Investigation of Antidepressant Properties of Yohimbine by Employing Structure-Based Computational Assessments

Network pharmacology combined with molecular docking and experimental verification to elucidate the effect of flavan-3-ols and aromatic resin on anxiety

This study investigated the potential anxiolytic properties of flavan-3-ols and aromatic resins through a combined computational and experimental approach. Network pharmacology techniques were utilized to identify potential anxiolytic targets and compounds by analyzing protein-protein interactions and KEGG pathway data. Molecular docking and simulation studies were conducted to evaluate the binding interactions and stability of the identified targets. Behavioral tests, including the elevated plus maze test, open field test, light-dark test, actophotometer, and holeboard test, were used to assess anxiolytic activity. The compound-target network analysis revealed complex interactions involving 306 nodes and 526 edges, with significant interactions observed and an average node degree of 1.94. KEGG pathway analysis highlighted pathways such as neuroactive ligand-receptor interactions, dopaminergic synapses, and serotonergic synapses as being involved in anxiety modulation. Docking studies on EGCG (Epigallocatechin gallate) showed binding energies of -9.5 kcal/mol for MAOA, -9.2 kcal/mol for SLC6A4, and -7.4 kcal/mol for COMT. Molecular dynamic simulations indicated minimal fluctuations, suggesting the formation of stable complexes between small molecules and proteins. Behavioral tests demonstrated a significant reduction in anxiety-like behavior, as evidenced by an increased number of entries into and time spent in the open arm of the elevated plus maze test, light-dark test, open field center activity, hole board head dips, and actophotometer beam interruptions (p < 0.05 or p < 0.01). This research provides a comprehensive understanding of the multi-component, multi-target, and multi-pathway intervention mechanisms of flavan-3-ols and aromatic resins in anxiety treatment. Integrated network and behavioral analyses collectively support the anxiolytic potential of these compounds and offer valuable insights for future research in this area.

Targeting GluR3 in Depression and Alzheimer's Disease: Novel Compounds and Therapeutic Prospects

BACKGROUND

The present study investigates the interrelated pathophysiology of depression and Alzheimer's disease (AD), with the objective of elucidating common underlying mechanisms.

OBJECTIVE

Our objective is to identify previously undiscovered biogenic compounds from the NuBBE database that specifically interact with GluR3. This study examines the bidirectional association between depression and AD, specifically focusing on the role of depression as a risk factor in the onset and progression of the disease.

METHODS

In this study, we utilize pharmacokinetics, homology modeling, and molecular docking-based virtual screening techniques to examine the GluR3 AMPA receptor subunit.

RESULTS

The compounds, namely ZINC000002558953, ZINC000001228056, ZINC000000187911, ZINC000003954487, and ZINC000002040988, exhibited favorable pharmacokinetic profiles and drug-like characteristics, displaying high binding affinities to the GluR3 binding pocket.

CONCLUSIONS

These findings suggest that targeting GluR3 could hold promise for the development of therapies for depression and AD. Further validation through in vitro, in vivo, and clinical studies is necessary to explore the potential of these compounds as lead candidates for potent and selective GluR3 inhibitors. The shared molecular mechanisms between depression and AD provide an opportunity for novel treatment approaches that address both conditions simultaneously.

Peptidomimetics for CVD screened via TRADD-TRAF2 complex interface assessments

The main aim of this study is to screen and develop Peptidomimetics to treat atherosclerosis (AS) which is a Cardio Vascular Disease (CVD). Peptidomimetics were obtained from the protein-protein interaction interface of TRADD (Tumor necrosis factor receptor type 1-associated DEATH domain protein) and TRAF2 (TNF receptor-associated factor 2) complex. TRADD-TRAF2 interaction is critical in AS pathogenesis since it assists a series of signal transducers that activate NF-κB. Conceptually, the triggered NF-κB makes an extensive amount of nitric oxide (NO) synthesized by inducible nitric oxide synthase (iNOS), which boons the progress of AS. The examined TRADD-TRAF2 complex (PDB ID: 1F3V) and its interaction details revealed that the sequence range W11-G165 of TRADD highly interacts with TRAF2. The sequence range W11-G165 was selected for the design and preparation of the inhibitory peptide in silico. The selected sequence was mutated with the alanine scanning method to have a range of inhibitory peptides. With the help of different in silico tools, the top three, namely MIP11-25 L, MIP131-143 h, and MIP149-164 m peptides showed the best interaction with the critical residues of TRAF2. Thus, these three peptides were used for generating peptidomimetics using pepMMsMIMIC, a peptidomimetics virtual screening tool. Around 600 peptidomimetics were identified & and retrieved for further screening by employing molecular docking tools and MD (Molecular Dynamics) simulations. Density Functional Theory (DFT) and ADMET predictions were applied to validate the screened peptidomimetics druggability. In the results, peptidomimic compounds MMs03918858 and MMs03927281 with binding energy values of -9.6 kcal/mol and - 9.1 kcal/mol respectively were screened as the best and are proposed for further pre-clinical studies.

Target validation and structure-based virtual screening to Discover potential lead molecules against the oncogenic NSD1 histone methyltransferase

The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. TCGA clinical data, molecular expression techniques were used to validate the target and structure-based virtual screening was performed to design hits against NSD1. Clinical data analysis suggests the role of NSD1 in metastasis, prognosis and influence on overall survival in various malignancies. Furthermore, the mRNA and protein expression profile of NSD1 was evaluated in various cell lines. NSD1 was exploited as a target protein for in silico design of inhibitors using two major databases including ZINC15 and ChemDiv by structure-based virtual screening approach. Virtual screening was performed using the pharmacophore hypothesis designed with a protein complex S-adenosyl-l-methionine (SAM) as an endogenous ligand. Subsequently, a combined score was used to distinguish the top 10 compounds from the docking screened compounds having high performance in all four scores (docking score, XP, Gscore, PhaseScreenScore, and MMGBSA delta G Bind). Finally, the top three Zinc compounds were subjected to molecular dynamic simulation. The binding MMGBSA data suggests that ZINC000257261703 and ZINC000012405780 can be taken for in vitro and in vivo studies as they have lesser MMGBSA energy towards the cofactor binding site of NSD1 than the sinefungin. Our data validates NSD1 as a cancer drug target and provides promising structures that can be utilized for further lead optimization and rational drug design to open new gateways in the field of cancer therapeutics.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00158-0.

Evaluating Biofilm Inhibitory Potential in Fish Pathogen, Aeromonas hydrophila by Agricultural Waste Extracts and Assessment of Aerolysin Inhibitors Using In Silico Approach

Aeromonas hydrophila, an opportunistic bacteria, causes several devastating diseases in humans and animals, particularly aquatic species. Antibiotics have been constrained by the rise of antibiotic resistance caused by drug overuse. Therefore, new strategies are required to prevent appropriate antibiotic inability from antibiotic-resistant strains. Aerolysin is essential for A. hydrophila pathogenesis and has been proposed as a potential target for inventing drugs with anti-virulence properties. It is a unique method of disease prevention in fish to block the quorum-sensing mechanism of A. hydrophila. In SEM analysis, the crude solvent extracts of both groundnut shells and black gram pods exhibited a reduction of aerolysin formation and biofilm matrix formation by blocking the QS in A. hydrophila. Morphological changes were identified in the extracts treated bacterial cells. Furthermore, in previous studies, 34 ligands were identified with potential antibacterial metabolites from agricultural wastes, groundnut shells, and black gram pods using a literature survey. Twelve potent metabolites showed interactions between aerolysin and metabolites during molecular docking analysis, in that H-Pyran-4-one-2,3 dihydro-3,5 dihydroxy-6-methyl (-5.3 kcal/mol) and 2-Hexyldecanoic acid (-5.2 kcal/mol) showed promising results with potential hydrogen bond interactions with aerolysin. These metabolites showed a better binding affinity with aerolysin for 100 ns in molecular simulation dynamics. These findings point to a novel strategy for developing drugs using metabolites from agricultural wastes that may be feasible pharmacological solutions for treating A. hydrophila infections for the betterment of aquaculture.

Yohimbine Alleviates Oxidative Stress and Suppresses Aerobic Cysteine Metabolism Elevated in the Rat Liver of High-Fat Diet-Fed Rats

Yohimbine is a small indole alkaloid derived from the bark of the yohimbe tree with documented biological activity, including anti-inflammatory, erectile dysfunction relieving, and fat-burning properties. Hydrogen sulfide (H₂S) and sulfane sulfur-containing compounds are regarded as important molecules in redox regulation and are involved in many physiological processes. Recently, their role in the pathophysiology of obesity and obesity-induced liver injury was also reported. The aim of the present study was to verify whether the mechanism of biological activity of yohimbine is related to reactive sulfur species formed during cysteine catabolism. We tested the effect of yohimbine at doses of 2 and 5 mg/kg/day administered for 30 days on aerobic and anaerobic catabolism of cysteine and oxidative processes in the liver of high-fat diet (HFD)-induced obese rats. Our study revealed that HFD resulted in a decrease in cysteine and sulfane sulfur levels in the liver, while sulfates were elevated. In the liver of obese rats, rhodanese expression was diminished while lipid peroxidation increased. Yohimbine did not influence sulfane sulfur and thiol levels in the liver of obese rats, however, this alkaloid at a dose of 5 mg decreased sulfates to the control level and induced expression of rhodanese. Moreover, it diminished hepatic lipid peroxidation. It can be concluded that HFD attenuates anaerobic and enhances aerobic cysteine catabolism and induces lipid peroxidation in the rat liver. Yohimbine at a dose of 5 mg/kg can alleviate oxidative stress and reduce elevated concentrations of sulfate probably by the induction of TST expression.

Mechanism of Magnolia Volatile Oil in the Treatment of Acute Pancreatitis Based on GC-MS, Network Pharmacology, and Molecular Docking

Objective

Magnoliae officinalis cortex (MOC) is one of the most frequently used traditional Chinese medicine (TCM) for the treatment of acute pancreatitis (AP). Magnolia volatile oil (MVO) is considered to be one of the main active ingredients in MOC for AP treatment. However, the underlying mechanism of MVO in AP therapy is unknown.

Methods

An integrated strategy of gas chromatography-mass spectrum (GC-MS), network pharmacology, and molecular docking simulation was employed to predict underlying mechanism of MVO in AP treatment. First, the compounds of MVO were identified by GC-MS, and the targets of the identified characteristic compounds were collected from several databases, as well as AP-related targets. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were carried out to obtain the mechanism. Moreover, the binding activity between core therapeutic targets and their corresponding compounds was evaluated by molecular docking simulation.

Results

GC-MS results showed a total of 35 compounds that appeared in at least 18 out of 20 chromatograms were considered as characteristic compounds of MVO, and 33 compounds of those were identified. Network analysis demonstrated that 33 compounds regulated 142 AP-related targets. Of those, 8 compounds (α-eudesmol, γ-eudesmol, (-)-terpinen-4-ol, terpineol, hinesol, linalool, borneol, and β-eudesmol) and 8 targets (TNF, IL-1β, PPARγ, PPARα, PTGS2, NCOA1, CNR1, and ESR1) have a close relationship with AP treatment and were recognized as the key active compounds and the core therapeutic targets, respectively. The 142 targets were involved in both inflammation and calcium overload-related biological pathways, such as neuroactive ligand-receptor interaction, estrogen, MAPK, and calcium signaling pathway. Moreover, molecular docking simulation indicated that the 8 core therapeutic targets strongly interacted with their corresponding compounds.

Conclusions

In summary, the present study elucidated that the efficacy of MVO in AP treatment might be attributed to anti-inflammation and inhibition of calcium overload through multicomponents and multitargets.

Identification of Potential Molecular Targets and Active Ingredients of Mingmu Dihuang Pill for the Treatment of Diabetic Retinopathy Based on Network Pharmacology

Objective. Mingmu Dihuang Pill (MMDHP) is a traditional Chinese formula that has shown remarkable improvements of dry eyes, tearing, and blurry vision; however, the mechanisms underlying MMDHP treatment for diabetic retinopathy have not been fully understood. This study is aimed at identifying the molecular targets and active ingredients of MMDHP for the treatment of diabetic retinopathy based on network pharmacology. Methods. All active ingredients of MMDHP were retrieved from TCMSP and BATMAN-TCM databases, and the targets of active ingredients of MMDHP were predicted on the SwissTargetPrediction website. Diabetic retinopathy-related target sets were retrieved from GeneCards and OMIM databases, and the intersecting targets between targets of active ingredients of MMDHP and potential therapeutic targets of diabetic retinopathy were collected to generate the traditional Chinese medicine-ingredient-target-diabetic retinopathy network and to create the protein-protein interaction network. In addition, GO terms and KEGG pathway enrichment analyses were performed to identify the potential pathways, and molecular docking was employed to verify the binding of active ingredients of MMDHP to key targets of diabetic retinopathy. Results. Network pharmacology predicted 183 active ingredients and 904 targets from MMDHP, and 203 targets were intersected with the therapeutic targets of diabetic retinopathy. The top 10 hub targets included PIK3RA, TP53, SRC, JUN, HRAS, AKT1, VEGFA, EGFR, ESR1, and PI3KCA. GO terms and KEGG pathway enrichment analyses identified AGE-RAGE, PI3K-AKT, and Rap1 signaling pathways as major pathways involved in MMDHP treatment for diabetic retinopathy. Molecular docking confirmed a good binding affinity of active ingredients of MMDHP, including luteolin, acacetin, naringenin, and alisol B, with AKT1, SRC, and VEGFA as the three key targets of diabetic retinopathy. Conclusion. MMDHP may be effective for the treatment of diabetic retinopathy through active ingredients luteolin, acacetin, naringenin, and alisol B via AKT1, SRC, and VEGFA in AGE-RAGE, PI3K-AKT, and Rap1 signaling pathways.

Ellagic Acid as a Potential Inhibitor against the Nonstructural Protein NS3 Helicase of Zika Virus: A Molecular Modelling Study

Zika virus is a member of the Flaviviridae family and genus Flavivirus, which has a phylogenetic relationship with spondweni virus. It spreads to humans through a mosquito bite. To identify potential inhibitors for the Zika virus with biosafety, we selected natural antiviral compounds isolated from plant sources and screened against NS3 helicase of the Zika virus. The enzymatic activity of the NS3 helicase is associated with the C-terminal region and is concerned with RNA synthesis and genome replication. It serves as a crucial target for the Zika virus. We carried out molecular docking for the target NS3 helicase against the selected 25 phytochemicals using AutoDock Vina software. Among the 25 plant compounds, we identified NS3 helicase-ellagic acid (-9.9 kcal/mol), NS3 helicase-hypericin (-9.8 kcal/mol), and NS3 helicase-pentagalloylglucose (-9.5 kcal/mol) as the best binding affinity compounds based on their binding energies. To understand the stability of these complexes, molecular dynamic simulations were executed and the trajectory analysis exposed that the NS3 helicase-ellagic acid complex possesses greater stability than the other two complexes such as NS3 helicase-hypericin and NS3 helicase-pentagalloylglucose. The ADMET property prediction of these compounds resulted in nontoxicity and noncarcinogenicity.

The dose-effect association between acupuncture sessions and its effects on major depressive disorder: A meta-regression of randomized controlled trials

BACKGROUND

The benefits of acupuncture on Major depressive disorder (MDD) have been well established in previous studies. However, uncertainty exists regarding the dose-effect relationship between acupuncture and MDD. This study aims to explore the association between acupuncture and its effects on MDD based on previously published data.

METHODS

Nine databases were searched from inception until 10th September 2021. Randomized controlled trials that compared acupuncture with sham acupuncture, or anti-depressants, were included. The data extraction, and assessing the data quality and risk of bias completed by two researcher, respectively. A non-linear meta-regression approach with restricted cubic spline was used to investigate the dose-effect relationship between acupuncture sessions and their effects on the Hamilton rating scale for depression (HAMD) score.

RESULTS

Of the 20,835 citations screened, 62 studies (2269 patients of MDD) were included. The dose-effect meta-analysis suggested that acupuncture session was associated with a decline in HAMD scores. Overall, an increase in the number of acupuncture sessions received was associated with symptom improvement in MDD patients. After 8 acupuncture sessions, the HAMD score decreased from 17.68 (95% CI: -11.81, -4.80) to 8.30 (95% CI: 14.23-21.13). After 24 acupuncture sessions, a decrease in HAMD scores was observed in 51% of cases (95% CI: 48% to 54%). After 36 acupuncture sessions, the effect of improvement in HAMD scores peaked at 66% of cases (95% CI: 59% to 72%).

CONCLUSIONS

A dose-effect relationship was found between the number of acupuncture sessions and HAMD scores. 36 acupuncture sessions were associated with optimal clinical response.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021290143.

Identification of Putative Plant-Based ALR-2 Inhibitors to Treat Diabetic Peripheral Neuropathy

Diabetic peripheral neuropathy (DPN) is a common diabetes complication (DM). Aldose reductase -2 (ALR-2) is an oxidoreductase enzyme that is most extensively studied therapeutic target for diabetes-related complications that can be inhibited by epalrestat, which has severe adverse effects; hence the discovery of potent natural inhibitors is desired. In response, a pharmacophore model based on the properties of eplarestat was generated. The specified pharmacophore model searched the NuBBE_DB database of natural compounds for prospective lead candidates. To assess the drug-likeness and ADMET profile of the compounds, a series of in silico filtering procedures were applied. The compounds were then put through molecular docking and interaction analysis. In comparison to the reference drug, four compounds showed increased binding affinity and demonstrated critical residue interactions with greater stability and specificity. As a result, we have identified four potent inhibitors: ZINC000002895847, ZINC000002566593, ZINC000012447255, and ZINC000065074786, that could be used as pharmacological niches to develop novel ALR-2 inhibitors.

Homology Modeling and Molecular Docking Approaches for the Proposal of Novel Insecticides against the African Malaria Mosquito (Anopheles gambiae)

Vector-borne infectious diseases are responsible for the deaths of over 700,000 people annually, than 400,000 of them resulting from malaria. The mosquito Anopheles gambiae is one of the dominant vector species of human malaria transmission. A significant issue of the conventional insecticides which target the arthropod borne infectious diseases is their induced resistance. To overcome this inconvenience, insecticides with new modes of action are required. One of the most promising targets for the development of new potential insecticides as evidenced by current studies is the D1-like dopamine receptor (DAR). To get a deeper understanding of the structural information of this receptor, the 3D homology model was built. The possible sites within the protein were identified and the most probable binding site was highlighted. The homology model along with a series of DAR antagonists with known activity against Anopheles gambiae larvae were used in docking experiments to gain insight into their intermolecular interactions. Furthermore, virtual screening of the natural compounds from the SPECS database led to the prediction of toxicity and environmental hazards for one potential new insecticide against the Anopheles gambiae mosquito.

Lestaurtinib Has the Potential to Inhibit the Proliferation of Hepatocellular Carcinoma Uncovered by Bioinformatics Analysis and Pharmacological Experiments

Patients diagnosed with hepatocellular carcinoma (HCC) seek a satisfactory prognosis. However, most HCC patients present a risk of recurrence, thus highlighting the lack of effectiveness of current treatments and the urgent need for improved treatment options. The purpose of this study was to identify new candidate factors in the STAT family, which is involved in hepatocellular carcinogenesis, and new targets for the treatment of HCC. Bioinformatics web resources, including Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), The Human Protein Atlas (HPA), Tumor Immune Estimation Resource (TIMER), and GSCALite, were used to identify candidate genes among the STAT family in HCC. STAT1 was significantly overexpressed in hepatocellular carcinoma. More meaningfully, the high STAT1 expression was significantly associated with poor prognosis. Therefore, STAT1 is expected to be a therapeutic target. The JAK2 inhibitor lestaurtinib was screened by the Genomics of Cancer Drug Sensitivity Project (GDSC) analysis. Pharmacological experiments showed that lestaurtinib has the ability to prevent cell migration and colony formation from single cells. We also found that STAT1 is involved in inflammatory responses and immune cell infiltration. Immune infiltration analysis revealed a strong association between STAT1 levels and immune cell abundance, immune biomarker levels, and immune checkpoints. This study suggests that STAT1 may be a key oncogene in hepatocellular carcinoma and provides evidence that the JAK2 inhibitor lestaurtinib is a potent antiproliferative agent that warrants further investigation as a targeted therapy for HCC.

Computational Saturation Mutagenesis to Investigate the Effects of Neurexin-1 Mutations on AlphaFold Structure

Neurexin-1 (NRXN1) is a membrane protein essential in synapse formation and cell signaling as a cell-adhesion molecule and cell-surface receptor. NRXN1 and its binding partner neuroligin have been associated with deficits in cognition. Recent genetics research has linked NRXN1 missense mutations to increased risk for brain disorders, including schizophrenia (SCZ) and autism spectrum disorder (ASD). Investigation of the structure-function relationship in NRXN1 has proven difficult due to a lack of the experimental full-length membrane protein structure. AlphaFold, a deep learning-based predictor, succeeds in high-quality protein structure prediction and offers a solution for membrane protein model construction. In the study, we applied a computational saturation mutagenesis method to analyze the systemic effects of missense mutations on protein functions in a human NRXN1 structure predicted from AlphaFold and an experimental Bos taurus structure. The folding energy changes were calculated to estimate the effects of the 29,540 mutations of AlphaFold model on protein stability. The comparative study on the experimental and computationally predicted structures shows that these energy changes are highly correlated, demonstrating the reliability of the AlphaFold structure for the downstream bioinformatics analysis. The energy calculation revealed that some target mutations associated with SCZ and ASD could make the protein unstable. The study can provide helpful information for characterizing the disease-causing mutations and elucidating the molecular mechanisms by which the variations cause SCZ and ASD. This methodology could provide the bioinformatics protocol to investigate the effects of target mutations on multiple AlphaFold structures.

Anti-Neuroinflammatory Components from Clausena lenis Drake

Clausena lenis Drake (C. lenis) is a folk medicinal herb to treat influenza, colds, bronchitis, and malaria. The 95% and 50% ethanol extract of C. lenis showed significant nitric oxide (NO) inhibition activity in BV-2 microglial cells stimulated by lipopolysaccharide (LPS). Bio-guided isolation of the active extract afforded five new compounds, including a chlorine-containing furoquinoline racemate, (±)-claulenine A (1), an amide alkaloid, claulenine B (2), a prenylated coumarin, claulenin A (3), a furocoumarin glucoside, clauleside A (4), and a multi-prenylated p-hydroxybenzaldehyde, claulenin B (5), along with 33 known ones. Their structures were determined via spectroscopic methods, and the absolute configurations of new compounds were assigned via the electronic circular dichroism (ECD) calculations and single-crystal X-ray diffraction analysis. Compounds 2, 23, 27, 28, 33, and 34 showed potent anti-neuroinflammatory effects on LPS-induced NO production in BV-2 microglial cells, with IC₅₀ values in the range of 17.6–40.9 μM. The possible mechanism was deduced to interact with iNOS through molecular docking.