitory Concentration (MIC) for the active compounds was determined against a panel of microorganisms, including Gram-positive and Gram-negative bacteria and yeasts. Moreover, a docking analysis was conducted by Molecular Operating Environment (MOE) software to provide supplementary information about the potential, as well as an ADME-T prediction to describe the pharmacokinetic properties of the best compound and its toxicity.

RESULTS

The results of the antimicrobial activity indicated that compound 2c showed the highest activity against Gram-positive bacteria, particularly S. aureus and B. subtilis whose MIC values were 0.039 ± 0.000 µg·mL-1. The results of the theoretical study of compound 2c were in line with the experimental data and exhibited excellent antibacterial potential.

CONCLUSIONS

On the basis of the obtained results, compound 2c can be used as an antibacterial agent model with high antibacterial potency.

Characterization of Promising Cytotoxic Metabolites from Tabebuia guayacan Hemsl.: Computational Prediction and In Vitro Testing

Genus Tabebuia is famous for its traditional uses and valuable phytoconstituents. Our previous investigation of Tabebuia species noted the promising anticancer activity of T. guayacan Hemsl. leaves extract, however, the mechanism underlying the observed anticancer activity is still unexplored. The current research was designed to explore the phytochemical content as well as to address the phytoconstituent(s) responsible for the recorded anticancer activity. Accordingly, sixteen compounds were isolated, and their structures were elucidated using different spectroscopic techniques. The drug-likeness of the isolated compounds, as well as their binding affinity with four anticancer drug target receptors: CDK-2/6, topoisomerase-1, and VEGFR-2, were evaluated. Additionally, the most promising compounds were in vitro evaluated for inhibitory activities against CDK-2/6 and VEGFR-2 enzymes using kinase assays method. Corosolic acid (3) and luteolin-7-O-β-glucoside (16) were the most active inhibitors against CDK-2 (-13.44 kcal/mol) and topoisomerase 1 (-13.83 kcal/mol), respectively. Meanwhile, quercetin 3-O-β-xyloside (10) scored the highest binding free energies against both CDK-6 (-16.23 kcal/mol) as well as against VEGFR-2 protein targets (-10.39 kcal/mol). Molecular dynamic simulation indicated that quercetin 3-O-β-xyloside (10) exhibited the least fluctuations and deviations from the starting binding pose with RMSD (2.6 Å). Interestingly, in vitro testing results confirmed the potent activity of 10 (IC50 = 0.154 µg/mL) compared to IC50 = 0.159 µg/mL of the reference drug ribociclib. These findings suggest the three noted compounds (3, 10, and 16) for further in vivo anticancer studies.

Multitarget-Based Virtual Screening for Identification of Herbal Substances toward Potential Osteoclastic Targets

Osteoporosis is a complex bone disease indicating porous bone with low bone mass density and fragility. Cathepsin K, V-ATPase, and αVβ3 integrin are exhibited as novel targets for osteoporosis treatment. Our preliminary study uses a state-of-the-art method, including target-based virtual screening and clustering methods to determine promising candidates with multitarget properties. Phytochemicals with osteoprotective properties from the literature are used to elucidate the molecular interactions toward three targets. The binding scores of compounds are normalized and rescored. The K-means and hierarchical clustering methods are applied to filter and define the promising compounds, and the silhouette analysis is supposed to validate the clustering method. We explore 108 herbal compounds by virtual screening and the cluster approach, and find that rutin, sagittatoside A, icariin, and kaempferitrin showed strong binding affinities against Cathepsin K, V-ATPase, and αVβ3 integrin. Dockings of candidates toward three targets also provide the protein-ligand interactions and crucial amino acids for binding. Our study provides a straightforward and less time-consuming approach to exploring the new multitarget candidates for further investigations, using a combination of in silico methods.