Absorption Distribution Metabolism Research Articles

In vitro antioxidant, anticancer and in silico studies of polyphenol enriched leaf extract of Asystasia gangetica

Polyphenols are natural biomolecules known for circumventing several diseases including cancer with little adverse effects. This study aimed to investigate the polyphenol enriched fractions from the leaf extract of Asystasia gangetica for their composition, biological activities such as antioxidant activity, haemolytic effects, and in vitro cytotoxicity against cancer cell lines. LC–MS/MS analysis of the enriched fractions identified a total of 35 distinct polyphenols with caffeic acid, luteolin, apigenin, and protocatechuic acid at higher concentrations. Fractions AG-3 and AG-4 exhibited the highest total antioxidant activity with higher concentration of phenolics and flavonoids. The AG-4 fraction had the highest levels of DPPH radical scavenging (IC50 = 32.74 µg mL-1) and ABTS radical scavenging (IC50 = 29.45 µg mL–1) activity, in addition to a modest iron chelating activity and reducing power. The fractions exhibited the least haemolytic activity. The cytotoxic potential of enriched fractions against the HCT-116, HeLa, PC-3, and HDF cell lines was further examined. While the extract showed no inhibitory effect on normal HDF cells, the cytotoxic activity of fractions on cell lines varied, with HCT-116 cells having the strongest anticancer activity with an IC50 of 43.82 µg mL–1. Additionally, fractions induced apoptotic activity in HCT-116 cells, resulting in cell cycle arrest at the G2M phase and an increase in sub-G0/G1 cells, with an IC50 of 13.54 µg mL–1 after 48 h of incubation. The in silico molecular docking of the active compounds against the TNIK receptor protein and ADMET (Absorption–Distribution–Metabolism–Excretion–Toxicity) characteristics are described. Overall, the study highlights the enhanced biological and antiproliferative activities of polyphenols in Asystasia gangetica leaf extract, which could be further utilized as a potential cancer treatment strategy.

Design, synthesis, in-vitro, in-silico, DFT and POM studies of a novel family of sulfonamides as potent anti-triple-negative breast cancer agents

In this study, a new family of ethacrynic acid-sulfonamides and indazole-sulfonamides was synthesized and tested in vitro against MDA-MB-468 triple-negative breast cancer cells and PBMCs human peripheral blood mononuclear cells, using the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay. The aim of this research is to discover novel compounds with potential therapeutic effects on breast cancer. The antiproliferative activity of these compounds showed a significant dose-dependent activity, with IC50 values ranging between 2.83 and 7.52 µM. The lead compounds 8 and 9 displayed similar IC50 values to paclitaxel with 2.83, 3.84 and 2.72 µM, respectively. This highlights the novelty and potential of these compounds as alternatives to current treatments. The binding properties of 8, 9, and paclitaxel with the active sites of the PARP1(Poly(ADP-ribose) polymérase 1) and EGFR (Epidermal growth factor receptor) proteins were analyzed by molecular docking methods showing, for PARP1 protein, binding affinities of −9.8 Kcal /mol, −10 Kcal /mol, and −9.4 Kcal /mol, respectively. While their binding affinities for EGFR protein are −7.5 Kcal/mol, −7.2 Kcal/mol and −6.9 Kcal/mol, respectively. Moreover, drug-likeness and ADMET (Absorption–distribution–metabolism–excretion–toxicity) analyses demonstrated that both molecules are orally bioavailable and have good pharmacokinetic and non-toxic profiles. DFT (Density functional theory) was also carried out on both compounds 8 and 9 additionally to POM (Petra/Osiris/Molinspiration) studies on all compounds. The outcomes of this study suggest that compounds 8 and 9 are promising candidates for further development as therapeutic agents against triple-negative breast cancer

A Robust In Vitro Anti‐tuberculosis, Antimicrobial, and Anti‐inflammatory Activities Based on Azomethine Chelates Incorporating Co(II), Ni (II), Cu(II), and Zn(II) Ions: Synthesis, Characterization, and Investigation of the Aspects of Docking Interaction

ABSTRACTIn recent times, there has been a growing exploration of transition metal complexes as potential solutions for significant health challenges, including tuberculosis, microbes infection, and inflammation. Therefore, in our ongoing effort to identify biologically effective agents, Co(II), Ni(II), Cu(II), and Zn(II) metal complexes of H2L1–H2L2 hydrazone ligands were synthesized. The structural features of synthesized compounds were recognized by employing several techniques such as FT‐IR, 1H NMR, 13C NMR, powder x‐ray diffraction (XRD), UV‐Vis, ESR, TG‐DTA, mass spectrometry, and molar conductance measurements. The bonding of ligands via Ophenolic, Oenolic, and Nazomethine donor atoms and the attachment of the three water molecules with metal ion to form the octahedral structure of complexes were corroborated by different spectroscopic techniques. The anti‐tuberculosis, antimicrobial, and anti‐inflammatory activities of the synthesized compounds were assessed using the microplate alamar blue assay, serial dilution, and bovine serum albumin (BSA) methods, respectively, and highlighted the more potency of the complexes than ligands. The synthesized Cu(II) (9) and Zn(II) (10) metal complexes exhibited excellent ability to inhibit the growth of H37Rv strain of Mycobacterium tuberculosis in comparison to standard drug streptomycin. The Cu(II) (6 and 9) and Zn(II) (10) complexes showed superb ability as antimicrobial agents, whereas Cu(II) (5) and Zn(II) (6) complexes exhibited significant anti‐inflammatory ability. The in vitro findings on the antituberculosis activity were reinforced by a significant molecular docking study, which has become a crucial component of computational research utilizing the enzyme Mtb Pks13 thioesterase domain of M. tuberculosis. Additionally, in this research work, the absorption–distribution–metabolism–excretion–toxicity (ADMET) study sparked the compounds' drug‐like behavior.

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.

Identification and Absorption–Distribution–Metabolism–Excretion–Toxicity Prediction of Potential MTHFD2 Enzyme Inhibitors from Urtica dioica Ethanolic Leaf Extract

This study aimed to explore the potential of Urtica dioica (U. dioica) ethanolic leaf extract for cancer treatment by identifying its components, evaluating its effects on cancer cell lines, and analyzing its molecular docking. The objective of this study was to investigate the anticancer properties of U. dioica ethanolic leaf extract and assess its potential as a therapeutic strategy for cancer treatment. This study utilized high-performance liquid chromatography (HPLC) to analyze the chemical composition of U. dioica ethanolic leaf extract. The anticancer effects of the extract were evaluated by assessing cell viability, determining IC50 values, and conducting ADMET analysis after oral administration. U. dioica ethanolic leaf extract was found to contain methyl hexadecanoate as its primary component, along with flavonoids and polyphenols. It effectively reduced cell viability in various tested cancer cell lines, with IC50 values varying for each cell line. The duration of treatment significantly influenced cell viability, with the most significant reduction observed after 48 h. Molecular docking studies suggested that catechin, kaempferol, and quercetin-3-O-rutinoside may have potential as inhibitors of the MTHFD2 enzyme. This study revealed the potential of U. dioica and its compounds in cancer treatment. Ethanolic leaf extract has been shown to have anticancer effects on various cancer cell lines, with catechin and kaempferol showing promise as inhibitors of the MTHFD2 enzyme. Further research is warranted to explore the therapeutic implications of U. dioica in cancer treatment.

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.

In silico screening and identification of lead molecules from Garcinia gummi-gutta with multitarget activity against SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has affected the human population, resulting in multiple waves of pandemics around the world. One of the main threats is hyper-evolved viral variants with high transmissibility and virulence, and the best solution is the application of multitargeted drugs of plant origin. In this perspective, the anti-SARS-CoV-2 activity of Garcinia gummi-gutta was evaluated through an in silico approach. A total of 97 phytochemicals from G. gummi-gutta were tested against three therapeutic targets of SARS-CoV-2, namely spike protein, main protease (Mpro), RNA-dependent RNA polymerase, and two human host targets such as angiotensin-converting enzyme-2 and nuclear factor-κB through molecular docking. Out of 97 phytochemicals screened, 18 of them showed significant binding free energy with all the five selected targets. The compound amentoflavone was chosen as the best lead molecule based on binding energy, molecular interactions, and absorption distribution metabolism and excretion profile. The interaction of amentoflavone with Mpro was further verified using molecular dynamic simulation. The overall results revealed that the compound amentoflavone can be recommended as the best lead compound with multitargeting potential against SARS-CoV-2, and can be recommended for further experimental studies leading to drug discovery.

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

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.

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.

Advanced prodrug approaches for neurodegenerative diseases

The prodrug technique is still one of the most effective ways to increase hydrophilic substances' medicinal, pharmacodynamic and pharmacokinetic properties. Prodrugs produced in current history have shown good pharmacokinetic characteristics, allowing for a more consistent release and fewer changes in plasma levels. Developing new prodrugs having a desirable ADME (Absorption Distribution Metabolism and Elimination) properties and that still can cross the Blood brain barrier (BBB) and pharmacologically active an appealing task for medicinal chemists. The loss of brain neuron activity characterizes neurodegenerative illnesses, resulting in progressive Gradual cognitive impairment (GCI). Some of the common neurodegenerative diseases are PD (Parkinson's disease), AD (Alzheimer's disease), MS (Multiple sclerosis), ALS (amyotrophic lateral sclerosis) & HD (Huntington's disease) are examples of neurodegenerative illnesses with a variety of etiologies and morphological and pathophysiological aspects. The current review is concerned with current advances in prodrug approaches for the treatment and prevention of the most prevalent neurological illnesses, as well as their absorption, selective CNS targeting and chemical and enzymatic stability.

Recent advances in the area of plant-based anti-cancer drug discovery using computational approaches.

Phytocompounds are a well-established source of drug discovery due to their unique chemical and functional diversities. In the area of cancer therapeutics, several phytocompounds have been used till date to design and develop new drugs. One of the desired interests of pharmaceutical companies and researchers globally is that new anti-cancer leads are discovered, for which phytocompounds can be considered a valuable source. Simultaneously, in recent years, the growth of computational approaches like virtual screening (VS), molecular dynamics (MD), pharmacophore modelling, Quantitative structure-activity relationship (QSAR), Absorption Distribution Metabolism Excretion and Toxicity (ADMET), network biology, and machine learning (ML) has gained importance due to their efficiency, reduced time-consuming nature, and cost-effectiveness. Therefore, the present review amalgamates the information on plant-based molecules identified for cancer lead discovery from in silico approaches. The mandate of this review is to discuss studies published in the last 5-6years that aim to identify the phytomolecules as leads against cancer with the help of traditional computational approaches as well as newer techniques like network pharmacology and ML. This review also lists the databases and webservers available in the public domain for phytocompounds related information that can be harnessed for drug discovery. It is expected that the present review would be useful to pharmacologists, medicinal chemists, molecular biologists, and other researchers involved in the development of natural products (NPs) into clinically effective lead molecules.

​Exploring Inhibitory Potential of Curcumin against Multiple Targets Involved in the Cancer Progression, Metastasis and Apoptosis Pathways by in silico Molecular Docking

Background: Cancer is a multifactorial disease characterized by altered gene expression and one of the most leading causes of death in the world. Curcumin obtained from Curcuma longa known to exhibit anti-inflammatory, antioxidant as well as anti-cancer properties. The present study was undertaken to know different targets through which curcumin acts to elicit the antitumor effect. Methods: In this present study in silico interaction of curcumin with different cancer targets were analyzed by molecular docking using Biovia Discovery studio 4.0. Proteins were selected based on their role in cancer pathways which include transcription factor Nf-kB p50 and p65 subunit, Matrix metalloproteinase involved in invasion and metastasis, cell cycle regulator cyclin D and apoptotic factor Bax. Result: Curcumin found to interact with all the selected proteins with high dock score of 125.428, 94.778, 114.5,111.731,98.6844 with Nf-kB p50, p65 subunits, MMP9, Cyclin D1 and Bax proteins, respectively. Amino acid residues to which curcumin interact, number of hydrogen bonds and hydrogen bond length also predicted. RMSD (Root Mean Square Deviation) value was found to be one in all the interactions. Based on the molecular interaction studies and ADME (Absorption Distribution Metabolism Excretion) predictions it was found that curcumin can act as potent inhibitor of many cancer targets and can be used as a starting molecule for the design of anticancerous drug.

Development of an Orally Active Small-Molecule Inhibitor of Receptor Activator of Nuclear Factor-κB Ligand.

Receptor activator of nuclear factor-κB (RANK) and its ligand, RANKL, play pivotal roles in bone remodeling. The monoclonal antibody denosumab successfully inhibited the maturation of osteoclasts (OCs) by binding to RANKL in the clinic. We continued our efforts to develop small-molecule inhibitors of RANKL. In this work, 41 β-carboline derivatives were synthesized based on previously synthesized compound Y1599 to improve its drug-like properties. Compound Y1693 was identified as a potent RANKL inhibitor that improved absorption-distribution-metabolism-excretion properties and effectively prevented RANKL-induced osteoclastogenesis and bone resorption. Furthermore, Y1693 also suppressed the expression of OC marker genes. Moreover, Y1693 demonstrated good tolerability and efficacy in an orally administered mouse model of osteoporosis as well as the ability to rescue alveolar bone loss in vivo caused by periodontal disease. Collectively, the above findings may provide a valuable direction for the development of novel antiresorptive therapies that target RANKL.

Inhibitors of α-glucosidase and Angiotensin-converting Enzyme in the Treatment of Type 2 Diabetes and its Complications: A Review on in Silico Approach

Background: The use of pharmacological agents to synergistically target key enzymes associated with carbohydrate digestion (α-glucosidase) and the hypertension-related angiotensin-converting enzyme (ACE) are critical strategies for the management of type 2 diabetes (T2D) and its end-stage complications. Furthermore, aside from their blood pressure-lowering effect, ACE inhibitors (ACEIs) are important therapeutic agents for preventing diabetic complications, highlighting their synergistic renoprotective and antihypertensive effects in diabetic patients who are normotensive and hypertensive. Objectives: We reviewed the safety and potent activity of phytochemicals discovered based on molecular docking and dynamics in recent years that could be used to treat T2D. Methods: We surveyed recently in silico drug discovery findings on α-glucosidase and ACE retrieved from the PubMed database. Computational in silico ADMET meta-analysis was performed on 57 compounds that could potentially inhibit α-glucosidase or ACE. Results: The review highlighted the fact that most hit compounds of α-glucosidase and ACE involving the use of molecular docking and molecular dynamics techniques are competitive and peptide inhibitors, respectively. Moreover, we found that most authors do not consider absorption distribution metabolism excretion toxicity (ADMET) studies on drug candidates, which is important in determining the safety profile of potent leads. Hence, we performed in silico ADMET meta-analysis of the reported compounds and found some inhibitors with an excellent pharmacological profile. Conclusion: We propose that further studies be conducted on these promising leads to demonstrate their efficacy and safety in the treatment of T2D.

A Cross Company Perspective on the Assessment of Therapeutic Protein Biotransformation.

Unlike with new chemical entities, the biotransformation of therapeutic proteins (TPs) has not been routinely investigated or included in regulatory filings. Nevertheless, there is an expanding pool of evidence suggesting that a more in-depth understanding of biotransformation could better aid the discovery and development of increasingly diverse modalities. For instance, such biotransformation analysis of TPs affords important information on molecular stability, which in turn may shed light on any potential impact on binding affinity, potency, pharmacokinetics, efficacy, safety, or bioanalysis. This perspective summarizes the current practices in studying biotransformation of TPs and related findings in the biopharmaceutical industry. Various TP case studies are discussed, and a fit-for-purpose approach is recommended when investigating their biotransformation. In addition, we provide a decision tree to guide the biotransformation characterization for selected modalities. By raising the awareness of this important topic, which remains relatively underexplored in the development of TPs (Bolleddula et al., 2022), we hope that current and developing practices can pave the way for establishing a consensus on the biotransformation assessment of TPs. SIGNIFICANCE STATEMENT: This article provides a comprehensive perspective of the current practices for exploring the biotransformation of therapeutic proteins across the drug development industry. We, the participants of the Innovation and Quality therapeutic protein absorption distribution metabolism excretion working group, recommend and summarize appropriate approaches for conducting biotransformation studies to support internal decision making based on the data generated in discovery and development.

Synthesis of a dual carbon-14-labeled calcitonin gene-related peptide receptor antagonist for use in a human absorption-distribution-metabolism-elimination study.

Oral calcitonin gene-related peptide (CGRP) receptor antagonists have been shown to be effective in the acute and preventive treatment of migraine. CGRP receptor antagonists offer safety advantages over triptans because they are not active vasoconstrictors, which reduces cardiovascular risks. Bristol Myers Squibb discovered a high affinity CGRP receptor antagonist BMS-927711 for the treatment of migraine now FDA approved as Nurtec® ODT (rimegepant). Dual-labeled [14 C]-BMS-927711 was prepared and used in a human absorption-distribution-metabolism-elimination (ADME) study. A dual-labeled analog of BMS-927711 was required to fully track the compound's metabolic transformation. The carbon-14-labeled synthesis of both right side and left side portions of [14 C]-BMS-927711 is described.

Computational studies on the cholinesterase, beta-secretase 1 (BACE1) and monoamine oxidase (MAO) inhibitory activities of endophytes-derived compounds: towards discovery of novel neurotherapeutics

Cholinesterases, beta-secretase 1 (BACE1) and monoamine oxidase (MAO) are significant in the etiology of neurodegenerative diseases. Inhibition of these enzymes is therefore a major strategy for the development of neurotherapeutics. Even though, this strategy has birthed some approved synthetic drugs, they are characterized by adverse effects. It is therefore, imperative to explore promising alternatives. Consequently, we assessed the inhibitory activities of some endophytes-derived compounds against selected targets towards discovery of novel neurotherapeutics. Standard inhibitors and 83 endophytes-derived compounds were docked against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), BACE 1 and MAO using AutodockVina while the molecular interactions between the selected targets and the compounds with notable binding affinity were viewed through Discovery Studio Visualizer. Druglikeness and Absorption–Distribution–Metabolism–Excretion-Toxicity (ADMET) and blood brain barrier (BBB) properties of the top 4 compounds were evaluated using the Swiss online ADME web tool and OSIRIS server; ligands-enzymes complex stability was assessed through molecular dynamics (MD) simulation. From the 83 compounds, asperflavin, ascomfurans C, camptothecine and corynesidone A exhibited remarkable inhibitory activity against all the four target enzymes compared to the respective standard inhibitors. However, only corynesidone A could transverse the BBB and predicted to be safe. MD simulation of the unbound and complexed enzymes with corynesidone A showed that the complexes were stable throughout the simulation time. Given the exceptional inhibitory activity of endophytes-derived corynesidone A against the four selected targets, its ability to permeate the BBB, excellent drugability properties as well as its stability when complexed with the enzymes, it is a good candidate for further studies towards development of new neurotherapeutics. Communicated by Ramaswamy H. Sarma

The role of eugenol and ferulic acid as the competitive inhibitors of transcriptional regulator RhlR in P. aeruginosa

Search inhibitors of Quorum Sensing (QS) in Pseudomonas aeruginosa are challenging to find therapies due to the broad antibiotic resistance. Therefore, this study aimed to probe ten aromatic compounds as inhibitors of three transcriptional regulators of QS in P. aeruginosa. The methodology consisted in determining the Binding Gibbs Energy (BGE) with software Chimera (tool vina) and Mcule, comparing the averages by the Tukey method (p≤0.05) to find inhibitors of QS. Subsequently, the LD50 in the mice model was evaluated by three QSAR models, and the in silico pharmacokinetic values were obtained from the ADME (the absorption distribution metabolism excretion) and PubChem databases. Found three potential inhibitors of RhlR with the lower BGE values in the range -6.70±0.21 to -7.43±0.35 kcal/mol. On the other side, all compounds were acceptable for Lipinski's rule of fives and the in silico oral mice LD50 and ADME values. Concluding, the ferulic acid and eugenol showed the best total BGE values (-75.07±0.892 and -70.36±1.022 kcal/mol), proposing them as a new therapy against the virulence of P. aeruginosa. Finally, the in silico studies have demonstrated are reproducible and valuable for putative QS inhibitors predicting and obtaining new studies derivatives from the results obtained in the present study.• The key benefits of this methodology are:Use free, licensed, flexible, and efficient software for in silico molecular docking.• Validation and comparison of BGE employing two molecular docking software in three different proteins.• Use classical molecular dynamics to define the stability and the total BGE of interaction protein-ligand and find the best inhibitor of a protein for proposing them as a possible therapy against the virulence of specific pathogens.

Computational Prediction of Pharmacokinetic and Toxicological Properties ofSelected Phytochemicals from Eugenia jambolana Lam.

Background Eugenia jambolana Lam. is a herb distributed throughout the world and documented to possess many beneficial effects. The plant has been documented for the presence of various phytochemicals including primary and secondary metabolites.Aim of the Study In the present investigation an attempt has been made to carry out computational prediction of pharmacokinetic and toxicological properties of selected phytoconstituents from Eugenia jambolana Lam.Methodology We have selected oleanolic acid ursolic acid arjunolic acid maslinic acid corosolic acid asiatic acid alphitolic acid betulinic acid. PubChem database was utilized to collect the canonical smiles. Molsoft server was utilized to determine the drug likeness of selected phytochemicals. The admetSAR Structure Activity Relationship and Swiss ADME Absorption Distribution Metabolism and Excretion server were used for the determination of toxicity and pharmacokinetic properties.Results The results of investigation yielded the drug likeness score of selected phytoconstituents along with its pharmacokinetic and toxicity properties. The selected constituents such as Maslinic acid Arjunolic acid Oleanolic acid Ursolic acid Corosolic acid Asiatic acid Alphitolic acid Betulinic acid were found to be better drug like candidates.Conclusion The proposed In-silico work concluded that computer aided prediction and server based investigation was important and informative in collecting the data regarding drug like candidates and pharmacokinetic and toxicological properties of bioactive compounds from plant Eugenia jambolana Lam.