Absorption, Distribution, Metabolism, Excretion Research Articles

Investigations on Growth, Characterization, NCI-RDG, AIM, Molecular Docking and In-Silico ADME Properties of 1,2-Benzene Dicarboxylic Acid Anhydride

Superior single crystal of 1,2-benzene dicarboxylic acid anhydride additionally called Phthalic anhydride (PAN) was developed via solution growth at low temperatures. Single crystal X-ray diffraction investigation revealed the crystal system and unit cell characteristics. The phase stability and crystalline nature were uncovered by powder X-ray diffraction analysis. FT-IR examination was done for the titular material so as to survey the various functional groups. With the use of the VEDA program's relevant resources, vibrational assignments have been made on the concept of Potential Energy Distribution (PED). Density Functional Theory (DFT) was employed to smooth out the molecular structure of PAN and was additionally utilized to consider FT-IR spectrum at molecular level. Non covalent interactions reduced density gradient (NCI-RDG) analysis has been used for the prediction of the weak interaction in the actual space in terms of the electron density along with its derivatives for PAN. Atoms in Molecules (AIM) analysis was carried for out for PAN. The docking research of the small molecule (PAN) with target protein confirmed that this is a great molecule which docks nicely with numerous targets associated with Hypoxia Inducible Factor 1-α. The absorption, distribution, metabolism, excretion (ADME) characteristics have been calculated with the assist of online server preADMET.

Antibacterial [Zn(nicotinamide)2Cl2] complex for the treatment of skin conditions: An experimental-theoretical study of physicochemical, microbiological and in silico pharmacokinetic properties

A dichlorobis(nicotinamide)zinc(II) complex, [Zn(nicotinamide)2Cl2], was crystallized through the slow evaporation method, and its vibrational, electronic, structural, and thermal properties have been characterized. Density functional theory (DFT) was used for the accurate analysis of intramolecular vibrational modes, obtaining chemical reactivity indices and comparative studies of geometric and electronic parameters, including solvation effects in methanol, ethanol, and water, as well as in vacuum. Additionally, the nature and strength of the bonds associated with the coordination sphere (Cl–Zn and N–Zn) were elucidated from the quantum theory of atoms in molecules and natural bond orbital analyses. Powder X-ray diffraction showed that the coordination compound belongs to a monoclinic symmetry with P21/a (C2h5) space group. Thermal analyses revealed that the material is stable up to 200 °C. From DFT calculations, the complex is chemically more stable in solvents compared to vacuum conditions, with the aqueous medium offering greater stability. The chemical stability was also analyzed by infrared and Raman spectroscopy, with the results showing spectral changes mainly for the vibrational spectra obtained in methanol, ethanol, and water against those obtained in vacuum. Biological experiments showed the complex antibacterial activity against Gram-positive and Gram-negative bacteria, mainly against the Cutibacterium acnes ATCC 6919 strain. A computational study of the absorption, distribution, metabolism, excretion (ADME), and drug-likeness were calculated to support the experimental data.

Absorption Distribution Metabolism Excretion and Toxicity Property Prediction Utilizing a Pre-Trained Natural Language Processing Model and Its Applications in Early-Stage Drug Development.

Machine learning techniques are extensively employed in drug discovery, with a significant focus on developing QSAR models that interpret the structural information of potential drugs. In this study, the pre-trained natural language processing (NLP) model, ChemBERTa, was utilized in the drug discovery process. We proposed and evaluated four core model architectures as follows: deep neural network (DNN), encoder, concatenation (concat), and pipe. The DNN model processes physicochemical properties as input, while the encoder model leverages the simplified molecular input line entry system (SMILES) along with NLP techniques. The latter two models, concat and pipe, incorporate both SMILES and physicochemical properties, operating in parallel and with sequential manners, respectively. We collected 5238 entries from DrugBank, including their physicochemical properties and absorption, distribution, metabolism, excretion, and toxicity (ADMET) features. The models' performance was assessed by the area under the receiver operating characteristic curve (AUROC), with the DNN, encoder, concat, and pipe models achieved 62.4%, 76.0%, 74.9%, and 68.2%, respectively. In a separate test with 84 experimental microsomal stability datasets, the AUROC scores for external data were 78% for DNN, 44% for the encoder, and 50% for concat, indicating that the DNN model had superior predictive capabilities for new data. This suggests that models based on structural information may require further optimization or alternative tokenization strategies. The application of natural language processing techniques to pharmaceutical challenges has demonstrated promising results, highlighting the need for more extensive data to enhance model generalization.

Novel Anthraquinone-Based Benzenesulfonamide Derivatives and Their Analogues as Potent Human Carbonic Anhydrase Inhibitors with Antitumor Activity: Synthesis, Biological Evaluation, and In Silico Analysis.

In this study, we designed two series of novel anthraquinone-based benzenesulfonamide derivatives and their analogues as potential carbonic anhydrase inhibitors (CAIs) and evaluated their inhibitory activities against off-target human carbonic anhydrase II (hCA II) isoform and tumor-associated human carbonic anhydrase IX (hCA IX) isoform. Most of these compounds exhibited good inhibitory activities against hCA II and IX. The compounds that exhibited the best hCA inhibition were further studied against the MDA-MB-231, MCF-7, and HepG2 cell lines under hypoxic and normoxic conditions. Additionally, the compounds exhibiting the best antitumor activity were subjected to apoptosis and mitochondrial membrane potential assays, which revealed a significant increase in the percentage of apoptotic cells and a notable decrease in cell viability. Molecular docking studies were performed to demonstrate the presence of numerous hydrogen bonds and hydrophobic interactions between the compounds and the active site of hCA. Absorption, distribution, metabolism, excretion (ADME) predictions showed that all of the compounds had good pharmacokinetic and physicochemical properties.

Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations.

The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRASG12D) mutation, a prevalent oncogenic driver in cancer, represents a significant unmet need in precision medicine. In this study, an integrated computational approach combining structure-based virtual screening and molecular dynamics simulation was employed to identify novel noncovalent inhibitors targeting the KRASG12D variant. Through virtual screening of over 1.7 million diverse compounds, potential lead compounds with high binding affinity and specificity were identified using molecular docking and scoring techniques. Subsequently, 200 ns molecular dynamics simulations provided critical insights into the dynamic behavior, stability, and conformational changes of the inhibitor-KRASG12D complexes, facilitating the selection of lead compounds with robust binding profiles. Additionally, in silico absorption, distribution, metabolism, excretion (ADME) profiling, and toxicity predictions were applied to prioritize the lead compounds for further experimental validation. The discovered noncovalent KRASG12D inhibitors exhibit promises as potential candidates for targeted therapy against KRASG12D-driven cancers. This comprehensive computational framework not only expedites the discovery of novel KRASG12D inhibitors but also provides valuable insights for the development of precision treatments tailored to this oncogenic mutation.

Vibrational spectra, molecular structure, electronic, pharmaceutical and bonding nature of (4S)-4-(3,4-dihydroxyphenyl)-1,2,3,4-tetrahydroisoquinoline-7,8-diol - anti hypertension agent

Several factors, including environment, behaviours, and heredity, influence the development of hypertension. The title compound dopamine D1 receptor agonist named (4S)-4-(3,4-dihydroxyphenyl)-1,2,3,4-tetrahydroisoquinoline-7,8-diol (4S4D4T) is one of the most important neurotransmitters associated with numerous neural disorders. Using DFT and quantum chemical simulations, the vibrational, electrical, and structural possessions of the heading compound were predicted. To carry out the quantum computational investigations, a highly compatible method entitled B3LYP basis set was adopted. Vibrational Modes of functional groups with PED values were calculated using VEDA software to compute geometric dimensions and assign fundamental vibrations. Using gas and solvent phases, MEP differentiates between nucleophilic and electrophilic sites and creates distribution for the charge of the molecules. The observed wavelength with (TDSCF) UV–Vis spectra for the various solvents phases were compared. The NBO approach provides an understanding of the electron delocalization that results from hyperconjugation. FUKUI analysis is used to determine the area of site reaction. Electron density's topological analysis was carried out using the QTAIM theory. The ADME (Absorption, Distribution, Metabolism, Excretion) profiles are produced with the Swiss ADME online tool. In summary, this dissertation offers a thorough examination that evaluates the impact of particular pharmaceuticals on solvation and enzyme efficiency using a combination of spectral and quantitative computing methodologies. Therefore, plans for further research can profit immensely by the information gathered. The results of protein-ligand docking using the Auto Dock method with various proteins suggest that the molecule has pharmaceutical properties against receptors.

Development and evaluation of new oxindole derivatives as potential anti-tubercular agents

Tuberculosis (TB), which affects the lungs and other parts of the body, claims the lives of around 3 million people. Indolin-2-one derivatives were identified as a novel anti-tubercular series from Microplate Alamar Blue Assay (MABA) method, along with its synthesis, characterisation, molecular docking, and molecular dynamic simulations. The enzyme decaprenylphosphoryl-β-D-ribose 20-oxidase (DprE1) demonstrated high binding interaction energies associated with these compounds, which were investigated through the use of the docking technique. A conventional dynamic simulation study lasting 20 ns was used to assess the interaction's stability. The parameters derived from the trajectories of molecular dynamic simulation were computed and validated with respect to the stability of the protein-ligand complex under dynamic conditions. The absorption-distribution-metabolism-excretion (ADME) values are favourable for all of the synthesized compounds. After testing each novel compound for in vitro anti-mycobacterial activity against Mycobacterium tuberculosis H37Rv (ATCC27294), the most promising lead analogues were 9e (MIC: 1.56 μg/mL), 13b (MIC: 3.125 μg/mL), and 13e (MIC: 3.125 μg/mL). In this study, we have designed and produced new 5-substituted Oxindole derivatives as anti-tubercular drugs through the application of docking and molecular dynamic modeling. Given the increasing demand for novel antibiotics and the ensuing urgent need for novel anti-TB medications, we think the currently reported oxindole derivatives of DprE1 inhibitors present an excellent possibility for future optimization.

Design, Virtual Screening, Molecular Docking, ADME and Cytotoxicity Studies of 1,3,5-Triazine Containing Heterocyclic Scaffolds as Selective BRAF Monomeric, Homo and Heterodimeric Inhibitors.

v-RAF murine sarcoma viral homolog B1 (BRAF) is one of the most frequently mutated kinases in human cancers. BRAF exhibits three classes of mutations: Class I monomeric mutants (BRAFV600), class II BRAF homodimer mutants (non-V600), and class III BRAF heterodimers (non-V600). In this manuscript, the protein-ligand interaction site of all three mutants: BRAF monomer, BRAF homodimer BRAF2:14-3-32, and BRAF heterodimer BRAF:14-3-32:MEK (Mitogen extracellular Kinase) has been discussed. FDA-approved drugs still have limitations against all three classes of mutants, especially against the second and third classes. Using the DesPot grid model, 1114 new compounds were designed. Using virtual screening, the three PDB Ids 4XV2 for monomers, 7MFF for homodimers, and 4MNE for heterodimers were used for 1114 newly designed compounds. Dabrafenib, encorafenib, sorafenib and vemurafenib were included as standard drugs. The top 10 hit molecules were identified for each protein. Additional binding studies were performed using molecular docking studies on the protein-ligand site of each PDB identifier. Absorption, distribution, metabolism, excretion (ADME) and toxicity studies were also performed. It was identified that top-hit molecules had better binding and interaction activity than standard in all three classes of mutants.

Design, synthesis, biological evaluations and in silico studies of N-substituted 2,4-thiazolidinedione derivatives as potential a-glucosidase inhibitors

Diabetes mellitus is considered as one of the principal global health urgencies of the twenty first century. In the present investigation, novel N-substituted 2,4-thiazolidinedione derivatives were designed, synthesized, and characterized by spectral techniques. All the newly synthesized N-substituted 2,4-thiazolidinedione derivatives were tested for in vitro α-glucosidase inhibitory activities and compounds A-12 and A-14 were found to be the most potent which were further subjected to in-vivo disaccharide loading test. The most potent compound was also found to be non-toxic in cytotoxicity studies. Further, docking studies were carried out to investigate the binding mode and key interactions with amino acid residues of α-glucosidase. Molecular dynamic simulations studies for the compounds acarbose, A2, A12, and A14 were done with α-glucosidase protein. Further, ΔG was calculated for acarbose, A2, A12, and A14. In silico studies and absorption, distribution, metabolism, excretion (ADME) prediction studies were also executed to establish the ‘druggable’ pharmacokinetic profiles. Here, we have developed novel N-substituted TZD analogues with different alkyl groups as α-glucosidase inhibitors.Communicated by Ramaswamy H. Sarma

The anticancer potential of chemical constituents of Moringa oleifera targeting CDK-2 inhibition in estrogen receptor positive breast cancer using in-silico and in vitro approches

Most of the breast cancers are estrogen receptor-positive recurring with a steady rate of up to 20 years dysregulating the normal cell cycle. Dinaciclib is still in clinical trials and considered as a research drug against such cancers targeting CDK2.The major goal of this study was to identify the potential inhibitors of CDK-2 present in Moringa oleifera for treating hormonal receptor positive breast cancers. For this purpose, in silico techniques; molecular docking, MM-GBSA and molecular dynamics simulations were employed to screen Moringa oleifera compounds and their anticancer potential was determined against CDK-2 protein targets. Among 36 compounds of Moringa oleifera reported in literature, chlorogenic acid (1), quercetin (2), ellagic acid (3), niazirin (4), and kaempferol (5) showed good affinity with the target. The interaction of the compounds was visualized using PYMOL software. The profiles of absorption, distribution, metabolism, excretion (ADME) and toxicity were determined using SWISS and ProTox II webservers. The MTT assay was performed in-vitro using MCF-7 cancer cell lines to validate the anticancer potential of Moringa oleifera leaf extract.MTT assay results revealed no significant change in proliferation of Mcf-7 cells following 24 h treatment with fraction A (petroleum ether). However, significant antiproliferative effect was observed at 200 µg/mL dose of fraction B (ethyl acetate) and cell viability was reduced to 40%.In conclusion, the data suggested that all the compounds with highest negative docking score than the reference could be the potential candidates for cyclin dependent kinase-2 (CDK-2) inhibition while ellagic acid, chlorogenic acid and quercetin being the most stable and potent inhibitors to treat estrogen receptor positive breast cancer targeting CDK-2. Moreover, the data suggested that further investigation is required to determine the optimum dose for significant antiproliferative effects using in-vivo models to validate our findings of in-silico analysis.

In silico approaches for the identification of novel ULK1 inhibitors: pharmacophore model, molecular docking and molecular dynamics simulations

The serine/threonine kinase unc-51-like autophagy activating kinase 1 (ULK1) has been regarded as an attractive target for tumor therapy. In this study, in silico approaches, such as the pharmacophore-based virtual screening strategy, molecular docking and molecular dynamics (MD) simulations, were applied to develop novel potential ULK1 inhibitors. The pharmacophore models based on known aminopyrimidine ULK1 inhibitors were constructed to screen the dataset of 1.68 million compounds, which were obtained via screening the 2.30 million compounds in ChEMBL database by Lipinski’s rule of five. Seven novel compounds and 1 known ULK1 inhibitor stand out for the strong virtual biological activity by molecular docking, cluster analysis, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation and Absorption Distribution Metabolism Excretion Toxicity (ADMET) prediction. Their results of MD included principal component analysis (PCA) and Free Energy Landscapes surface (FELs) indicated that the protein–ligand complex was stable in simulated trajectories of 100 ns. The binding free energy (BFE) calculations showed that a total of 6 novel compounds (CL130, CL834, CL961, CL966, CL163 and CL329) with the stable binding state and stronger BFE (−61.17 to −37.01 kcal/mol) than that of original ligand 3RF (−36.66 kcal/mol). With reference to the ULK1 inhibition of 3RF (IC50 = 160 nM), it can be inferred that these compounds could be used as a new type of potential ULK1 inhibitors and be worthy of further investigation for tumor treatments. Communicated by Ramaswamy H. Sarma

Oral Drug Delivery Systems Applied to Launched Products: Value for the Patients and Industrial Considerations.

Drug delivery systems (DDS) control the amount, rate, and site of administration of drug substances in the body as well as their release and ADME (absorption, distribution, metabolism, excretion). Among the various types of DDS, amount-controlled DDS for solubilization and absorption increase the bioavailability. Time- and amount-controlled DDS are controlled release formulations classified as (1) membrane-type, (2) matrix-type, (3) osmotic-type, and (4) ion-exchange type. Timed-release formulations also control the time and amount of release and the absorption of drugs. Site- and amount-controlled DDS are characterized by colonic delivery and intestinal lymph-targeting to improve release and ADME of drug substances. Finally, site-, time-, and amount-controlled DDS are gastroretentive formulations and local delivery in the oral cavity to improve site retention, release, and ADME of drugs. DDS can enhance efficacy, reduce adverse effects, and optimize the dosing frequency of various drug products to increase patient value. This review focuses on patient value and industrial considerations of launched oral DDS. We provide a technological overview of candidate and marketed DDS, as well as the pros/cons of the technologies for industrialization with consideration to excipients, manufacturing, and storage stability. Moreover, to demonstrate the usefulness of the technology and support the selection and development of the best technologies for patients, we also describe patient value from clinical studies and analyses, particularly with regard to increased new medical options, higher efficacy, reduced adverse effects, reduced number of doses and clinic visits, easier administration, higher quality of life, greater adherence, and satisfaction.

Novel wild type and mutate HIV-1 protease inhibitors containing heteroaryl carboxamides in P2: Synthesis, biological evaluations and in silico ADME prediction

The Virus HIV-1 infection still represents a serious disease even if actually it is transformed in chronic pathology. Considering the crucial role of the enzyme Protease in life cycle of HIV many efforts have been made in the research of new organic compounds showing inhibitory activity. After development of several series of non peptidic inhibitors we report here the synthesis of novel simple HIV-Protease inhibitors containing heteroaryl carboxamides and their antiviral activity in vitro and in HEK293 cells. Benzofuryl- benzothienyl- and indolyl rings as well as aryl sulfonamides with different electronic properties have been introduced by efficient synthetic procedures. All compounds showed inhibitory activity similar to the commercial drug Darunavir, effective against both wild-type HIV-1 protease and that containing the V32I or V82A mutations. Absorption, distribution, metabolism, excretion (ADME) properties were also evaluated in silico, showing the potential of such compounds to be developed as drugs.

Structure-based discovery of pyrazole-benzothiadiazole hybrid as human HPPD inhibitors

4-Hydroxyphenylpyruvate dioxygenase (HPPD) has attracted increasing attention as a target for treating type I tyrosinemia and other diseases with defects in tyrosine catabolism. Only one commercial drug, 2-(2-nitro-4-trifluoromethylbenzoyl)-1, 3-cyclohexanedione (NTBC), clinically treat type I tyrosinemia, but show some severe side effects in clinical application. Here, we determined the structure of human HPPD-NTBC complex, and developed new pyrazole-benzothiadiazole 2,2-dioxide hybrids from the binding of NTBC. These compounds showed improved inhibition against human HPPD, among which compound a10 was the most active candidate. The Absorption Distribution Metabolism Excretion Toxicity (ADMET) predicted properties suggested that a10 had good druggability, and was with lower toxicity than NTBC. The structure comparison between inhibitor-bound and ligand-free form human HPPD showed a large conformational change of the C-terminal helix. Furthermore, the loop 1 and α7 helix were found adopting different conformations to assist the gating of the cavity, which explains the gating mechanism of human HPPD.

Solvent-solute interaction, thermodynamic behaviour, structural, chemical and anti-cancer biological properties of 3(2H)-furanone derivatives

In this work, the structures, reactivities, and electronic and biological properties of the 3(2H)-furanone derivatives, 2-hydroxy-2,5-diphenyl-4-(phenylamino)furan-3(2H)-one (HDPF), 2-methoxy-2,4,5-triphenylfuran-3(2H)-one (MTPF), 3-oxo-2,4,5-triphenyl-2,3-dihydrofuran-2-yl acetate (OTDF), and 2-chloro-2,4,5-triphenylfuran-3(2H)-one (CTPF), are explored via theoretical investigations using DFT (Density Functional Theory) techniques as the main tools for the study. The DFT studies include geometry optimisation, FMO (Frontier Molecular Orbital) analysis, theoretical UV studies, molecular electrostatic potential (MEP) investigations, non-linear optical (NLO) analyses, and the evaluation of thermodynamic parameters. Multiwfn 3.8 software is utilised to conduct the topological analyses. The ADME (Absorption, Distribution, Metabolism, Excretion) profiles are produced with the SwissADME online tool. The target proteins, MCL-1 (Myeloid cell leukemia-1), BCL-2 (B-cell lymphoma-2), and myeloblastin, are docked with the title molecules using AutoDock 1.5.6.

Identification of key phenolic compounds for alleviating gouty inflammation in edible chrysanthemums based on spectrum-effect relationship analyses

Edible chrysanthemum is a common food resource for tea and functional foods with potential benefits for human health. Studies have indicated that chrysanthemum has the potential effect on inflammatory diseases, while the effects on gouty inflammation remain underexplored. The present study aimed to investigate the anti-gout activity and characterize the active ingredients of chrysanthemums by using metabolite profiles, in vitro experiments, and spectrum-effect analysis. Results showed that ‘Boju’ (BJ), ‘Hangbaiju’ (HBJ), and ‘Huaiju’ (HJ) exhibited regulatory effects on monosodium urate (MSU)-induced inflammation. At the dose of 50 µg/mL, the inhibitory rates of IL-1β secretion were 24.53 %, 14.36 %, and 38.10 %, respectively. A total of 32 phenolic compounds were identified or preliminarily assigned in UPLC-Q/TOF-MS analysis. And seven phenolics related to anti-gout activity were identified by spectrum-effect relationships. According to ADME (absorption, distribution, metabolism, excretion) evaluation and experiments verification, luteolin, acacetin-7-O-glucoside, and apigenin-7-O-glucoside were critical constituents potentially associated with the reduction of inflammation in gout. Additionally, these phenolics might be suitable as quality control indicators. This study clarified the anti-gout properties of different cultivars of chrysanthemums and active compounds, providing a theoretical basis for its scientific utilization in functional foods.

Artificial Intelligence in ADME Property Prediction.

Absorption, distribution, metabolism, excretion (ADME) are key properties of a small molecule that govern pharmacokinetic profiles and impact its efficacy and safety. Computational methods such as machine learning and artificial intelligence have gained significant interest in both academic and industrial settings to predict pharmacokinetic properties of small molecules. These methods are applied in drug discovery to optimize chemical libraries, prioritize hits from biological screens, and optimize ADME properties of lead molecules. In the recent years, the drug discovery community witnessed the use of a range of neural network architectures such as deep neural networks, recurrent neural networks, graph neural networks, and transformer neural networks, which marked a paradigm shift in computer-aided drug design and development. This chapter discusses recent developments with an emphasis on their application to predict ADME properties.

Pharmacokinetics and Pharmacodynamics of GalNAc-Conjugated siRNAs.

Small interfering RNAs (siRNAs) represent a new class of drugs with tremendous potential for battling previously "undruggable" diseases. After nearly 2 decades of efforts in addressing the problems of the poor drug profile of naked unmodified siRNAs, this new modality has finally come to fruition, with 5 agents (patisiran, givosiran, lumasiran, inclisiran, and vutrisiran) being approved since 2018, and with many others in the different phases of clinical development. Unlike small-molecule drugs and protein therapeutics, siRNAs have different sizes, distinct mechanisms of action, differing physicochemical and pharmacological properties, and, accordingly, a unique pharmacokinetic/pharmacodynamic (PK/PD) relationship. To support the continuous development of siRNAs, it is important to have a thorough and deep understanding of the PK/PD and clinical pharmacology related features of siRNAs. As most of the current siRNA products are conjugated by N-acetylgalactosamine (GalNAc), this review focuses on the PK/PD relationships and clinical pharmacology of GalNAc-conjugated siRNAs, including their absorption, distribution, metabolism, excretion (ADME) properties, PK/PD models, drug-drug interactions, clinical pharmacology in special populations, and safety evaluation. In addition, necessary background information related to the development of siRNAs as a therapeutic modality, including the mechanisms of action, the advantages of siRNAs, the problems of naked siRNAs, as well as the strategies used to enhance the clinical utility of siRNAs, have also been covered. The goal of this review is to serve as a "primer" on siRNA PK/PD, and I hope the readers, especially those who have a limited background on siRNA therapeutics, will have a fundamental understanding of siRNA PK/PD and clinical pharmacology after reading this review.

Buchholzia coriacea Leaves Attenuated Dyslipidemia and Oxidative Stress in Hyperlipidemic Rats and Its Potential Targets In Silico

AbstractThe study aimed to investigate how the solvent extract of Buchholzia coriacea (BCE), a widely known hypolipidemic agent, could contribute to hyperlipidemia treatment and identify the potential bioactive compounds. We studied Wistar albino rats, dividing them into seven groups: the normal control, normal rats treated with 400 mg/kg.b.wt of BCE (NRG group), the hyperlipidemic control (HPC group), hyperlipidemic rats treated with atorvastatin, a standard control drug (SC group), as well as 200, 400, and 800 mg/kg.b.wt of BCE extract respectively (T1, T2, T3 groups). The potential compounds that functioned in BCE extract were analyzed by in silico binding to acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN). The binding affinities and drug-like properties of the compounds were determined using virtual screening and absorption distribution metabolism excretion and toxicity prediction analysis. The gas chromatography-mass spectrometry analysis identified alkaloids, saponins, flavonoids, phenols, terpenoids, and 44 chemical compounds in the leaf extract of BCE. BCE significantly reduced the levels of triacylglycerol, total cholesterol, low-density lipoprotein, very low-density lipoprotein, atherogenic coefficient, atherogenic index, and coronary risk index, while enhancing the levels of high-density lipoprotein and cardioprotective index in comparison to the HPC group. The BCE reduced malondialdehyde quantities, which exhibit high levels in HPC. Superoxide dismutase and glutathione peroxidase activities as well as glutathione levels, which are otherwise reduced in HPC, were increased upon the BCE treatment. Among the identified BCE compounds, lupenone and 2,7-dimethylnaphthalene exhibited the highest binding affinities to ACC and FASN, suggesting that these two compounds might be the bioactive BCE components displaying hypolipidemic properties. BCE is found to be beneficial in blocking hyperlipidemia through the modulation of lipid profile, the protection of cardiovascular function, as well as the suppression of oxidative stress. BCE may be a natural source for exploring novel drugs for the treatment of dyslipidemia.

In vitro and in silico perspectives on the activation of antioxidant responsive element by citrus-derived flavonoids.

Oxidative stress plays an essential role in the pathogenesis of chronic diseases. Disrupting the Keap1-Nrf2 pathway by binding Keap1 is identified as a potential strategy to prevent oxidative stress-related chronic diseases. Therefore, of special interest is the utilization of dietary antioxidations from citrus, including narirutin, naringenin, hesperetin, hesperidin, naringin, neohesperidin dihydrochalcone, neohesperidin, and nobiletin, has been exploited as a prospective way to treat or prevent several human pathologies as Keap1-Nrf2 inhibitors for modulation of antioxidant properties. To probe into the structural foundation of the molecular identification of citrus-derived antioxidations, we calculated the antioxidant responsive element activation ability of citrus-derived flavonoids after binding with Keap1. Also, the quantum chemistry properties and binding mode were performed theoretically with frontier molecular orbitals, molecular electrostatic potential analysis, molecular docking, and absorption, distribution, metabolism, excretion (ADME) calculation. Experimental findings combining computational assays revealed that the tested citrus-derived flavonoids can be grouped into strong agonists and weak agonists. The citrus-derived antioxidations were well housed in the bound zone of Keap1 via stable hydrogen bonding and hydrophobic interaction. Eventually, three of eight antioxidations were identified after ADME and physicochemical evaluations. The citrus-derived flavonoids were identified as potential dietary antioxidants of the Keap1-Nrf2 interaction, and can be used to improve oxidative stress-related chronic diseases.