Absorption, Distribution, Metabolism, Excretion And Toxicity Research Articles

Computational Insights into Pharmacokinetic Profiling of Amygdalin: An In-Silico Study

Amygdalin is a naturally occurring cyanogenic glycoside which has been used as an alternative anti-cancer agent despite controversies surrounding its efficacy and safety. This study utilized computational approaches to investigate the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of amygdalin based on its molecular structure. Amygdalin was modeled in ChemBio3D and submitted to SwissADME and admetSAR servers for ADMET parameter prediction. The in-silico simulations indicated suboptimal pharmacological properties for amygdalin, including low lipophilicity, poor bioavailability, minimal blood-brain barrier permeability and non-compliance with drug-likeness criteria. Additional pharmacokinetic modeling through Simcyp suggested rapid clearance and short half-life after intravenous administration.While toxicity was predicted to be low at regular dosages, the overall pharmacological limitations may pose challenges for amygdalin’s efficacy as an anti-cancer therapy. The computational findings provide comprehensive insights into amygdalin’s drug-like behavior and can inform future in vitro/in vivo investigations on this naturally derived compound.

PharmaBench: Enhancing ADMET benchmarks with large language models

Accurately predicting ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties early in drug development is essential for selecting compounds with optimal pharmacokinetics and minimal toxicity. Existing ADMET-related benchmark sets are limited in utility due to their small dataset sizes and the lack of representation of compounds used in drug discovery projects. These shortcomings hinder their application in model building for drug discovery. To address this issue, we propose a multi-agent data mining system based on Large Language Models that effectively identifies experimental conditions within 14,401 bioassays. This approach facilitates merging entries from different sources, culminating in the creation of PharmaBench. Additionally, we have developed a data processing workflow to integrate data from various sources, resulting in 156,618 raw entries. Through this workflow, we constructed PharmaBench, a comprehensive benchmark set for ADMET properties, which comprises eleven ADMET datasets and 52,482 entries. This benchmark set is designed to serve as an open-source dataset for the development of AI models relevant to drug discovery projects.

An Integrative Computational Approach for Design and Evaluation of Novel [1,2,4]triazolo[3,4-b][1,3,4]thiadiazole Analogues as Dual-Action Anti-Retroviral and Anti-Bacterial Agents: Insights into Rational Drug Design Strategies

The development of effective antiretroviral inhibitors (HIV-1 Reverse Transcriptase) and glucosamine-6-phosphate (GlcN6P) agents represent a significant challenge for combating viral infections and related diseases. In this study, we employed a multidisciplinary approach to design and evaluate a series of novel triazole analogs as potential candidates for anti-retroviral and glucosamine-6-phosphate agents. Using molecular docking, we explored the binding interactions between the RSA3 analog and the target proteins implicated in viral replication and glucosamine metabolism. Density functional theory (DFT) employing the 6-311++G(d,p) basis set was utilized for computational analysis, with a subsequent examination of the electronic parameters. The HOMO and LUMO orbitals as well as the molecular electrostatic potential map were investigated using DFT to characterize the reactivity of our molecule. Molecular dynamics simulations were performed to investigate the stability and dynamic behavior of the ligand-protein complex (RSA3) over time (300 ns). Furthermore, we employed MM-GBSA calculations of the compound RSA3 (molecular mechanics generalized band surface area) to estimate the binding free energies (−71.30 ± 7.26 kcal/mol and −67.86 ± 7.09 kcal/mol, respectively) and identified the most promising compounds with high affinity for the target proteins. Additionally, predictive absorption, distribution, metabolism, excretion and toxicity (ADMET) studies of compound RSA3 were conducted to assess its drug-like properties and potential safety profiles of the selected compound. Our results revealed that RSA3 has favorable binding interactions, is a stable complex and has significant binding affinity for target proteins. Moreover, predictive ADMET studies indicated that RSA3 possesses desirable drug-like properties, suggesting its potential for further investigation as an anti-retroviral agent and glucosamine-6-phosphate agent. Overall, this integrative computational approach combining molecular docking, DFT analysis, dynamics simulations, MM-GBSA and predictive ADMET studies provides valuable insights into the design and evaluation of novel triazole analogs with potential therapeutic applications, highlighting the importance of rational drug design strategies in the field of antiretroviral and glucosamine research.

Discovery of Natural Multi‐Target Neuraminidase Inhibitors Anti‐Influenza Virus from Chinese Medicinal Herbs Containing Coumarin: In Silico and In Vitro Experiments

AbstractDuring in silico research, based on molecular docking, dynamics simulation, network pharmacology and ADMET (absorption, distribution, metabolism, excretion, and toxicity) property, 31 potential compounds are obtained from seven Chinese medicinal herbs containing coumarins. Moreover, mechanism researches discover these compounds treat influenza A virus through key targets TLR4, MMP9, and IL6 (high fever, acute respiratory distress syndrome), MAPK1 and MAPK3 (MAPK signaling pathway, viral RNP export and viral protein expression), CASP3 (apoptosis), EP300 and CREBBP (viral myocarditis, chemoattraction of monocytes and macrophages, T cell activation antibody response). Further experimental verification finds that 22 of 31 compounds have various degrees of anti‐influenza virus activities. Moreover, 12 of 22 compounds have better biological activities (IC50=0.1609–54.95 μM) than oseltamivir (IC50=114.3 μM). 3 of 12 compounds have better antioxidant activities (IC50=2.087–3.796 μM) than vitamin C (IC50=5.004 μM). Therefore, ellagic acid, hyperoside, and fraxetin are promising multi‐target lead compounds for influenza virus therapy. Meanwhile, the present study offers compelling evidence for the development of novel antiviral medications.

Design, Synthesis and in Silico Studies of New 2-MethylQuinazolin-4(3H)- Ones Derivatives

The concept of the green chemistry consists in the development of an environmentally friendly approach for organic synthesis using ecological and efficient protocols. In order to develop a methodology that could fit into the green chemistry field, for the synthesis of new quinazolin-4(3H)-ones derivatives via benzoxazinone, the choice was made on the use of both as catalysts, known for their efficiency, and microwave irradiations for time saving.The quinazolinone core and its derivatives form an important class of compounds, as they are present in a large family of products with broad biological activities. They generally display useful therapeutic and pharmacological properties such as anti-inflammatory, anti-convulsant, antihypertensive and antimalarial activity.The derivatives of the 2-metylquinazolin-4(3H)-ones 3a-d series was synthesized from 2- methyl benzoxazin-4(3H)-one 1 and aniline in the presence of H3PW12O40 (PW12) under microwave irradiation and solvent free conditions. The compound structures were established using IR, 1H-NMR, 13C-NMR and mass spectroscopy. The toxicity of the hydrazone derivatives was studied through ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) simulations using ADMET Lab 2.0 server.

Bioinformatic Test and Pharmacokinetic Profile Prediction of Gnetin-C Compound in Melinjo (Gnetum gnemon L.) Seeds Toward Colorectal Cancer

Cancer is one of the unresolved health problems in the world, including Indonesia. One of the most common types of cancer is colorectal cancer. Melinjo (Gnetum gnemon L.) is one of Indonesian local commodities which has many benefits including its potential to be developed as an anticancer agent. Through bioinformatics and molecular docking technology, the aim of this study was to investigate the functions of gnetin-C from melinjo against colorectal cancer. PkCSM database were used to search the ADMET (absorption, distribution, metabolism, elimination and toxicity) properties and stitch-string database were used to identify common genes related to colon cancer. During identification of colon cancer related genes, STAT3 protein showed the highest degree score. Furthermore, molecular docking was carried out to find out the interaction between the STAT3 protein and gnetin c compound found in melinjo seeds. From the docking stage, the pose with the best affinity energy was obtained with a docking score of 1,966 kcal/mol. this shows that the compound gnetin c has the potential to be used as a new anticancer agent from natural ingredients.Keywords: Melinjo, Gnetum gnemon, colon cancer, bioinformatics, molecular docking.

Novel Prodrug Strategies for the Treatment of Tuberculosis.

The emergence of drug-resistant strains of Mycobacterium tuberculosis (M.tb), the causative agent of tuberculosis, is on the rise and increasing antimicrobial resistance is a global threat. This phenomenon necessitates new drug design methods such as a prodrug strategy to develop novel antitubercular agents. The prodrug strategy is a viable and useful means to improve the absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles of pharmacologically active agents. Granulomas are a pathological hallmark of M.tb infection and bear a remarkable resemblance to the tumour microenvironment, including regions of hypoxia. The hypoxic environment observed in the two structures offer an exceptional opportunity to deliver antitubercular agents selectively in a similar manner to hypoxia activated prodrugs in cancer therapy. Nitroimidazoles have been studied extensively as bioactivated prodrugs of cancer, and their suitability as substrates for mammalian reductases highlight their huge potential. This review will discuss the mechanism of action and resistance mechanisms of the current prodrugs used for the treatment of tuberculosis. It will also highlight the potential advantages and challenges of using hypoxia activated prodrugs as a viable strategy to target latent M.tb in hypoxic regions of granulomas.

Profiling of antioxidant properties and identification of potential analgesic inhibitory activities of Allophylus villosus and Mycetia sinensis employing in vivo, in vitro, and computational techniques

Ethnopharmacological relevanceThe traditional use of plants for medicinal purposes, called phytomedicine, has been known to provide relief from pain. In Bangladesh, the Chakma indigenous community has been using Allophylus villosus and Mycetia sinensis to treat various types of pain and inflammation. Aim of the studyThe object of this research is to evaluate the effectiveness of these plants in relieving pain and their antioxidant properties using various approaches such as in vitro, in vivo, and computational techniques. Additionally, the investigation will also analyse the phytochemicals present in these plants. Materials and methodsWe conducted in vivo analgesic experiment on Swiss albino mice and in-silico inhibitory activities on COX-2 & 15-LOX-2 enzymes. Assessment of DPPH, Anti Radical Activities (ARA), FRAP, H2O2 Free Radical Scavenging, Reducing the power of both plants performed significant % inhibition with tolerable IC50. Qualitative screening of functional groups of phytochemicals was précised by FTIR and GC-MS analysis demonstrated phytochemical investigations. ResultsThe ethyl acetate (EtOAc) fractioned Mycetia sinensis extract as well as the ethanoic extract and all fractioned extracts of Allophylus villosus have reported a significant percentage (%) of writhing inhibition (p < 0.05) with the concentrated doses 250 mg as well as 500 mg among the Swiss albino mice for writhing observation of analgesic effect. In the silico observation, a molecular-docking investigation has performed according to GC-MS generated 43 phyto-compounds of both plants to screen their binding affinity by targeting COX-2 and 15-LOX-2 enzymes. Consequently, in order to assess and ascertain the effectiveness of the sorted phytocompounds, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) investigation, DFT (Density-functional theory) by QM (Quantum mechanics), and MDS (Molecular dynamics simulation) were carried out. As the outcome, compounds like 5-(2,4-ditert-butylphenoxy)-5-oxopentanoic acid; 2,4-ditert-butylphenyl 5-hydroxypentanoate; 3,3-diphenyl-5-methyl-3H-pyrazole; 2-O-(6-methylheptan-2-yl) 1-O-octyl benzene-1,2-dicarboxylate and dioctan-3-yl benzene-1,2-dicarboxylate derived from the ethnic plant A. villosus and another ethnic plant M. sinensis extracts enchants magnificent analgesic inhibitions and performed more significant drug like activities with the targeted enzymes. ConclusionsPhytocompounds from A. villosus &M. sinensis exhibited potential antagonist activity against human 15-lipoxygenase-2 and cyclooxygenase-2 proteins. The effective ester compounds from these plants performed more potential anti-nociceptive activity which could be used as a drug in future.

Synthesis, molecular docking, drug‐likeness analysis, and ADMET prediction of nickel and zinc tetraphenyl‐porphyrin complexes as possible antioxidant agents

AbstractNickel tetraphenyl‐porphyrin (NiTPPH₂) and zinc tetra(4‐methophenyl)‐porphyrin (ZnTPPH₂(p‐methyl)) were successfully synthesized and characterized using 1H NMR spectroscopy. Their antioxidant activities and interactions with the superoxide anion radical () were evaluated using cyclic voltammetry. Remarkably, NiTPPH₂ displayed superior antioxidant activity with an IC50 value of 54.57 μg mL−1, significantly outperforming α‐tocopherol (IC50 = 353.27 μg mL−1), indicating its potential as a potent antioxidant. Binding free energy calculations demonstrated that electrostatic interactions predominantly govern the binding, with values of −23.47 kJ mol−1 for NiTPPH₂ and −22.50 kJ mol−1 for ZnTPPH₂(p‐methyl). These values suggest robust binding affinities with . Quantum chemical parameters, obtained through density functional theory (DFT), showed a strong correlation with experimental results, validating the computational approach. Additionally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and drug‐likeness assessments, alongside molecular docking studies, highlighted favorable pharmacokinetic profiles and binding affinities. These findings underscore the potential of NiTPPH₂ and ZnTPPH₂(p‐methyl) as promising candidates for antioxidant therapy, exhibiting drug‐like properties and favorable pharmacokinetics. This research advances the understanding of these porphyrin derivatives and their application in the development of novel antioxidant therapeutics.

Exploration of cytotoxicity of iodoquinazoline derivatives as inhibitors of both VEGFR-2 and EGFRT790M: Molecular docking, ADMET, design, and syntheses.

Novel inhibitors of epidermal growth factor receptor (EGFR)T790M/vascular endothelial growth factor receptor-2 (VEGFR-2) were synthesized based on the iodoquinazoline scaffold linked to different heteroaromatic, aromatic, and/or aliphatic moieties. The novel derivatives were in vitro examined for anticancer activities against A549, HCT116, michigan cancer foundation-7 (MCF-7), and HepG2 cells. Molecular modeling was applied to discover their orientation of binding with both VEGFR-2 and EGFR active sites. Compounds 8d, 8c, 6d, and 6c indicated the highest cytotoxicity with IC50 = 6.00, 6.90, 6.12 and 6.24 µM, 7.05, 7.35, 6.80, and 6.80 µM, 5.75, 7.50, 6.90, and 6.95 µM, and 6.55, 7.88, 7.44, and 7.10 µM against the A549, HepG2, HCT116, and MCF-7 cell lines, correspondingly. The cytotoxicity against normal VERO (normal african green monkey kidney cells) of the extremely active eight compounds 6a-d and 8a-d was evaluated. Our compounds exhibited low toxicity concerning normal VERO cells with IC50 = 45.66-51.83 μM. Furthermore, inhibition assays for both the EGFRT790M and VEGFR-2 enzymes were done for all compounds. Remarkable inhibition of EGFRT790M activity was achieved with compounds 6d, 8d, 6c, and 8c at IC50 = 0.35, 0.42, 0.48, and 0.50 µM correspondingly. Moreover, remarkable inhibition of VEGFR-2 activity was achieved with compounds 8d, 8c, 6d, and 6c at IC50 = 0.92, 0.95, 1.00, and 1.20 µM correspondingly. As planned, derivatives 6d, 8d, 6c, and 8c presented exceptional inhibition of both EGFRT790M/VEGFR-2 activities. Finally, in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies were made for the highly active four compounds 6c, 6d, 8c, and 8d in comparison with erlotinib and sorafenib as reference standards.

Cucumis melo compounds: A new avenue for ALR-2 inhibition in diabetes mellitus

Diabetes mellitus (DM) is a prominent contributor to morbidity and mortality in developed nations, primarily attributable to vascular complications such as atherothrombosis occurring in the coronary arteries. Aldose reductase (ALR2), the main enzyme in the polyol pathway, catalyzes the conversion of glucose to sorbitol, leading to a significant buildup of reactive oxygen species in different tissues. It is therefore a prime candidate for therapeutic targeting, and extensive study is currently underway to discover novel natural compounds that can inhibit it. Cucumis melo (C. melo) has a long history as a lipid-lowering ethanopharmaceutical plant. In this study, compounds derived from C. melo were computationally evaluated as possible lead candidates. Various computational filtering methods were employed to assess the drug-like properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles of the compounds. The compounds were subsequently addressed to analysis of their interactions, molecular docking, and molecular dynamics simulation studies. When compared to the conventional therapeutic compounds, three compounds exhibited enhanced binding affinity and intra-molecular residue interactions, resulting in increased stability and specificity. Consequently, four potent inhibitors, namely PubChem CIDs 119205, 65373, 6184, and 332427, have been identified. These inhibitors exhibit promising potential as pharmacological targets for the advancement of novel ALR-2 inhibitors.

Investigation of the chemical composition, antioxidant, and enzyme inhibitory activities of Ononis natrix subsp. natrix, performance of in silico analyses of its major compounds

In this study, phytochemical composition, antioxidant, anti-Alzheimer, anti-diabetic, tyrosinase activities and in silico analyses of methanol, ethyl acetate and water extracts obtained from the aerial parts of Ononis natrix subsp. natrix, which is naturally distributed in the flora of Mediterranean area, were performed. The extracts were first analyzed for their phytochemical composition using quantitative chromatographic techniques. As a result of spectrophotometric analyses (Agilent Technologies 1260 Infinity liquid chromatography system with 6420 Triple Quad mass spectrometer), it was determined that the methanol extract was the richest in terms of total phenolics (74.60 mg GAEs/g dry weight), while the water extract was found to be richest in terms of total flavonoids (27.88 mg REs/g dry weight). As a result of quantitative phytochemical analyses, taxifolin, hyperoside, eriodictiol and quercetin were found to be present in high concentrations. As a result of quantitative phytochemical analyses, taxifolin, hyperoside, eriodictyol, and quercetin were found to be present in high concentrations. The methanol extract displayed higher activity in all test systems except for DPPH radical scavenging activity. The results from the phosphomolybdenum, ABTS radical scavenging, CUPRAC, FRAP, and metal chelating tests for the methanol extract were: 1.71, 1.07, 1.02 mg, 0.91, and 1.47 mg /ml, respectively. When the AChE, BChE and α-glucosidase inhibitory activity tests were evaluated in terms of IC50, the methanol extract showed higher activity with IC50 values of 1.02, 1.70 and 1.02 mg/ml, respectively. In contrast, the ethyl acetate extract showed higher activity in the tyrosinase and α-amylase tests, with IC50 values of 1.42 and 1.78 mg/ml, respectively. It was found that there was a strong correlation between the total phenolic and flavonoid contents of the extracts and their antioxidant and enzyme inhibitor activities. The study also conducted in silico molecular docking, MM/GBSA, drug-likeness, and ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) analyses to describe the pharmacokinetic and pharmacodynamic properties of bioactive compounds with potential pharmacological action present in O. natrix subsp. natrix extracts. The compounds studied were eriodictyol, hyperoside, quercetin, and taxifolin. Researchers have found that, based on molecular docking, MM/GBSA, and key interactions within the enzyme active sites, hyperoside may inhibit α-amylase and BChE, eriodictyol may inhibit α-glucosidase and AChE, and both hyperoside and eriodictyol may inhibit tyrosinase. The presented data on antioxidant and enzyme inhibitory activity, along with in silico studies, represent the first recorded findings in the literature.

GR-pKa: a message-passing neural network with retention mechanism for pKa prediction.

During the drug discovery and design process, the acid-base dissociation constant (pKa) of a molecule is critically emphasized due to its crucial role in influencing the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties and biological activity. However, the experimental determination of pKa values is often laborious and complex. Moreover, existing prediction methods exhibit limitations in both the quantity and quality of the training data, as well as in their capacity to handle the complex structural and physicochemical properties of compounds, consequently impeding accuracy and generalization. Therefore, developing a method that can quickly and accurately predict molecular pKa values will to some extent help the structural modification of molecules, and thus assist the development process of new drugs. In this study, we developed a cutting-edge pKa prediction model named GR-pKa (Graph Retention pKa), leveraging a message-passing neural network and employing a multi-fidelity learning strategy to accurately predict molecular pKa values. The GR-pKa model incorporates five quantum mechanical properties related to molecular thermodynamics and dynamics as key features to characterize molecules. Notably, we originally introduced the novel retention mechanism into the message-passing phase, which significantly improves the model's ability to capture and update molecular information. Our GR-pKa model outperforms several state-of-the-art models in predicting macro-pKa values, achieving impressive results with a low mean absolute error of 0.490 and root mean square error of 0.588, and a high R2 of 0.937 on the SAMPL7 dataset.

Identification of new inhibitors for the avian H1N1 virus through molecular docking and dynamic simulation approaches

The new variant of influenza A virus is known as avian H1N1 subtype which particularly affects birds, and poultry. However, recently it is affecting in human, and creating global health problem. So, this research has studied the myricetin derivatives as novel therapeutic agents that target the Hemagglutinin Protein in Avian H1N1 Virus. The study is focused on addressing the critical need for effective antiviral agents through computational drug design approaches. The research assesses the binding affinities, quantum calculation, molecular dynamic simulation, binding free energy calculation, electronic characteristics, DCCM, PCA and stability of myricetin derivatives with the hemagglutinin protein. This extensive investigation has documented that all the compounds showed outstanding binding affinities, more precisely compounds like 03 and 47, which show better binding energies than the conventional antiviral Tamiflu. Furthermore, the reactivity, pharmacokinetics, and stability, molecular dynamics simulations, ADMET characteristics, and quantum chemical descriptors are investigated, and they all are satisfied by favorable drug like properties. Besides that, this research highlights the significance of electrical characteristics, dipole moment, and hydrogen bonding in developing efficient antiviral medications. In addition, the myricetin derivatives show promise for oral delivery based on ADMET (absorption, distribution, metabolism, excretion, and toxicity) characteristics. Finally, the molecular dynamics simulations show that the ligand-protein complexes are stable and flexible over the MD simulation of 100 ns. Although, the discovered compounds show potential interactions with the avian H1N1 influenza A virus, with outstanding binding affinity, however, it is still crucial needed to perform experimental validation in near future.

Quantum chemical investigations, Hirschfeld surface analysis, FMO, MESP, topology analyses, in-silico analysis and pharmacokinetics properties of 3-chloro-N-(4-hydroxy-3-methoxy-benzyl)-2,2-dimethyl propanamide [CHMBDP]

This article reports a comprehensive theoretical investigation of 3-chloro-n-(4-Hydroxy-3-Methoxy-Benzyl)-2,2-Dimethyl Propenamide (CHMBDP). Hirshfeld surface analysis provided a detailed visualization of intermolecular interactions within the crystal structure of CHMBDP. Analyses of Molecular Electrostatic Potential (MESP), Electron Localization Function (ELF), Localized Orbital Locator (LOL), and Reduced Density Gradient (RDG) offered insights into the compound’s reactivity and stability. The energies of the Highest Occupied Molecular Orbital (HOMO) and the Lowest Unoccupied Molecular Orbital (LUMO) indicated significant charge transfer within the molecule. In-silico analysis explored the compound’s interactions with TRPV1 (Transient Receptor Potential Vanilloid subtype 1), DNA, and BSA (Bovine Serum Albumin). The pharmacokinetic properties of CHMBDP were assessed using the Swiss ADME online tool to interpret its ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) characteristics. Overall, this study presents a thorough computational investigation of CHMBDP, characterizing its structure, properties, and potential applications.

Computational Insights into Chromene/pyran Derivatives: Molecular Docking, ADMET Studies, DFT Calculations, and MD Simulations as Promising Candidates for Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative condition characterized by both motor and non-motor symptoms. Although PD is commonly associated with a decline of dopaminergic neurons in the substantia nigra, other diagnostic criteria and biomarkers also exist. In the search for novel therapeutic agents, chromene and pyran derivatives have shown potential due to their diverse pharmacological activities. This study utilizes a comprehensive computational approach to investigate the viability of chromene/pyran compounds as potential treatments for PD. The drug-likeness characteristics of these molecules were analyzed using ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) studies. Molecular docking was performed against PDB ID: 2V5Z. The best three molecules chosen were compound 7, compound 24, and compound 67 have a binding energy of -6.7, -8.6, and -10.9 kcal/mol. Molecules demonstrating positive blood-brain barrier permeability, good solubility, and favorable binding affinity were further evaluated using Density Functional Theory (DFT) calculations and Molecular Dynamics (MD) simulations to assess their electronic structure and stability. DFT calculations indicated that molecule 82 has a dipole moment of 15.70 D. RMSD and RMSF results confirmed the stability of the complexes over a 100 ns simulation, with a maximum of 3 hydrogen bonds formed.

In Silico Drug Repurposing Against PSMB8 as a Potential Target for Acute Myeloid Leukemia Treatment.

PSMB8 emerges as a prominent gene associated with cancer survival, yet its potential therapeutic role in acute myeloid leukemia (AML) remains unexplored within the existing literature. The principal aim of this study is to systematically screen an expansive library of molecular entities, curated from various databases to identify the prospective inhibitory agents with an affinity for PSMB8. A comprehensive assortment of molecular compounds obtained from the ZINC15 database was subjected to molecular docking simulations with PSMB8 by usingtheAutoDock tool in PyRx (version 0.9.9) to elucidate binding affinities. Following the docking simulations, a select subset of molecules underwent further investigation through comprehensive ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis employing AdmetSar and SwissADME tools. Finally, RMSD, RMSF, Rg, and H bond analyses were conducted via GROMACS to determine the best conformationally dynamic molecule that represents the candidate agent for the study. Following rigorous evaluation, Adozelesin, Fiduxosin, and Rimegepant have been singled out based on considerations encompassing bioavailability scores, compliance with filter criteria, and acute oral toxicity levels. Additionally, ligand interaction analysis indicates that Adozelesin and Fiduxosin exhibit an augmented propensity for hydrogen bond formation, a factor recognized for its facilitative role in protein-ligand interactions. After final analyses, we report that Fiduxosin may offera treatment possibility by reversing the low survival rates caused by PSMB8 high activation in AML. This study represents a strategic attempt to repurpose readily available pharmaceutical agents, potentially obviating the need for de novo drug development, and thereby offering promising avenues for therapeutic intervention in specific diseases.

Preclinical tests for salicylhydrazones derivatives to explore their potential for new antituberculosis agents

PurposeThis study target the synthesis of 22 salicylhydrazones derivatives to apply in vitro screening to explore their potential in the search for new anti-TB prototypes drugs. MethodsThe minimum inhibitory concentration (MIC) were evaluated against Mycobacterium tuberculosis (Mtb) H37Rv and clinical isolates. Drug combination assay, cytotoxicity assay, ethidium bromide accumulation assay (EtBr) and in silico analysis regarding the absorption, distribution, metabolism, excretion and toxicity (ADMET) and pharmacological properties were also performed. ResultsThree most promising compounds were selected (10, 11 and 18) to proceed with screening tests. Compound 18 presented the lowest MIC value (0.49 μg/mL) against Mtb H37Rv strain, followed by compounds 11 (3.9 μg/mL) and 10 (7.8 μg/mL). All compounds showed activity against drug susceptible and resistant clinical isolates. Cytotoxicity results were promising for all salicylhydrazones, with SI values up to 4,205 for compound 18. The derivative 10 was the only one that demonstrated a non-promising cytotoxicity scenario for a single cell line. All derivatives showed an additive effect (FICI >0.5 to 4.0) in combination with isoniazid, ethambutol and rifampicin. ConclusionAll salicylhydrazones showed potential in the screening tests performed in this study and compound 18 stood out due to its activity against susceptible and resistant bacilli at low concentrations and low cytotoxicity.

4D-QSAR, ADMET properties, and molecular dynamics simulations for designing N-substituted urea/thioureas as human glutaminyl cyclase inhibitors

Human glutaminyl cyclase (hQC) inhibitors have great potential to be used as anti- Alzheimer's disease (AD) agents by reducing the toxic pyroform of β-amyloid in the brains of AD patients. The four-dimensional quantitative structure activity relationship (4D-QSAR) model of N-substituted urea/thioureas was established with satisfying predictive ability and statistical reliability (Q2 = 0.521, R2 = 0.933, R2prep = 0.619). By utilizing the developed 4D-QSAR model, a set of new N-substituted urea/thioureas was designed and evaluated for their Absorption Distribution Metabolism Excretion and Toxicity (ADMET) properties. The results of molecular dynamics (MD) simulations, Principal component analysis (PCA), free energy landscape (FEL), dynamic cross-correlation matrix (DCCM) and molecular mechanics generalized Born Poisson-Boltzmann surface area (MM-PBSA) free energy calculations, revealed that the designed compounds were remained stable in protein binding pocket and compounds b ∼ f (−35.1 to −44.55 kcal/mol) showed higher binding free energy than that of compound 14 (−33.51 kcal/mol). The findings of this work will be a theoretical foundation for further research and experimental validation of urea/thiourea derivatives as hQC inhibitors.

DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery.

Artificial intelligence (AI)-aided drug design has demonstrated unprecedented effects on modern drug discovery, but there is still an urgent need for user-friendly interfaces that bridge the gap between these sophisticated tools and scientists, particularly those who are less computer savvy. Herein, we present DrugFlow, an AI-driven one-stop platform that offers a clean, convenient, and cloud-based interface to streamline early drug discovery workflows. By seamlessly integrating a range of innovative AI algorithms, covering molecular docking, quantitative structure-activity relationship modeling, molecular generation, ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction, and virtual screening, DrugFlow can offer effective AI solutions for almost all crucial stages in early drug discovery, including hit identification and hit/lead optimization. We hope that the platform can provide sufficiently valuable guidance to aid real-word drug design and discovery. The platform is available at https://drugflow.com.