In silico exploration of anti-prostate cancer compounds from differential expressed genes.

Prostate cancer (PCa) is a complex and biologically diverse disease with no curative treatment options at present. This study aims to utilize computational methods to explore potential anti-PCa compounds based on differentially expressed genes (DEGs), with the goal of identifying novel therapeutic indications or repurposing existing drugs. The methods employed in this study include DEGs-to-drug prediction, pharmacokinetics prediction, target prediction, network analysis, and molecular docking. The findings revealed a total of 79 upregulated DEGs and 110 downregulated DEGs in PCa, which were used to identify drug compounds capable of reversing the dysregulated conditions (dexverapamil, emetine, parthenolide, dobutamine, terfenadine, pimozide, mefloquine, ellipticine, and trifluoperazine) at a threshold probability of 20% on several molecular targets, such as serotonin receptors 2a/2b/2c, HERG protein, adrenergic receptors alpha-1a/2a, dopamine D3 receptor, inducible nitric oxide synthase (iNOS), epidermal growth factor receptor erbB1 (EGFR), tyrosine-protein kinases, and C-C chemokine receptor type 5 (CCR5). Molecular docking analysis revealed that terfenadine binding to inducible nitric oxide synthase (-7.833 kcal.mol-1) and pimozide binding to HERG (-7.636 kcal.mol-1). Overall, binding energy ΔGbind (Total) at 0 ns was lower than that of 100 ns for both the Terfenadine-iNOS complex (-101.707 to -103.302 kcal.mol-1) and Ellipticine-TOPIIα complex (-42.229 to -58.780 kcal.mol-1). In conclusion, this study provides insight on molecular targets that could possibly contribute to the molecular mechanisms underlying PCa. Further preclinical and clinical studies are required to validate the therapeutic effectiveness of these identified drugs in PCa disease.

High-throughput virtual screening of Streptomyces spp. metabolites as antiviral inhibitors against the Nipah virus matrix protein.

Nipah virus (NiV) remains a significant global concern due to its impact on both the agricultural industry and human health, resulting in substantial economic and health consequences. Currently, there is no cure or commercially available vaccine for the virus. Therefore, it is crucial to prioritize the discovery of new and effective treatment options to prevent its continued spread. Streptomyces spp. are rich sources of metabolites known for their bioactivity against certain diseases; however, their potential as antiviral drugs against the Nipah virus remain unexplored. In this study, 6524 Streptomyces spp. metabolites were screened through in silico methods for their inhibitory effects against the Nipah virus matrix (NiV-M) protein, which assists in virion assembly of Nipah virus. Different computer-aided tools were utilized to carry out the virtual screening process: ADMET profiling revealed 913 compounds with excellent safety and efficacy profiles, molecular docking predicted the binding poses and associated docking scores of the ligands in their respective targets, MD simulations confirmed the binding stability of the top ten highest-scoring ligands in a 100 ns all-atom simulation, PCA elucidated simulation convergence, and MMPB(GB)SA calculations estimated the binding energies of the final candidate compounds and determined the key residues crucial for complex formation. Using in silico methods, we identified six metabolites targeting the main substrate-binding site and five targeting the dimerization site that exhibited excellent stability and strong binding affinity. We recommend testing these compounds in the next stages of drug development to confirm their effectiveness as therapeutic agents against Nipah virus.

Molecular Mechanism of Cynodon dactylon Phytosterols Targeting MAPK3 and PARP1 to Combat Epithelial Ovarian Cancer: A Multifaceted Computational Approach.

Epithelial Ovarian Cancer (EOC) presents a global health concern, necessitating the development of innovative therapeutic strategies to combat its impact. This study was employed to investigate the unexplored therapeutic efficacy of Cynodon dactylon phytochemicals against EOC using a multifaceted computational approach. A total of 19 out of 89 rigorously curated phytochemicals were assessed as potential drug targets via ADMET profiling, while protein-protein interaction analysis scrutinized the top 20 hub genes among 264 disease targets, revealing their involvement in cancer-related pathways and underscoring their significance in EOC pathogenesis. In molecular docking, Stigmasterol acetate showed the highest binding affinity (-10.9 kcal/mol) with Poly [ADP-ribose] polymerase-1 (PDB: 1UK1), while Arundoin and Beta-Sitosterol exhibited strong affinities (-10.4 kcal/mol and -10.1 kcal/mol, respectively); additionally, Beta-Sitosterol interacting with Mitogen-activated protein kinase 3 (PDB: 4QTB) showed a binding affinity of -10.1 kcal/mol, forming 2 hydrogen bonds and a total of 10 bonds with 10 residues. Molecular dynamics simulations exhibited the significant structural stability of the Beta-Sitosterol-4QTB complex with superior binding free energy (-36.61 kcal/mol) among the three complexes. This study identified C. dactylon phytosterols, particularly Beta-Sitosterol, as effective in targeting MAPK3 and PARP1 to combat EOC, laying the groundwork for further experimental validation and drug development efforts.

Construction of IRAK4 inhibitor activity prediction model based on machine learning.

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a crucial serine/threonine protein kinase that belongs to the IRAK family and plays a pivotal role in Toll-like receptor (TLR) and Interleukin-1 receptor (IL-1R) signaling pathways. Due to IRAK4's significant role in immunity, inflammation, and malignancies, it has become an intriguing target for discovering and developing potent small-molecule inhibitors. Consequently, there is a pressing need for rapid and accurate prediction of IRAK4 inhibitor activity. Leveraging a comprehensive dataset encompassing activity data for 1628 IRAK4 inhibitors, we constructed a prediction model using the LightGBM algorithm and molecular fingerprints. This model achieved an R2 of 0.829, an MAE of 0.317, and an RMSE of 0.460 in independent testing. To further validate the model's generalization ability, we tested it on 90 IRAK4 inhibitors collected in 2023. Subsequently, we applied the model to predict the activity of 13,268 compounds with docking scores less than - 9.503 kcal/mol. These compounds were initially screened from a pool of 1.6 million molecules in the chemdiv database through high-throughput molecular docking. Among these, 259 compounds with predicted pIC50 values greater than or equal to 8.00 were identified. We then performed ADMET predictions on these selected compounds. Finally, through a rigorous screening process, we identified 34 compounds that adhere to the four complementary drug-likeness rules, making them promising candidates for further investigation. Additionally, molecular dynamics simulations confirmed the stable binding of the screened compounds to the IRAK4 protein. Overall, this work presents a machine learning model for accurate prediction of IRAK4 inhibitor activity and offers new insights for subsequent structure-guided design of novel IRAK4 inhibitors.

Novel 1,3,4-oxadiazole derivatives of naproxen targeting EGFR: Synthesis, molecular docking studies, and cytotoxic evaluation.

The close association between inflammation and cancer inspired the synthesis of a series of 1,3,4-oxadiazole derivatives (compounds H4-A-F) of 6-methoxynaphtalene. The chemical structures of the new compounds were validated utilizing Fourier-transform infrared, proton nuclear magnetic resonance, and carbon-13 nuclear magnetic resonance spectroscopic techniques and CHN analysis. Computer-aided drug design methods were used to predict the compounds biological target, ADMET properties, toxicity, and to evaluate the molecular similarities between the design compounds and erlotinib, a standard epidermal growth factor receptor (EGFR) inhibitor. The antiproliferative effects of the new compounds were evaluated by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide assay, cell cycle analysis, apoptosis detection by microscopy, quantitative reverse transcription-polymerase chain reaction, and immunoblotting, and EGFR enzyme inhibition assay. In silico analysis of the new oxadiazole derivatives indicated that these compounds target EGFR, and that compounds H4-A, H4-B, H4-C, and H4-E show similar molecular properties to erlotinib. Additionally, the results indicated that none of the synthesized compounds are carcinogenic, and that compounds H4-A, H4-C, and H4-F are nontoxic. Compound H4-A showed the best-fit score against EGFR pharmacophore model, however, the in vitro studies indicated that compound H4-C was the most cytotoxic. Compound H4-C caused cytotoxicity in HCT-116 colorectal cancer cells by inducing both apoptosis and necrosis. Furthermore, compounds H4-D, H4-C, and H4-B had potent inhibitory effect on EGFR tyrosine kinase that was comparable to erlotinib. The findings of this inquiry offer a basis for further investigation into the differences between the synthesized compounds and erlotinib. However, additional testing will be needed to assess all of these differences and to identify the most promising compound for further research.

Unlocking the biological potential of transition metal complexes with Thiosemicarbazone ligands: Insights from computational studies.

In the previous study, the synthesis and characterization of 4-(3-fluorophenyl)-3-thiosemicarbazide and benzaldehyde derivatives based thiosemicarbazone ligands and their Co(II), Ni(II), Cu(II), Zn(II) complexes were carried out to evaluate their malarial and oxidant and inflammatory inhibition abilities, demonstrating that these compounds have robust efficacy for these ailments. In the present research, to find out a combating agent against breast cancer, tuberculosis, bacterial and fungal ailments, the compounds were tested through MTT, microplate alamar blue and serial dilution protocols. ADMET and DFT investigation were analyzed against highly bioactive compounds (2, 7-10) to give a new insight about compound's reactivity, stability and drug likeness properties. Furthermore, activity results shows that the ligand (2) and its complexes demonstrate greater efficacy compared to ligand (1) and its complexes. The Cu(II) (9) and Zn(II) (10) complexes were observed as highly efficient for breast cancer (MCF-7 cell line), TB (H37Rv strain), bacterial and fungal ailments in comparison of standard drugs with 0.029 ± 0.001 µM IC50 value for (9) in anticancer activity and 0.0034 ± 0.0017 µmol/mL MIC value for (10) in anti-tuberculosis activity. In the molecular docking investigation, the various kind of binding interactions and lowest binding affinity of (9) (against 4RJ3 (-10.0 kcal/mol), 2VCJ (-7.9 kcal/mol)) and (10) (-7.8 and -8.3 kcal/mol for 5V3Y and 3PTY protein) support their bioactivity. This research highlights the pharmaceutical importance of transition metal complexes having thiosemicarbazones, presenting a significant approach for the discovery of potent anti-infectious agent.

Multireceptor Analysis for Evaluating the Antidiabetic Efficacy of Karanjin: A Computational Approach.

BACKGROUND: Diabetes mellitus, notably type 2, is a rising global health challenge, prompting the need for effective management strategies. Common medications such as metformin, insulin, repaglinide and sitagliptin can induce side effects like gastrointestinal disturbances, hypoglycemia, weight gain and specific organ risks. Plant-derived therapies like Karanjin from Pongamia pinnata present promising alternatives due to their historical use, holistic health benefits and potentially fewer adverse effects. This study employs in silico analysis to explore Karanjin's interactions with diabetes-associated receptors, aiming to unveil its therapeutic potential while addressing the limitations and side effects associated with conventional medications. METHODOLOGY: The research encompassed the selection of proteins from the Protein Data Bank (PDB), followed by structural refinement processes and optimization. Ligands such as Karanjin and standard drugs were retrieved from PubChem, followed by a comprehensive analysis of their ADMET profiling and pharmacokinetic properties. Protein-ligand interactions were evaluated through molecular docking using AutoDockTools 1.5.7, followed by the analysis of structural stability using coarse-grained simulations with CABS Flex 2.0. Molecular dynamics simulations were performed using Desmond 7.2 and the OPLS4 force field to explore how Karanjin interacts with proteins over 100 nanoseconds, focusing on the dynamics and structural stability. RESULTS: Karanjin, a phytochemical from Pongamia pinnata, shows superior drug candidate potential compared to common medications, offering advantages in efficacy and reduced side effects. It adheres to drug-likeness criteria and exhibits optimal ADMET properties, including moderate solubility, high gastrointestinal absorption and blood-brain barrier penetration. Molecular docking revealed Karanjin's highest binding energy against receptor 3L2M (Pig pancreatic alpha-amylase) at -9.1 kcal/mol, indicating strong efficacy potential. Molecular dynamics simulations confirmed stable ligand-protein complexes with minor fluctuations in RMSD and RMSF, suggesting robust interactions with receptors 3L2M. CONCLUSION: Karanjin demonstrates potential in pharmaceutical expansion for treating metabolic disorders such as diabetes, as supported by computational analysis. Prospects for Karanjin in pharmaceutical development include structural modifications for enhanced efficacy and safety. Nanoencapsulation may improve bioavailability and targeted delivery to pancreatic cells, while combination therapies could optimize treatment outcomes in diabetes management. Clinical trials and experimental studies are crucial to validate its potential as a novel therapeutic agent.

Multi-Target In-Silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors.

Cardiovascular diseases, including heart failure, stroke, and hypertension, affect 608 million people worldwide and cause 32% of deaths. Combination therapy is required in 60% of patients, involving concurrent Renin-Angiotensin-Aldosterone-System (RAAS) and Neprilysin inhibition. This study introduces a novel multi-target in-silico modeling technique (mt-QSAR) to evaluate the inhibitory potential against Neprilysin and Angiotensin-converting enzymes. Using both linear (GA-LDA) and non-linear (RF) algorithms, mt-QSAR classification models were developed using 983 chemicals to predict inhibitory effects on Neprilysin and Angiotensin-converting enzymes. The Box-Jenkins method, feature selection method, and machine learning algorithms were employed to obtain the most predictive model with ~ 90% overall accuracy. Additionally, the study employed virtual screening of designed scaffolds (Chalcone and its analogues, 1,3-Thiazole, 1,3,4-Thiadiazole) applying developed mt-QSAR models and molecular docking. The identified virtual hits underwent successive filtration steps, incorporating assessments of drug-likeness, ADMET profiles, and synthetic accessibility tools. Finally, Molecular dynamic simulations were then used to identify and rank the most favourable compounds. The data acquired from this study may provide crucial direction for the identification of new multi-targeted cardiovascular inhibitors.

The synthetic cathinones MDPHP and MDPV: Comparison of the acute effects in mice, in silico ADMET profiles and clinical reports.

The 3,4-methylenedioxy-alpha-pyrrolidinohexanophenone (MDPHP) is a synthetic cathinone closely related to 3,4-methylenedioxypyrovalerone (MDPV), one of the most common synthetic cathinones present in the "bath salts". MDPHP has recently gained attention due to increasing seizures and involvement in human intoxications which occurred in Europe and Italy in the last years, but currently there is a lack of information about its pharmaco-toxicological effects. With the aim at filling this gap, the present study is endeavoured to (i) evaluate the effects of acute administration of MDPHP (0.01-20 mg/kg; i.p.) on behaviour, cardiorespiratory and cardiovascular parameters in CD-1 male mice, comparing them to those observed after administration of MDPV; (ii) predict the ADMET profile of the two analogues using the Plus ADMET Predictor®; (iii) present clinical data related to MDPHP and MDPV-induced intoxications recorded between 2011 and 2023 by the Pavia Poison Control Centre (PCC) - National Toxicology Information Centre (Istituti Clinici Scientifici Maugeri, IRCCS Pavia, Italy). Our results substantiated that MDPHP and MDPV similarly affect sensorimotor and behavioural responses in mice, importantly increased locomotion and induced aggressive behaviour, and, at higher dosage, increased heart rate and blood pressure. These findings are in line with those observed in humans, revealing severe toxidromes typically characterized by Central Nervous System (CNS) alterations (behavioural/neuropsychiatric symptoms), including psychomotor agitation and aggressiveness, cardiovascular and respiratory disorders (e.g. tachycardia, hypertension, dyspnoea), and other peripheral symptoms (e.g. hyperthermia, acidosis, rhabdomyolysis).

Comparative In Vitro and In Silico Analyses of Phytochemicals From Butea monosperma for Wound-Healing Potential in Human Cells.

Aim The objective of this study is to investigate the phytochemicals present in Butea monosperma and assess their potential for healing wounds using a computational comparative method. Materials and methods The phytochemical substances derived from B. monosperma were examined using a phytochemical test, Fourier-transform infrared (FTIR) spectroscopy, and gas chromatography-mass spectroscopy (GCMS). The chemical structures of these substances were investigated in silico using computational techniques to predict their wound-healing capacity. The molecular docking tests evaluate the binding strengths of the phytochemicals to specific proteins that play a major role in wound-healing mechanisms. The pharmacokinetic features of the substances were evaluated by analyzing their ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles. Results The computer analysis found several phytochemicals from B. monosperma that bind strongly to the proteins for wound healing: compounds such as hexanoic acid, 2,7-dimethyloct-7-en-5-yn-4-yl ester, 1,3,5-pentanetriol, 3-methyl-, and 2-butyne-1,4-diol. The ADMET analysis indicated favorable pharmacokinetic properties for the majority of the identified compounds, with low predicted toxicity. Conclusion Based on the in silico analysis, the phytochemicals in B. monosperma possess significant potential for use in wound-healing applications. These findings required additional in vitro and in vivo studies to confirm the effectiveness and safety of these drugs for improving wound healing. This study emphasizes the potential of B. monosperma as a source of innovative medicinal substances for wound care.

Discovery of azaleatin as a potential allosteric inhibitor for dengue NS2B-NS3 protease using in vitro and in silico studies.

The rise in dengue cases in tropical and sub-tropical areas has become a significant health concern. At present, there is no definitive cure for dengue fever, which underscores the importance of identifying potent inhibitors. Dengue NS2B-NS3 protease is the prime drug target due to its vital function for replication. Quercetin, a flavone, has anti-dengue virus properties but is limited by low bioavailability. Previous studies have shown that methoxy substitution in flavones improves bioavailability and metabolic stability. Azaleatin is a derivative of quercetin with a methoxy substitution at the C5 position, however its ability to inhibit dengue is unknown. In this study, azaleatin was investigated for its inhibition against dengue NS2B-NS3 protease using in vitro and in silico techniques. The fluorescence assay was used to determine the IC50 value and inhibition kinetics. The molecular interaction between azaleatin and NS2B-NS3 was studied using CB-Dock2 and AutoDock Vina. The complex's stability was then analysed using GROMACS. Besides, the ADMETlab 2.0 was utilized to predict pharmacokinetic of the azaleatin. Results showed that azaleatin inhibits dengue NS2B-NS3 protease non-competitively with a Ki of 26.82 µg/ml and an IC50 of 38 µg/ml. Molecular docking indicated binding of the azaleatin to the allosteric pocket of NS2B-NS3 with a docking score of -8.2 kcal/mol. Azaleatin was found stable in the pocket along 100 ns, supporting its inhibitory mode. The compound has favourable pharmacokinetic profiles and conformed to Lipinski's Rule of Five. Taken together, azaleatin inhibits NS2B-NS3 protease in a non-competitive mode, suggesting its potential as safer anti-dengue compound.Communicated by Ramaswamy H. Sarma.

Chemoinformatics Study of Benzodiazepine-1, 2, 3-triazole Derivatives Targeting Butyrylcholinesterase.

This study aims to assess the potential bioactivity of newly designed benzodiazepine-1,2,3-triazole derivatives using in-silico methodologies, with a primary focus on elucidating their inhibitory interactions with the butyrylcholinesterase (BuChE) enzyme, which is implicated in Alzheimer's disease. We employed multiple linear regression (MLR) methods to conduct a quantitative structure-activity relationship (QSAR) analysis on a collection of 31 benzodiazepine-1,2,3-triazole derivatives, with the goal of investigating, assessing, and predicting their activities, as well as designing novel compounds. This approach yielded highly accurate results, with coefficients of determination (R²) of 0.77 and 0.81 for the training and test datasets, respectively. Additionally, the optimized compounds were subjected to an Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis, demonstrating their potential as non-hepatotoxic agents with enhanced absorption and blood-brain barrier permeability. To further validate these findings, the most favorable docking conformations were analyzed using molecular dynamics (MD) simulations with GROMACS software, predicting the stability of the formed complexes. These simulations underscored the critical role of hydrogen bonds in stabilizing the compounds at the BuChE receptor binding site. The results hold great promise for the development of innovative benzodiazepine-1,2,3-triazole derivatives as effective BuChE inhibitors, potentially leading to therapeutic interventions for Alzheimer's disease.

Skin anti-aging potential of Launaea procumbens extract: Antioxidant and enzyme inhibition activities supported by ADMET and molecular docking studies.

Aging is a natural process that occurs in all living organisms. Particularly, the skin embodies aging since it serves as a barrier between the body and its surroundings. Previously, we reported the wound healing effect of Launaea procumbens and identified compounds therein. The study aims to explore the skin anti-aging properties of the plant extract. To that effect, the antioxidant potential of L. procumbens methanolic extract (LPM) was assessed using two complementary DPPH and FRAP assays. The enzyme inhibitory effect of the extract on collagenase, elastase, hyaluronidase, and tyrosinase was evaluated to assess the direct skin anti-aging effects. Similarly, the anti-inflammatory activity was evaluated to explore the indirect anti-aging effects via the assessment of extract inhibitory effects on cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX). In addition, ADMET and molecular docking studies were performed to explore the interaction mechanisms of identified compounds in LPM with target enzymes. LPM demonstrated significant antioxidant activity in DPPH (IC50 = 29.08 µg/mL) and FRAP (1214.67 µM FeSO4/g extract) assays. Plant extract showed significant inhibition of collagenase, elastase, hyaluronidase, and tyrosinase (IC50 = 52.68, 43.76, 31.031, and 37.13 µg/mL, respectively). The extract demonstrated significant COX-2 and 5-LOX inhibition capacity with IC50 values of 8.635 and 10.851 µg/mL, respectively. The molecular docking study revealed the high potential of the identified compounds to bind to the active sites of enzymes crucially involved in the skin aging process. ADMET analysis of the compounds revealed their good absorption, distribution, and metabolism profiles, and they were found to be safe as well. Study findings suggest L. procumbens as a promising source for the development of natural skin anti-aging and antioxidant compounds. This, in turn, may facilitate its incorporation into cosmetic formulations after further investigation.

Investigation of 3-Phenylcoumarin Derivatives as Potential Multi-target Inhibitors for Human Cholinesterases and Monoamine oxidases: A Computational Approach.

Alzheimer's disease (AD) is the predominant etiology of dementia, impacting a global population of approximately 50 million individuals. In the field of medicinal chemistry, there have been notable advancements in the utilization of monoamine oxidase (MAO) and cholinesterase (ChE) inhibitors for the purpose of addressing the neurotransmitter shortage associated with Alzheimer's disease (AD). A selection of previously synthesized 3-Phenylcoumarin derivatives (5a-m) were selected for examination in the pursuit of potential multi-targeting inhibitors of MAO-A, MAO-B, AChE, and BChE. The stability and reactivity of the compounds were investigated through the utilization of density functional theory (DFT) simulations. Subsequently, a CoMFA technique, grounded in 3D-QSAR principles, was employed to construct a model and predict the inhibitory properties of analogues belonging to the class of 3-phenylcoumarin derivatives. Through the application of molecular docking methodologies, we have employed predictive analyses to determine the potential binding interactions and stability of the drugs under investigation. The results obtained from the present investigation indicate that the 3-phenylcoumarin derivatives possess a reactive electronic characteristic that is crucial for their anti-cholinesterase activity. Compound 5a demonstrated a noteworthy binding score with AChE, BChE, MAO-A and MAO-B, respectively, indicating a robust binding affinity.

Investigating mechanistic insights of curcumin in blocking the Interleukin-8 signaling pathway associated with Breast Cancer: An in-silico approach.

Interleukin-8 (IL-8) is a chemokine, a type of signaling molecule that has a role in immunological responses and inflammation. In recent years, IL-8 is additionally related to cancer growth and recurrence. Breast cancer growth, progression, and metastatic development are all linked to IL-8. Breast cancer cells are known to develop faster when IL-8 stimulates their proliferation and survival. It can also cause angiogenesis, or the creation of new blood vessels, which is necessary for tumor nutrition and growth. IL-8 and curcumin have been subjects of interest in drug design, particularly in the context of inflammation-related disorders and cancer. This study aims to give an overview of the role of IL-8. Inhibitor-based treatment approaches were being used to target IL-8 with curcumin. Molecular docking method was employed to find a potential interaction to supress competitive inhibition of IL-8 with curcumin. PASS analysis and ADMET characteristics were also being carried out. In the end, IL-8 complexed with curcumin is chosen for MD simulations. Overall, our results showed that during the simulation, the complex stayed comparatively stable. It is also possible to investigate curcumin further as a possible treatment option. The combined results imply that IL-8 and their genetic alterations can be studied in precision cancer therapeutic treatments, utilizing target-driven therapy and early diagnosis.

α-Glucosidase inhibition of prenylated pyranocoumarins: Kinetics, in silico prediction of their physicochemical properties and molecular docking.

Three naturally occurring prenylated pyranocoumarins, nordentatin (1), dentatin (2), and clausarin (3), isolated from the roots of Clausena excavata (Family Rutaceae), and O-methylclausarin (4) which was obtained by methylation of 3, were investigated for their α-glucosidase inhibitory activity. The mechanism of action and the in silico prediction of their physicochemical and ADMET properties as well as the molecular docking were also studied. Compounds 1-4 exhibited stronger α-glucosidase inhibitory activity than the positive control, acarbose, through a non-competitive mechanism. Among them, 3 exhibited the highest activity, with an IC50 of 8.36 µM, which is significantly stronger than that of acarbose (IC50 = 430.35 µM). The prenyl group on C-3 and the hydroxyl group on C-5 in 3 may play important roles in enhancing the activity. Calculated physicochemical and ADMET parameters of 1-4 satisfied the Lipinski's and Veber's rules. Molecular simulation analysis indicated they are promising drug candidates with no hepatotoxicity. Compound 3 exhibited potent activity in the experiment and demonstrated good drug properties based on the calculations. A molecular docking study revealed that 3 showed H-bonding and π-π stacking interactions with selective Phe321, as well as interactions with thirteen other amino acid residues of the α-glucosidase.

Predicting ADMET Properties from Molecule SMILE: A Bottom-Up Approach Using Attention-Based Graph Neural Networks.

Understanding the pharmacokinetics, safety and efficacy of candidate drugs is crucial for their success. One key aspect is the characterization of absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, which require early assessment in the drug discovery and development process. This study aims to present an innovative approach for predicting ADMET properties using attention-based graph neural networks (GNNs). The model utilizes a graph-based representation of molecules directly derived from Simplified Molecular Input Line Entry System (SMILE) notation. Information is processed sequentially, from substructures to the whole molecule, employing a bottom-up approach. The developed GNN is tested and compared with existing approaches using six benchmark datasets and by encompassing regression (lipophilicity and aqueous solubility) and classification (CYP2C9, CYP2C19, CYP2D6 and CYP3A4 inhibition) tasks. Results show the effectiveness of our model, which bypasses the computationally expensive retrieval and selection of molecular descriptors. This approach provides a valuable tool for high-throughput screening, facilitating early assessment of ADMET properties and enhancing the likelihood of drug success in the development pipeline.

Molecular docking of antidiabetic molecules of libas (Spondias pinnata) fruit and prediction of their pharmacokinetic properties.

Diabetes mellitus is one of the chronic metabolic disorders that affects more than 16 million Filipinos. Proper education, medical intervention, and a good lifestyle can help individuals control and manage this disease. Spondias pinnata is one of the underutilized crops in the Philippines that is well-known for its satisfactory flavor and medicinal properties, including its antidiabetic activity. The quest for a natural and effective drug to manage diseases is a continuous work in progress. Drug discovery and design is a tedious and expensive process. Computer-aided drug design guides the design and makes the process more efficient and less costly. Molecular docking was used to determine the potential antidiabetic compounds from the 48 reported compounds found in S. pinnata fruit. Seven compounds namely squalene (-9.1 kcal/mol), rutin (-9 kcal/mol), catechin (-8.7 kcal/mol), quercetin (-8.5 kcal/mol), tocopherol (-8.4 kcal/mol), myricetin (-8.4 kcal/mol), and ellagic acid (-8.3 kcal/mol) showed binding affinities comparable to those of pioglitazone, a standard drug, with peroxisome proliferator-activated receptor gamma (PPARγ). Tocopherol and catechin showed good ADMET properties. Among the two compounds, catechin passed the four filters for drug-likeness. Thus, catechin could be a potential compound for the development of antidiabetic drugs. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00230-3.

New Triazole-Isoxazole Hybrids as Antibacterial Agents: Design, Synthesis, Characterization, In Vitro, and In Silico Studies.

Novel isoxazole-triazole conjugates have been efficiently synthesized using 3-formylchromone as starting material according to a multi-step synthetic approach. The structures of the target conjugates and intermediate products were characterized by standard spectroscopic techniques (1H NMR and 13C NMR) and confirmed by mass spectrometry (MS). The all-synthesized compounds were screened for their antibacterial activity against three ATCC reference strains, namely Staphylococcus aureus ATCC 25923, Staphylococcus aureus ATCC BAA-44, and Escherichia coli ATCC 25922 as well as one strain isolated from the hospital environment Pseudomonas aeruginosa. The findings indicate that conjugate 7b exhibits a stronger antibacterial response against the tested Escherichia coli ATCC 25922 and Pseudomonas aeruginosa pathogenic strains compared to the standard antibiotics. Furthermore, hybrid compound 7b proved to have a bactericidal action on the Escherichia coli ATCC 25922 strain, as evidenced by the results of the MBC determination. Moreover, the ADMET pharmacokinetic characteristics revealed a favorable profile for the examined compound, as well as a good level of oral bioavailability. Molecular docking and molecular dynamics simulations were performed to explore the inhibition mechanism and binding energies of conjugate 7b with the proteins of Escherichia coli and Pseudomonas aeruginosa bacterial strains. The in silico results corroborated the data observed in the in vitro evaluation for compound 7b.

A novel approach to assessing the antioxidant and anti-diabetic potential of synthesized calcium carbonate nanoparticles using various extracts of Ailanthus altissima.

Calcium carbonate nanoparticles (CaCO3) have been found to exhibit unique properties that show their potential to be used in various therapies. Green synthesis of CaCO3 has been progressively gaining ac-ceptance due to its cost-effectiveness and energy-efficient nature. In the current study, different extracts of Ailanthus altissima were used to synthesize the calcium carbonate nanoparticles the synthesis and characterization of CCNPs were confirmed by using Fourier Transform Infra-Red spectroscopy, UV-Vis spectroscopy, and Scanning Electron Microscopy (SEM). The antioxidant activities (hydrogen peroxide, phosphomolydbenum, and ferric reducing) of calcium carbonate nanoparticles were affirmed by a good range of percentages of inhibition against free radical scavenging. The antidebate assays of CCNPs were observed by in-vitro and in silico approaches in a range at various concentrations while maximum inhibition occurred. In conclusion, the current study depicted that conjugated CaCO3 with A. altissima has a good potential to cure oxidative stress and Type II diabetes and could be used in the future as biogenic nanomedicine for the treatment of other metabolic diseases.