Search Results (26)

A total of 16 organic sunscreens and over 160 products of their degradation in biotic and abiotic conditions were investigated in the context of their safety during pregnancy. Drug-likeness and the ability of the studied compounds to be absorbed from the gastrointestinal tract and cross the human placenta were predicted in silico using the SwissADME software (for drug-likeness and oral absorption) and multiple linear regression and “ARKA” models (for placenta permeability expressed as fetus-to-mother blood concentration in the state of equilibrium), with the latter outperforming the MLR models. It was established that most of the studied compounds can be absorbed from the gastrointestinal tract. The drug-likeness of the studied compounds (expressed as a binary descriptor, Lipinski) is closely related to their ability to cross the placenta (most likely by a passive diffusion mechanism). The organic sunscreens and their degradation products are likely to cross the placenta, except for very bulky and highly lipophilic 1,3,5-triazine derivatives; an avobenzone degradation product, 1,2-bis(4-tert-butylphenyl)ethane-1,2-dione; diethylamino hydroxybenzoyl hexyl benzoate; and dimerization products of sunscreens from the 4-methoxycinnamate group. Full article

Lipinski’s Rule of Five and Ghose filter are empirical guidelines for evaluating the drug-likeness of a compound, suggesting that orally active drugs typically fall within specific ranges for molecular descriptors such as hydrogen bond donors and acceptors, weight, and lipophilicity. We revisit these practices and offer a more analytical perspective using the Dominance-based Rough Set Approach (DRSA). By analyzing representative samples of drug and non-drug molecules and focusing on the same molecular descriptors, we derived decision rules capable of distinguishing between these two classes systematically and reproducibly. This way, we reduced human bias and enabled efficient knowledge extraction from available data. The performance of the DRSA model was rigorously validated against traditional rules and available machine learning (ML) approaches, showing a significant improvement over empirical rules while achieving comparable predictive accuracy to more complex ML methods. Our rules remain simple and interpretable while being characterized by high sensitivity and specificity. Full article

Lipophilicity is an essential parameter of a compound that determines the solubility and pharmacokinetic properties that determine the transport of the drug to the molecular target. Dimers of dipyridothiazines are diazaphenothiazine derivatives exhibiting diverse anticancer potential in vitro, which is related to their affinity for histone deacetylase. In this study, the lipophilicity of 16 isomeric dipyridothiazine dimers was investigated theoretically and experimentally by reversed-phase thin-layer chromatography (RP-TLC) in an acetone–TRIS buffer (pH = 7.4). The relative lipophilicity parameter R_M0 and specific hydrophobic surface area b were significantly intercorrelated, showing congeneric classes of dimers. The parameter R_M0 was transformed into parameter logP_TLC by use of the calibration curve. Molecular descriptors, ADMET parameters and probable molecular targets were determined in silico for analysis of the pharmacokinetic profile of the tested compounds showing anticancer activity. The analyzed compounds were tested in the context of Lipinski’s rule of five, Ghose’s rule and Veber’s rule, confirming their bioavailability. Full article

The quinoline derivative, N-(7-chloro-4-morpholinoquinolin-2-yl)benzamide, was synthesized in a conventional three-step procedure from 4,7-dichloroquinoline using a N-oxidation reaction/C2-amide formation reaction/C4 S_NAr reaction sequence. The structure of the compound was fully characterized by FT-IR, ¹H-, ¹³C-NMR, DEPT-135°, and ESI-MS techniques. Its physicochemical parameters (Lipinski’s descriptors) were also calculated using the online SwissADME database. Such derivatives are relevant therapeutic agents exhibiting potent anticancer, antibacterial, antifungal, and antiparasitic properties. Full article

Alzheimer’s disease (AD) is a neurodegenerative disease that affects the majority of people worldwide. To date, there is no cure for the disease, so new therapeutic targets need to be identified and studied. Acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) are promising therapeutic targets for AD treatment. In order to identify new inhibitors, a newly synthesized series containing thirty seven 2-hydroxy-N-phenylbenzamidederivatives were tested to study the inhibition of enzymes associated with this disease. Our work focuses on the use of molecular modeling methods based on molecular docking, QSAR and ADME property prediction. Our molecular docking results discussion is based on a number of parameters. Analysis of these obtained results showed that the ligands L18, L17 and L6 have a high inhibitory effect in the case of the enzyme AChE, while the ligands L6′, L30′ and L4′ have a high inhibitory effect in the case of the enzyme BuChE. In addition, the ADME-T properties calculation proved that these ligands respect the Lipinski, Veber and Egan rules, allowing us to select them as being probably the best inhibitors of Alzheimer’s disease (AD). Then, a QSAR model was developed to explain and predict the inhibitory activity of a series of compounds using different descriptors. This model has been validated by two methods: internal and external. Full article

This study investigates the crystal structure, physicochemical properties, and pharmacokinetic profile of Ethyl 2-amino-6-methyl-4,5,6,7-tetrahydrothieno[2,3-c]pyridine-3-carboxylate (EAMT) as a potential therapeutic agent. The crystal structure was analyzed using Hirshfeld surface analysis in conjunction with the quantum theory of atoms in molecules (QT-AIM). Non-covalent interactions were evaluated through reduced-density gradient reduction, revealing that the EAMT crystal is stabilized by hydrogen bonds between EAMT molecules in the crystal and between EAMT molecules and water molecules. The molecular electrostatic nature of interactions was examined using MESP, while global and local descriptors were calculated to assess the compound’s reactivity. Molecular docking with the Adenosine A1 receptor was performed and validated through a 50 ns molecular dynamics simulation (MDS). Results suggest that EAMT influences protein structure, potentially stabilizing specific secondary structure elements. The compactness analysis showed a slightly more compact protein conformation and a marginally increased solvent exposure in the presence of the EAMT ligand, as indicated by R_g and SASA values. The total binding free energy (ΔG total) was determined to be −114.56 kcal/mol. ADMET predictions demonstrated EAMT’s compliance with Lipinski’s and Pfizer’s rule of five, indicating good oral availability. The compound may exhibit low-potency endocrine activity. In conclusion, EAMT presents potential as a therapeutic candidate, warranting further exploration of its molecular interactions, pharmacokinetics, and potential safety concerns. Full article

Drug design with machine learning support can speed up new drug discoveries. While current databases of known compounds are smaller in magnitude (approximately ${10}^8$), the number of small drug-like molecules is estimated to be between ${10}^{23}$ and ${10}^{60}$. The use of molecular docking algorithms can help in new drug development by sieving out the worst drug-receptor complexes. New chemical spaces can be efficiently searched with the application of artificial intelligence. From that, new structures can be proposed. The research proposed aims to create new chemical structures supported by a deep neural network that will possess an affinity to the selected protein domains. Transferring chemical structures into SELFIES codes helped us pass chemical information to a neural network. On the basis of vectorized SELFIES, new chemical structures can be created. With the use of the created neural network, novel compounds that are chemically sensible can be generated. Newly created chemical structures are sieved by the quantitative estimation of the drug-likeness descriptor, Lipinski’s rule of 5, and the synthetic Bayesian accessibility classifier score. The affinity to selected protein domains was verified with the use of the AutoDock tool. As per the results, we obtained the structures that possess an affinity to the selected protein domains, namely PDB IDs 7NPC, 7NP5, and 7KXD. Full article

The ever-expanding pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has gained attention as COVID-19 and caused an emergency in public health to an unmatched level to date. However, the treatments used are the only options; currently, no effective and licensed medications are available to combat disease transmission, necessitating further research. In the present study, an in silico-based virtual screening of anti-HIV bioactive compounds from medicinal plants was carried out through molecular docking against the main protease (M^pro) (PDB: 6LU7) of SARS-CoV-2, which is a key enzyme responsible for virus replication. A total of 16 anti-HIV compounds were found to have a binding affinity greater than −8.9 kcal/mol out of 150 compounds screened. Pseudohypericin had a high affinity with the energy of −10.2 kcal/mol, demonstrating amino acid residual interactions with LEU141, GLU166, ARG188, and GLN192, followed by Hypericin (−10.1 kcal/mol). Moreover, the ADME (Absorption, Distribution, Metabolism and Excretion) analysis of Pseudohypericin and Hypericin recorded a low bioavailability (BA) score of 0.17 and violated Lipinski’s rule of drug-likeness. The docking and molecular simulations indicated that the quinone compound, Pseudohypericin, could be tested in vitro and in vivo as potent molecules against COVID-19 disease prior to clinical trials.This was also supported by the theoretical and computational studies conducted. The global and local descriptors, which are the underpinnings of Conceptual Density FunctionalTheory (CDFT) have beenpredicted through successful model chemistry, hoping that they could be of help in the comprehension of the chemical reactivity properties of the molecular systems considered in this study. Full article

Computational chemistry, molecular docking, and drug design approaches, combined with the biochemical evaluation of the antitumor activity of selected derivatives of the thiouracil-based dihydroindeno pyrido pyrimidines against topoisomerase I and II. The IC50 of other cell lines including the normal human lung cell line W138, lung cancer cell line, A549, breast cancer cell line, MCF-7, cervical cancer, HeLa, and liver cancer cell line HepG2 was evaluated using biochemical methods. The global reactivity descriptors and physicochemical parameters were computed, showing good agreement with the Lipinski and Veber’s rules of the drug criteria. The molecular docking study of the ligands with the topoisomerase protein provides the binding sites, binding energies, and deactivation constant for the inhibition pocket. Various biochemical methods were used to evaluate the IC50 of the cell lines. The QSAR model was developed for colorectal cell line HCT as a case study. Four QSAR statistical models were predicted between the IC50 of the colorectal cell line HCT to correlate the anticancer activity and the computed physicochemical and quantum chemical global reactivity descriptors. The predictive power of the models indicates a good correlation between the observed and the predicted activity. Full article

Mycobacterium tuberculosis (M.tb.) enoyl-acyl carrier protein (ACP) reductase (InhA) is validated as a useful target for tuberculosis therapy and is considered an attractive enzyme to drug discovery. This study aimed to identify the novel inhibitor of the InhA enzyme, a potential target of M.tb. involved in the type II fatty acid biosynthesis pathway that controls mycobacterial cell envelope synthesis. We compiled 80 active compounds from Ruta graveolens and citrus plants belonging to the Rutaceae family for pharmacokinetics and molecular docking analyses. The chemical structures of the 80 phytochemicals and the 3D structure of the target protein were retrieved from the PubChem database and RCSB Protein Data Bank, respectively. The evaluation of druglikeness was performed based on Lipinski’s Rule of Five, while the computed phytochemical properties and molecular descriptors were used to predict the ADMET of the compounds. Amongst these, 11 pharmacokinetically-screened compounds were further examined by performing molecular docking analysis with an InhA target using AutoDock 4.2. The docking results showed that gravacridonediol, a major glycosylated natural alkaloid from Ruta graveolens, might possess a promising inhibitory potential against InhA, with a binding energy (B.E.) of −10.80 kcal/mole and inhibition constant (Ki) of 600.24 nM. These contrast those of the known inhibitor triclosan, which has a B.E. of −6.69 kcal/mole and Ki of 12.43 µM. The binding efficiency of gravacridonediol was higher than that of the well-known inhibitor triclosan against the InhA target. The present study shows that the identified natural compound gravacridonediol possesses drug-like properties and also holds promise in inhibiting InhA, a key target enzyme of M.tb. Full article

A 2,4-diarylquinoline derivative, 2-(4-chlorophenyl)-4-(3,4-dimethoxyphenyl)-6-methoxy-3-methylquinoline, was synthesized in a conventional two-step procedure from p-anisidine, p-chlorobenzaldehyde and methyl isoeugenol as available starting reagents through a sequence of BF₃·OEt₂-catalyzed Povarov cycloaddition reaction/oxidative dehydrogenation aromatization processes under microwave irradiation conditions in the presence of a green oxidative I₂-DMSO system. The structure of the compound was fully characterized by FT-IR, ¹H and ¹³C-NMR, ESI-MS, and elemental analysis. Its physicochemical parameters (Lipinski’s descriptors) were also calculated using the Molinspiration Cheminformatics software. The diarylquinoline molecule obtained is an interesting model with increased lipophilicity and thus permeability, an important descriptor for quinoline-based drug design. Such types of derivatives are known for their anticancer, antitubercular, antifungal, and antiviral activities. Full article

Withania somnifera is a traditional Indian herb described under the ‘Rasayana’ class in Ayurveda, which gained immense popularity as a dietary supplement in the USA, Europe, Asia, and the Indian domestic market. Despite enormous research on the pharmacological effect of withanosides and withanolides, bioanalytical method development and pharmacokinetics remained challenging and unexplored for these constituents due to isomeric and isobaric characteristics. In current research work, molecular descriptors, pharmacokinetic, and toxicity prediction (ADMET) of these constituents were performed using Molinspiration and admetSAR tools. A rapid, selective, and reproducible bioanalytical method was developed and validated for seven withanosides and withanolides as per USFDA/EMA guidelines, further applied to determine pharmacokinetic parameters of Withania somnifera root extract (WSE) constituents in male Sprague Dawley rats at a dose of 500 mg/kg. Additionally, an ex vivo permeability study was carried out to explore the absorption pattern of withanosides and withanolides from the intestinal lumen. In silico, ADMET revealed oral bioavailability of withanosides and withanolides following Lipinski’s rules of five with significant absorption from the gastrointestinal tract and the ability to cross the blood-brain barrier. Upon oral administration of WSE, C_max was found to be 13.833 ± 3.727, 124.415 ± 64.932, 57.536 ± 7.523, and 7.283 ± 3.341 ng/mL for withanoside IV, withaferin A, 12-Deoxy-withastramonolide, and withanolide A, respectively, with T_max of 0.750 ± 0.000, 0.250 ± 0.000, 0.291 ± 0.102, and 0.333 ± 0.129 h. Moreover, at a given dose, withanoside V, withanolide B, and withanone were detected in plasma; however, the concentration of these constituents was found below LLOQ. Thus, these four major withanoside and withanolides were quantified in plasma supported by ex vivo permeation data exhibiting a time-dependent absorption of withanosides and withanolides across the intestinal barrier. These composite findings provide insights to design a clinical trial of WSE as a potent nutraceutical. Full article

Fifty (50) phytocompounds from several subclasses of polyphenols, chosen based on their abundance in the plant world, were analyzed through density functional methods, using computational tools to evaluate their oral availability and particular bioactivity on several cell modulators; key descriptors and molecular features related to the electron density and electrostatic potential for the lowest energy conformers of the investigated molecules were computed. An analysis of the bioactivity scores towards six cell modulators (GPCR ligand, ion channel modulator, kinase inhibitor, nuclear receptor ligand, protease inhibitor and enzyme inhibitor) was also achieved, in the context of investigating their potential side effects on the human digestive processes. Summarizing, computational results confirmed in vivo and in vitro data regarding the high bioavailability of soy isoflavones and better bioavailability of free aglycones in comparison with their esterified and glycosylated forms. However, by a computational approach analyzing Lipinski’s rule, apigenin and apigenin-7-O-rhamnoside, naringenin, hesperetin, genistein, daidzin, biochanin A and formonetin in the flavonoid series and all hydroxycinnamic acids and all hydroxybenzoic acids excepting ellagic acid were proved to have the best bioavailability data; rhamnoside derivatives, the predominant glycosides in green plants, which were reported to have the lowest bioavailability values by in vivo studies, were revealed to have the best bioavailability data among the studied flavonoids in the computational approach. Results of in silico screening on the phenolic derivatives series also revealed their real inhibitory potency on the six parameters studied, showing a remarkable similitude between the flavonoid series, while flavonoids were more powerful natural cell modulators than the phenyl carboxylic acids tested. Thus, it can be concluded that there is a need for supplementation with digestive enzymes, mainly in the case of individuals with low digestive efficiency, to obtain the best health benefits of polyphenols in humans. Full article

The lipophilicity parameters (logP_calcd, R_M0 and logP_TLC) of 10 new active anticancer dipirydothiazines with a 1,2,3-triazole ring were determined theoretically using computational methods and experimentally by reversed-phase TLC. Experimental lipophilicity was assessed using mobile phases (a mixture of TRIS buffer and acetone) using a linear correlation between the R_M retention parameter and the volume of acetone. The R_M0 parameter was correlated with the specific hydrophobic surface b, revealing two congenerative subgroups: 1,2,3-triazole-1,6-diazaphenothiazines and 1,2,3-triazole-1,8-diazaphenothiazines hybrids. The R_M0 parameter was converted into the logP_TLC lipophilicity parameter using a calibration curve. The investigated compounds appeared to be moderately lipophilic. Lipophilicity has been compared with molecular descriptors and ADME properties. The new derivatives followed Lipinski’s, Ghose’s and Veber’s rules. Full article

Diabetes mellitus is a multifactorial disease that affects both developing and developed countries and is a major public health concern. Many synthetic drugs are available in the market, which counteracts the associated pathologies. However, due to the propensity of side effects, there is an unmet need for the investigation of safe and effective drugs. This research aims to find a novel phytoconstituent having diminished action on blood glucose levels with the least side effects. Shikonin is a naturally occurring naphthoquinone dying pigment obtained by the roots of the Boraginaceae family. Besides its use as pigments, it can be used as an antimicrobial, anti-inflammatory, and anti-tumor agent. This research aimed to hypothesize the physicochemical and phytochemical properties of Shikonin’s in silico interaction with protein tyrosine phosphate 1B, as well as it’s in vitro studies, in order to determine its potential anti-diabetic impact. To do so, molecular docking experiments with target proteins were conducted to assess their anti-diabetic ability. Analyzing associations with corresponding amino acids revealed the significant molecular interactions between Shikonin and diabetes-related target proteins. In silico pharmacokinetics and toxicity profile of Shikonin using ADMET Descriptor, Toxicity Prediction, and Calculate Molecular Properties tools from Biovia Discovery Studio v4.5. Filter by Lipinski and Veber Rule’s module from Biovia Discovery Studio v4.5 was applied to assess the drug-likeness of Shikonin. The in vitro studies exposed that Shikonin shows an inhibitory potential against the PTP1B with an IC50 value of 15.51 µM. The kinetics studies revealed that it has a competitive inhibitory effect (Ki = 7.5 M) on the enzyme system, which could be useful in the production of preventive and therapeutic agents. The findings of this research suggested that the Shikonin could be used as an anti-diabetic agent and can be used as a novel source for drug delivery. Full article