Eudesma-4(15), 7-dien-1-β-ol, A promising natural drug candidate for Alzheimer's disease targeting the NMDA pathway: GC-MS identification, molecular docking, pharmacokinetic and molecular dynamic analysis.

1-Ethoxycarbonyl-beta-carboline inhibits the M2 polarization of tumor-associated macrophages: A study based on network pharmacology and molecular docking analyses

Alzheimer's disease (AD) is a “progressive, neurodegenerative disease that occurs when nerve cells in the brain die.” There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool—Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.

Mechanism of Keke tablets in treating post-infectious cough following influenza A virus infection based on network pharmacology, molecular docking, molecular dynamics and in vivo experiments.

Anti-malarial proguanil (1) and phenoxypropoxy biguanide derivatives (2–9) are prodrugs. Their efficacy is directly proportional to the quantity of active triazine metabolites produced from these prodrugs. Detailed molecular docking analyses for all nine drug candidates in the active site of CYP3A4, CYP2D6, and CYP2C19 were carried out under the influence of induced-fit effect of ligand during molecular dynamic simulations. We have developed a strategy based on docking pose clusters to quantify the production of active metabolites for this class of molecules. For all drugs, site of metabolism based clusters of docking poses were prepared in both phases of the molecular docking analyses and correlated with the percentage of metabolites generated in the pooled human liver microsomes study. The total numbers of docking poses representing active metabolite formation were found to be well correlated with the experimental results in post-induced fit docking analyses. This strategy was first validated using proguanil, PS-15 and JPC-2056. Further, this methodology was employed to correlate the theoretically predicted metabolite formation of 4–9 to the experimentally estimated values which further led to clues on isoenzyme specificity in producing the metabolites. Binding requirements of these leads in the active sites of CYPs were also explored in this study.

Unveiling the interaction mechanism of alogliptin benzoate with human serum albumin: Insights from spectroscopy, microcalorimetry, and molecular docking and molecular dynamics analyses.

Alzheimer's disease is a serious and widespread neurodegenerative illness in the modern healthcare scenario. GSK-3β and BuChE are prominent enzymatic targets associated with Alzheimer's disease. Co-targeting GSK3β and BChE in Alzheimer's disease helps to modify disease progression and enhance cognitive function by addressing both tau pathology and cholinergic deficits. However, the treatment arsenal for Alzheimer's disease is extremely inadequate, with present medications displaying dismal success in treating this never-ending ailment. To create novel dual inhibitors, we have used molecular docking and dynamics analysis. Our focus was on analogs formed from the fusion of tacrine and amantadine ureido, specifically tailored to target GSK-3β and BuChE. In the following study, molecular docking was executed by employing AutoDock Vina and molecular dynamics and ADMET predictions were performed using the Desmond and Qikprop modules of Schrödinger. Our findings unveiled that compounds DKS1 and DKS4 exhibited extraordinary molecular interactions within the active domains of GSK-3β and BuChE, respectively. These compounds engaged in highly favorable interactions with critical amino acids, including Lys85, Val135, Asp133, and Asp200, and His438, Ser198, and Thr120, yielding encouraging docking energies of -9.6 and -12.3 kcal/mol. Additionally, through extensive molecular dynamics simulations spanning a 100 ns trajectory, we established the robust stability of ligands DKS1 and DKS4 within the active pockets of GSK-3β and AChE. Particularly noteworthy was DKS5, which exhibited an outstanding human oral absorption rate of 79.792%, transcending the absorption rates observed for other molecules in our study. In summary, our in silico findings have illuminated the potential of our meticulously designed molecules as groundbreaking agents in the fight against Alzheimer's disease, capable of simultaneously inhibiting both GSK-3β and BuChE.

Alzheimer's disease (AD) is a growing healthcare crisis with limited effective therapies. This study aims to identify new candidate drugs that can be repurposed using key transcriptional regulators (DERs) in AD as therapeutic targets. Multi-cohort single-nucleus RNA sequencing (snRNA-seq) data from the prefrontal cortexwere analysed to identify DERs. Molecular docking and dynamic simulations analysis evaluated interactions between DERs and 2200 Food and Drug Administration-approved drugs to assess bindingstability, whilst pharmacokinetic parameters relevant to blood-brain barrier permeability were evaluated. We identified 20 key DERs associated with AD. Lasmiditan stood out as the most promising drug amongst other drug candidates (Vorapaxar, Bictegravir, Tonaftate, Fluspirilene, Lisuride, Olaparib) interacting with five DERs: ZEB2, APP, PAX6, ETV6, and ST18. Lasmiditan-ETV6 complex showed the best binding stability (RMSD: 2.98 Å, H-bonds: 68.38) and optimal passive diffusion (LogP3-4, TPSA 60-75 Å2). Lasmiditan is a potential AD therapeutic candidate that warrants further preclinical validation. 20 key transcriptional regulators (DERs) were identified linked to AD in myeloid, and neuronal cell populations. The DERs correlated with Braak stage, APOE genotype, and aging. ETV6 is a potentially viable therapeutic target due to its ability to form stable and strongly interacting complexes across multiple drugs. Lasmiditan showed the strongest binding to ETV6 (RMSD: 2.98Å, H-bonds: 68.38) and optimal blood-brain-barrier (BBB) penetration (LogP 3-4, TPSA 60-75). Lasmiditan is a potentially promising AD therapeutic candidate that warrants further preclinical validation.

Inflammatory response plays important roles in both tumorigenesis and carcinogenesis. In this study, secondary metabolite compounds from Lactococcus lactis subsp. lactis (Lac3) were analyzed by LC-MS and the potential inhibition activity against the COX-2 receptor was screened through molecular docking and molecular dynamics (MD) analysis. Anti-inflammatory agents, mofezolac and ibuprofen, were used as positive control ligands. The result indicates a potential COX-2 inhibitor of 5-[(4-Amino-6-morpholin-4-yl-1,3,5-triazin-2-yl)amino]-2- methylbenzenesulfonate, which has a hydrogen bond on the active site Tyr385 of COX-2 with affinity energy of –9.0 kcal/mol. Moreover, another candidate of COX-2 inhibitor, designated as 3-Indolepropionic acid binds hydrogen on the important residue Ser530 of COX-2, with an affinity energy of –6.9 kcal/mol. To confirm the binding specificity, molecular docking analysis was also performed against COX-1. The binding stability and flexibility were confirmed using MD simulations. In addition, the toxicity and solubility of the potential ligands were predicted according to Lipinski’s rules and BOILED-Egg modeling. The 5-[(4-Amino-6-morpholin-4-yl- 1,3,5-triazin-2-yl)amino]-2-methylbenzenesulfonate shows the propensity for passive absorption through the gastrointestinal tract, whereas 3-Indolepropionic acid shows a high probability of blood-brain barrier penetration. In conclusion, this study identified potential compounds through molecular docking analysis which can be developed as COX-2 inhibitors.

Local QSAR modeling of cytotoxic activity of newly designed androstane 3-oximes towards malignant melanoma cells

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6 Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.

The novel Coronavirus (COVID-19) has spread rapidly across the globe and has involved more than 215 countries and territories. Due to a lack of effective therapy or vaccine, urgent and concerted efforts are needed to identify therapeutic targets and medications. COVID-19 main protease represents a major target for drug treatment to inhibit viral function. The present study sought to evaluate medicinal plant compounds as potential inhibitors of the COVID-19 main protease using molecular docking and molecular dynamic analysis. The PDB files of COVID-19 main protease and some medicinal plant compounds were retrieved from the Protein Data Bank (http://www.rcsb.org) and Pubchem server, respectively. The Gromacs software was used for simulation studies, and molecular docking analysis was done using Autodock 4.2. The COVID-19 main protease simulation, compared with some phytochemicals docked to the COVID-19 main protease, were analyzed. Glabridin, catechin, and fisetin had the greatest tendency to interact with the COVID-19 main protease by hydrogen and hydrophobic interactions. Docking of these phytochemicals to COVID-19 main protease led to an increase in the radius of gyration (Rg), decrease in the Root mean square fluctuation (RMSF), and induced variation in COVID-19 main protease secondary structure. The high tendency interaction of glabridin, catechin, and fisetin to COVID-19 main protease induced conformational changes on this enzyme. These interactions can lead to enzyme inhibition. This simulated study indicates that these phytochemicals may be considered as potent inhibitors of the viral protease; however, more investigations are required to explore their potential medicinal use. Communicated by Ramaswamy H. Sarma

Pharmacotherapeutic potential of bilobetin to combat chromium induced hepatotoxicity via regulating TLR-4, Nrf-2/Keap-1, JAK1/STAT3 and NF-κB pathway: A pharmacokinetic and molecular dynamic approach

A Flavonoid glycoside compound, isolated and identified from E. polyantha as myricitrin, was analyzed as a ligand for its molecular binding activity against SARS-CoV-2 protein (receptor binding domain on Spike/RBD, main protease/nsp5, EndoRNAse, RNA-dependent-RNA-polymerase/RdRp), and its receptor, ACE2, and computationally assessed via molecular docking method. This study aims to determine the potential of myricitrin in E. polyantha from Indonesia as an antiviral drug for SARS-CoV-2 through molecular docking and molecular dynamic simulation analysis. The results showed that the myricitrin had the strongest binding affinity energy towards the three important SARS-CoV-2 proteins, namely endoRNAse, main protease (3CLpro), and RdRp with ∆G values of −9.60 kcal/mol, −8.40 kcal/mol, and −8.30 kcal/mol, respectively. These values are stronger than the comparator ligands of favipiravir (−5.60 kcal/mol), atazanavir (−7.20 kcal/mol), and remdesivir (−7.70 kcal/mol). This indicated that the compound has the potential as an inhibitor against 3CLpro, endoRNAse, and RdRp of SARS-CoV-2 proteins. This result was supported by the prediction made according to the Molprobity and PASS Online web servers, which showed that myricitrin has high bioactivity potential as an enzyme inhibitor (with a score of 0.38) and antiviral (with a score of 0.704).

Background: Alzheimer's disease (AD) stands out as one of the most devastating and prevalent neurodegenerative disorders known today. Researchers have identified several enzymatic targets associated with AD among which Glycogen synthase kinase-3β (GSK-3β) and Acetylcholinesterase (AChE) are prominent ones. Unfortunately, the market offers very few drugs for treating or managing AD, and none have shown significant efficacy against it. Objectives: To address this critical issue, the design and discovery of dual inhibitors will represent a potential breakthrough in the fight against AD. In the pursuit of designing novel dual inhibitors, we explored molecular docking and dynamics analyses of tacrine and amantadine uredio-linked amide analogs such as GSK-3β and AChE dual inhibitors for curtailing AD. Tacrine and adamantine are the FDA-approved drugs that were structurally modified to design and develop novel drug candidates that may demonstrate concurrently dual selectivity towards GSK-3β and AChE. Methods: In the following study, molecular docking was executed by employing AutoDock Vina, and molecular dynamics and ADMET predictions were made using Desmond, Qikprop modules of Schrödinger. Results: Our findings revealed that compounds DST2 and DST11 exhibited remarkable molecular interactions with active sites of GSK-3β and AChE, respectively. These compounds effectively interacted with key amino acids, namely Lys85, Val135, Asp200, and Phe295, resulting in highly favourable docking energies of -9.7 and -12.7 kcal/mol. Furthermore, through molecular dynamics simulations spanning a trajectory of 100 ns, we confirmed the stability of ligands DST2 and DST11 within the active cavities of GSK-3β and AChE. The compounds exhibiting the most promising docking results also demonstrated excellent ADMET profiles. Notably, DST21 displayed an outstanding human oral absorption rate of 76.358%, surpassing the absorption rates of other molecules. Conclusion: Overall, our in-silico studies revealed that the designed molecules showed potential as novel anti-Alzheimer agents capable of inhibiting both GSK-3β and AChE simultaneously. So, in the future, the designing and development of dual inhibitors will harbinger a new era of drug design in AD treatment.

We investigate the mechanism of action of astragalin (AST) in the treatment of Alzheimer's disease (AD). Network pharmacology was conducted to analyze the relationships among AST, AD, and neuroinflammation, The APP/PS1 transgenic mice with AD were used in the experiments; to be specific, the influence of AST on the behavior of mice was analyzed by Morris water maze and eight-arm radial maze tests, the tissue inflammatory factor levels were detected by ELISA, and pathological changes were analyzed by H&E and immunohistochemical staining. Analysis results of network pharmacology suggested that AST exerted the multi-target effect on neuroinflammation in AD. Through molecular docking and dynamics analyses, COX2 might be the target of AST. Moreover, animal experimental results demonstrated that AST improved the behavior of AD mice, and enhanced the motor and memory abilities, meanwhile, it suppressed the expression of inflammatory factors in tissues and the activation of microglial cells. this study discovers that AST can suppress microglial cell activation via COX2 to improve neuroinflammation in AD.