Withanolide A Inhibits hIAPP aggregation: An In silico, Biophysical, and Drosophila-Based In Vivo Validation

Withanolide A Inhibits hIAPP aggregation: An In silico, Biophysical, and Drosophila-Based In Vivo Validation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Withanolide A Inhibits hIAPP aggregation: An In silico, Biophysical, and Drosophila-Based In Vivo Validation Smita Manjari Panda, Kalpanarani Dash, Devi Prashanna Behera, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9208858/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The aberrant aggregation of human islet amyloid polypeptide (hIAPP) or Amylin into toxic oligomers and fibrils leads to pancreatic β-cell dysfunction and progressive cell death, which is a key pathological feature of Type II diabetes mellitus (T2DM). In this study, we adopted a hybrid approach combining virtual screening and molecular dynamics (MD) simulation, with experimental validation, to identify inhibitors of hIAPP aggregation. Herein, we screened 2000 phytoconstituents from natural products using molecular docking, followed by in silico ADMET predictions. Withaferin A and Withanolide A (phytoconstituents of Ashwagandha) were found to be lead molecules with suitable drug-like properties. Next, we performed an 800 ns MD simulation to assess the stability and interaction dynamics of hIAPP-ligand complexes. Building on the computational screening, we further carried out a comprehensive experimental analysis to validate the inhibitory effects of lead molecules. The collective experimental results from the Thioflavin T (ThT) assays, combined with Confocal and Transmission Electron Microscopy (TEM), suggest that the ligands (preferably Withanolide A) have a potent inhibitory effect against hIAPP aggregation by increasing the lag phase and inhibiting fibril formation of hIAPP. For in vivo validation using Drosophila models, Withanolide A was found to mitigate hIAPP oligomer-induced toxicity by reducing apoptosis, necrosis, and oxidative stress in the Drosophila gut, as confirmed by multiple cell death staining assays and reactive oxygen species (ROS) analysis. Besides, in diabetic flies, Withanolide A lowered glucose levels, demonstrating anti-diabetic activity. Thus, this work, for the first time, suggests that Withanolide A may be a potential candidate for inhibiting hIAPP aggregation and as a T2DM drug. Biological sciences/Biochemistry Biological sciences/Biophysics Biological sciences/Computational biology and bioinformatics Biological sciences/Drug discovery Human islet amyloid polypeptide Diabetes Molecular docking MD simulation Withanolide A Drosophila Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Several chronic and neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and type 2 diabetes mellitus (T2DM), are linked to amyloidogenesis, which collectively contribute to rising global morbidity and mortality[ 1 – 3 ]. About 36 different human proteins misfold and turn into morphologically similar β-sheet-rich aggregates, also referred to as amyloid fibrils, that are linked to more than 50 diseases [ 3 – 5 ]. A complicated nucleation-polymerization process that involves several structural intermediates and changes from unstructured monomers to oligomers, protofilaments, and finally mature fibrils underlies amyloid aggregation [ 3 , 6 , 7 ], and the most significant approach for treating amyloid-associated disorders is to prevent misfolded peptides from aggregating. Human Islet Amyloid Polypeptide (hIAPP), also known as Amylin, a 37-residue neuroendocrine hormone peptide, is secreted from the pancreatic β-cell alongside insulin and ranks among the most amyloidogenic proteins [ 4 , 8 , 9 ]. Numerous scientific studies have demonstrated that aggregation of hIAPP leads to amyloid deposition in the pancreatic tissue of ~ 90% T2DM patients, making it a key pathological hallmark of T2DM [ 4 , 10 ]. A correlation was observed between hIAPP deposition and β-cell death in pancreatic islets of Langerhans. These findings suggest that the cytotoxic properties of hIAPP directly contribute to the cellular dysfunction in T2DM [ 11 ]. Besides, the β-cell dysfunction of T2DM patients is associated with various pathogenic mechanisms, including membrane disruption, mitochondrial impairment, ER stress with UPR (unfolded protein response) activation, inflammatory cascades, hIAPP-induced reactive oxygen species (ROS)-mediated, and programmed cell death [ 12 , 13 ]. Given this, hIAPP is an appealing molecular target for drug development and combating the progression of T2DM [ 11 , 14 ]. A significant amount of work has been invested in identifying various types of amyloid inhibitors that prevent misfolded amyloid peptides from clumping together, including small natural molecules [ 15 – 24 ]. These molecules target either the monomeric or intermediate state of the amyloid precursor, aiming to inhibit amyloid production at an early stage [ 11 , 25 ]. For instance, naturally occurring organic compounds, such as polyphenols, have been shown to prevent hIAPP aggregation [ 26 ]. Similarly, it has been demonstrated that morin hydrate breaks the IAPP fibrils [ 27 , 28 ]. Substantial evidence suggests that resveratrol is the most potent anti-aggregative polyphenol, owing to its significantly higher binding affinity for the hIAPP pentamer [ 28 ]. A well-known natural molecule, the polyphenol epigallocatechin gallate [EGCG], binds to various amyloid peptides such as α-synuclein, amyloid beta, and κ-casein to disrupt their misfolding and aggregation pathways [ 29 , 30 ]. Similarly, curcumin, derived from turmeric, can inhibit the production of Aβ and α-synuclein fibrils in a dose-dependent manner [ 31 , 32 ]. These findings underscore the relevance and therapeutic potential of naturally occurring molecules. In light of this, the foundation of our study builds upon our previous computational work, where we identified two phytoconstituents of Withania Somnifera (Withaferin A and Withacoagulin) as inhibitors of hIAPP after screening our lab-made library of 1000 natural compounds [ 33 ]. However, MD simulation analysis showed that Withaferin A exhibits stable binding to hIAPP, whereas Withacoagulin induces greater flexibility (higher RMSF) in hIAPP and an aggregation-prone structural change. Therefore, we prioritize Withaferin A, and expanded the virtual screening to 2,000 natural compounds to identify additional effective inhibitors. Following this, we have also adopted an experimental approach to confirm the inhibitory potential of the selected compounds. Every experiment was conducted with and without the inhibitors. The well-known Thioflavin T (ThT) fluorescence assay was used to track the kinetics of amyloid aggregation. Additionally, the morphological characteristics of hIAPP aggregates were characterized using confocal microscopy and transmission electron microscopy (TEM). Drosophila melanogaster has evolved into a fundamental model organism for investigating cell death associated with protein aggregation, due to the remarkable conservation of its genome and the parallels between Drosophila and human biology. Their genetic traceability and short lifespan make them ideal for investigating the processes behind protein aggregation and its effects on cellular and tissue levels [ 34 ]. Therefore, to assess biological relevance, we have used Drosophila melanogaster as an in vivo model. We also tested the anti-diabetic effects of lead compounds on the free glucose levels of diabetic Drosophila. The study will yield a potential drug candidate for the treatment of T2DM. 2. Materials and Methods 2.1. Virtual screening and lead optimization 2.1.1. hIAPP and ligands preparation The crystal structure of the hIAPP was retrieved from the RCSB Protein Data Bank (PDB ID: 2KB8) ( https://www.rcsb.org/structure/2KB8 ). Autodock tool ( https://ccsb.scripps.edu/mgltools/1-5-7/ ) was used to compute partial charges using Gasteiger’s method, and polar hydrogen atoms were added and then converted to .pdbqt format. We have created a homemade database of 2000 phytoconstituents of natural products, and the structures of the molecules were obtained from the PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ) database, LOTUS ( https://lotus.naturalproducts.net/ ), and IMPATT2.0 ( https://cb.imsc.res.in/imppat/ )[ 35 , 36 ]. Using the Open Babel toolbox [ 37 ], these ligand molecules were then optimized and converted to the .pdbqt format. 2.1.2. Molecular docking The best binding poses and interactions between ligand molecules and target receptors can be predicted using molecular docking. The popular and reliable program Autodock Vina is used in this work to investigate the binding interaction of ligand molecules with the hIAPP [ 38 ]. The lowest energy conformation was determined using a quasi-Newtonian optimization technique and a hybrid scoring function. In the docking study, a grid box was generated with a grid box center at (-8.734, -2.184, -2.885) with a grid spacing of 14 Å, 88 Å, and 16 Å in the X, Y, and Z dimensions, respectively. The exhaustiveness of the search was set to 10. For each docking simulation, nine docking conformations are generated, and the conformation with the lowest docking energy is selected as the preferred docking conformation. The maximum energy difference between the best and worst binding modes was set to 3 kcal/mol. The docking results are analyzed using Pymol 2.5.4 ( https://pymol.org/2/ ), ligplot+, and Discovery Studio ( https://discover.3ds.com/ ). 2.1.3. In-Silico ADMET analysis Evaluation of pharmacokinetic properties is essential in the early stages of drug development and screening. Several essential processes, including absorption, distribution, metabolism, excretion, and Toxicity (ADMET), are involved in pharmacokinetics. The SwissADME tool was used to calculate the physiological and pharmacokinetic properties from the SMILES structures of the compounds ( http://www.swissadme.ch/ ) [ 39 ]. Furthermore, to predict toxicity, we utilized a novel, freely accessible web server, pkCSM ( https://biosig.lab.uq.edu.au/pkcsm/ ) [ 40 ]. In the early stages of drug discovery, in silico ADMET analysis significantly reduces the risk of failure in clinical trials. The virtual screening, including the ADMET evaluation protocol used here, is established and reported in our previous literature [ 33 , 41 ]. 2.2. Classical molecular dynamics for hIAPP-ligand interaction The time-dependent dynamics of hIAPP (in free and bound form) were carried out using classical molecular dynamics (MD) simulation using Gromacs 2022.2 with the CHARMM 36 force field [ 42 ]. The CGENFF server was used to generate parameters of Withaferin A and Withanolide A [ 43 , 44 ]. Every protein-ligand combination was solvated in the TIP3P model [ 45 ]. For neutralization, the proper quantity of counterions (Na + and Cl − ) was added. To prevent any steric clashes, the resulting systems were energy-minimized in several steps, using a combination of steepest descent and conjugate gradient methods. Equilibration of the NVT and NPT ensembles was carried out for 20 ns for each system at 300 K. The particle mesh Ewald and force-switching methods were implemented for electrostatic and van der Waals interactions[ 46 ]. The velocity-rescaling scheme from the Berendsen thermostat and the isotropic-rescaling scheme from the Parrinello-Rahman barostat maintained the temperature and pressure during the simulation [ 47 , 48 ]. A final production run of 800 ns was performed for all the systems with a time step of 2 fs, and the frames from the trajectory were extracted at 20 ps intervals. The resulting MD trajectories were analyzed using the built-in tools of GROMACS. 2.3. Experimental 2.3.1. Materials hIAPP (with purity ≥ 95%): purchased from Anaspec, USA (AS-60804). Withaferin A (≥ 98%) (CFN91895) and Withanolide A (≥ 98%) (CFN91964): purchased from ChemFaces, China. Dimethyl sulfoxide (DMSO, ≥ 99.9%): purchased from HiMedia, India (MB058); thioflavin T (ThT, ≥ 98%): purchased from Sigma Aldrich Merck, Germany (2390-54-7). Sucrose: purchased from HiMedia, India (GRM601), Cornmeal: purchased from local store, Yeast: purchased from local store, Type I Agar: purchased from HiMedia, India (GRM666), Methyl paraben: purchased from HiMedia, India (GRM1899), Propionic acid: purchased from HiMedia, India (GRM3658), Paraformaldehyde: purchased from Sigma Aldrich Merck, Germany (STBK4638) purity 95%, Anhydrous glucose; purchased from HiMedia, India (MB037), Glucose oxidase reagent; purchased from Sigma-Aldrich, Merck Germany (G7793), O-dianisidine; purchased from Sigma Aldrich Merck, Germany (D2679), Acridine orange: purchased from HiMedia, India (GRM3087), Glycerol: purchased from HiMedia, India (MB060), Propidium Iodide: purchased from HiMedia, India (TC252), DAPI: purchased from HiMedia, India (MB097), DCFH-DA: purchased from Sigma-Aldrich Merck, Germany (35845), Nitro blue tetrazolium (NBT): purchased from HiMedia, India (RM578), Glacial acetic acid: purchased from HiMedia, India (AS001). 2.3.2. hIAPP and ligands solution preparation The hIAPP stock was prepared by dissolving 1 mg of the original packaged peptide into 500 µl of DMSO. Alliquots were made of 15 µl and stored at -80°C. The stock aliquots were dissolved in 20 mM phosphate buffer (PBS, pH 7.4) before the experiments. For ligands’ solution, primary stock of Withaferin A (11 mM) and Withanolide A (8 mM) were prepared by dissolving 0.4 µg and 0.5 µg, respectively, in DMSO. These primary stocks were aliquoted and stored at -20°C until use. Secondary stocks (100 µM) were freshly made in 20 mM PBS (pH 7.4) prior to each experiment, and final working concentrations were adjusted to achieve a 1:1 molar ratio with hIAPP. 2.3.3. Thioflavin T (ThT) aggregation assay To monitor the aggregation of hIAPP and evaluate the inhibitory effects of selected lead molecules (Withaferin A and Withanolide A), we performed Thioflavin T (ThT) fluorescence assay[ 49 ]. ThT produces enhanced fluorescence after binding specifically with amyloid fibrils, enabling real-time tracking of fibrillation kinetics. 5 mg ThT Powder was first dissolved in 1 ml of PBS (pH 7.4). The stock solution was kept in the dark, and prior to the experiment, a working solution of 10 µM was prepared by appropriate dilution. The FluoroMax-4P spectrofluorimeter (Horiba Jobin Yvon, USA) with a 1 cm quartz cuvette was used to record the fluorescence intensity. The readings were continuously recorded for the mixture containing 15 µM hIAPP (with or without inhibitor) and 10 µM ThT in PBS at excitation/emission wavelengths of 440/480 nm at regular intervals until the aggregation curve reached a plateau, indicating saturation of fibril production. 2.3.4. Transmission electron microscopy (TEM) The hIAPP was incubated with or without inhibitors in 20 mM phosphate buffer (pH 7.4) at room temperature for 2 hours, and the samples were imaged by TEM to assess ligand-mediated inhibition of fibril formation. For TEM grid preparation, 5 µL of each sample was carefully deposited onto 200-mesh carbon-coated copper grids and incubated at room temperature for 10 minutes to ensure adequate adsorption. Excess liquid was washed out gently with DI water. High-resolution TEM images of these samples were then taken using a FEI, Tecnai G2 TF30-ST instrument operated at 300 kV, enabling detailed visualization of hIAPP aggregate morphology. 2.3.5. Confocal microscopy Morphological differences in hIAPP aggregates, with or without inhibitors (1:1 molar ratio), were assessed using confocal fluorescence microscopy (Leica STELLARIS 5). hIAPP samples were prepared by ageing 15 µM hIAPP with 10 µM ThT in 20 mM PBS and kept at room temperature for 2 hours. Then the solution was drop-casted onto a glass slide covered with a coverslip and left to dry before imaging. Excitation was set to 440 nm, the ThT maximum, to ensure optimal contrast and enable high-resolution imaging of aggregate morphology. 2.3.6. In vivo assay in Drosophila melanogaster 2.3.6.1. Fly maintenance and standard doses of drugs The experiments used the Oregon R strain of Drosophila melanogaster, obtained from the C-CAMP Fly Facility in Bangalore, India. The flies were reared on a standard diet consisting of 0.15 M sucrose, cornmeal, yeast, and Type I agar, supplemented with methyl paraben and propionic acid to prevent microbial and fungal contamination. Flies were housed in vials at a ratio of five females to three males and maintained under controlled environmental conditions of 60% relative humidity, a constant temperature of 25°C, and a 12-hour light/dark cycle. The flies were transferred to freshly prepared food in a male-to-female ratio of 3:5. After seven days, third-instar larvae were collected from the control food medium for subsequent experiments. After the larvae were collected from the control food medium, they were correctly washed in 1X PBS and treated with the drug for 1.5 hours. Group1-(10–15) control larvae were treated with 1X PBS Group 2-(10–15) control larvae were treated with 15 µM hIAPP Group 3-(10–15) control larvae were treated with 15 µM hIAPP + 15 µM Withaferin A Group 4-(10–15) control larvae were treated with 15 µM hIAPP + 15 µM Withanolide A Group 5-(10–15) control larvae were treated with 15 µM Withaferin A in 1X PBS Group 6-(10–15) control larvae were treated with 15 µM Withanolide A in 1X PBS After 1.5 hours, larvae were collected from all groups and washed thoroughly with 1X PBS; all subsequent experiments were then performed. 2.3.6.2. NBT assay to detect ROS The nitro blue tetrazolium (NBT) assay assessed intracellular ROS levels in third-instar larvae. A total of 15 larvae per group were used for the assay. The larvae were first rinsed in 1X phosphate-buffered saline (PBS) and transferred to a 0.5 mL microcentrifuge tube with a bottom incision for hemolymph collection. This tube was placed inside a 1.5 mL collection tube. Each larva was punctured in the thoracic region to extract hemolymph using a pre-sterilized needle while on ice to prevent melanization. The tubes were centrifuged at 8000 rpm for 5 minutes at 4°C to separate the hemolymph. A 5 µL aliquot of the isolated hemolymph was transferred to a fresh tube and diluted with 10 µL of 1X PBS. An equal volume (15 µL) of 1.6 mM NBT solution was added, and the mixture was incubated in the dark for 30 minutes. Following incubation, the reaction was terminated by adding 30 µL of 100% glacial acetic acid for 5 minutes, followed by 150 µL of 50% glacial acetic acid. The optical density (OD) was measured at 595 nm, and the absorbance values were used to quantify ROS levels, with higher absorbance indicating increased ROS concentrations [ 50 ]. 2.3.6.3. DAPI-DCFH-DA staining to detect nuclear fragmentation Third-instar larval gut tissues were subjected to staining with 4',6-diamidino-2-phenylindole (DAPI) and 2',7’-dichlorodihydrofluorescein diacetate (DCFDA). DAPI binds to the major groove of DNA at A: T-rich regions, enabling the detection of nuclear damage. Meanwhile, DCFDA interacts with intracellular ROS, emitting green fluorescence proportional to ROS levels [ 51 ]. Larvae were dissected in cold 1X phosphate-buffered saline (PBS) under a stereomicroscope (Motic 3Plus, India) to isolate the gut tissues. The samples were then fixed in 4% paraformaldehyde (PFA) at 4°C overnight. Following fixation, PFA was removed, and the tissues were washed three times with 1X PBS. Subsequently, the samples were rinsed twice with 1X PBST (PBS containing Tween-20) for 10 minutes. The gut tissues were then placed on a clean, grease-free slide and simultaneously stained with DCFDA and DAPI for 30 minutes and 5 minutes in the dark. To remove excess dye, samples were washed once with PBS and mounted using 20% glycerol before being covered with a coverslip. Fluorescent imaging was performed using a confocal microscope (Leica DMI8). 2.3.6.4. DAPI-PI staining to detect necrosis To quantify the extent of necrotic cell death induced by hIAPP protein, DAPI-PI (Propidium Iodide) staining was performed [ 52 ]. We administered hIAPP protein (15 µL) diluted in 1X PBS to third-instar Drosophila larvae for 1.5 hours. Throughout the incubation phase, the larvae only consumed the protein solution. We excised the gut from third-instar larvae after incubation and preserved them in 4% paraformaldehyde (PFA) for 30 minutes. Following fixation, the samples were rinsed in 1X PBS twice for 10 minutes each. The samples were treated with 20 µL of PI (1 µg/mL) for 5 minutes, followed by 20 µL of DAPI (1 µg/mL) for 5 minutes. After incubation, the samples were washed with 1X PBS and mounted using 20% glycerol. Gut images showing the region of necrotic spots were acquired using a confocal microscope (Leica DMI8). 2.3.6.5. Acridine orange (AO) staining to detect apoptosis To quantify the extent of cell death induced by hIAPP protein, we administered hIAPP protein (15 µl) diluted in 1X PBS to third instar Drosophila larvae for 1.5 hours. Throughout the incubation phase, the larvae only consumed the protein solution. We excised the gut from third-instar larvae after incubation and preserved them in 4% paraformaldehyde (PFA) for 30 minutes. Following fixation, the samples were rinsed in 1X PBS twice for 10 minutes each. The samples were subsequently treated with 1% PBST for 10 minutes, followed by a 10-minute interval. The samples were treated with 20 µl of Acridine orange (1 µg/ml) for 15 minutes in the dark. After incubation, the samples were washed with 1X PBS and mounted using 20% glycerol. Gut images showing a region of cell death were acquired using a confocal microscope (Leica DMI8) at emission wavelengths of 520 nm. 2.3.6.6. Free glucose assay Control flies were cultivated on a conventional diet containing 0.15 M sucrose, cornmeal, yeast, and type I agar, supplemented with methyl paraben and propionic acid to inhibit microbial and fungal contamination. Diabetic flies were cultivated on a High Sucrose diet of 1.5 M sucrose, while maintaining all other ingredients constant. Drugs Withaferin A and Withanolide A were administered to the control food medium at a concentration of 15 µM. Flies subjected to a high sugar diet for 15 days were classified as diabetic flies. Diabetic flies were subsequently transferred to a diet containing Withaferin A and Withanolide A for an additional 7 days. Diabetic flies fed a standard diet for 7 days served as the positive control group. Following a 7-day treatment, the hemolymph glucose levels of 21-day-old adult flies were measured to evaluate the anti-diabetic efficacy of Withaferin A and Withanolide A. Flies from all experimental mediums (n = 10) were homogenized with 100 µL of chilled 1X PBS and stored in a mini cooler at -20°C. Glucose standards were prepared from a 1 mg/mL D-glucose stock and stored at -20°C. Thirty microliters of supernatants, glucose standards, and PBS blank solution were added to distinct wells of a 96-well plate, with each concentration represented in triplicate. The enzymatic reaction that converts D-glucose to gluconic acid commenced upon the addition of 100 µL of glucose oxidase/peroxidase reagent to each well. The plate was subsequently incubated at 37°C for one hour. Subsequently, 100 µL of 12N H 2 SO 4 was introduced to halt the reaction, resulting in a pinkish to purple coloration. The final absorbance was measured with a microplate reader at 540 nm [ 53 ]. 2.3.6.7. Statistics Data were presented as mean ± Standard deviation (SD). Statistical analyses were conducted using GraphPad Prism (GraphPad, San Diego, CA, USA). Single-parameter-based comparisons were made using one-way ANOVA. The Probability (P) values *P < 0.05, **P < 0.01, ***P 0.05 is non-significant (ns). 3. Results and Discussion 3.1. Virtual screening combined with ADMET filtering identifies potential candidates Our goal was to identify drug-like small molecules that could prevent hIAPP from forming amyloid, building on previous work targeting hIAPP. To this, we employed two-stage computational approaches: (1) molecular docking of our in-house natural compound library using cagnizifinol as a control inhibitor and (2) in-silico ADMET profiling of top-ranked compounds to shortlist the most promising candidates. Canagliflozin, a well-known FDA-approved anti-diabetic drug [ 11 ], had a docking score of -6.4 kcal/mol, which was the screening cut-off. We identified 13 molecules (listed in Table 1 ) with binding values above the cut-off and selected them for further study. As Lipinski’s rule of five [ 54 ] [molecular mass less than 500 Dalton, high lipophilicity (Log P < 5), hydrogen bond donors ≤ 5, and hydrogen bond acceptors ≤ 10] served as the primary filter for the drug-likeness, the compounds that satisfy this were considered for further evaluation. Furthermore, after excluding molecules that lacked essential drug-likeness characteristics based on Lipinski’s rule and other drug-likeness criteria, we assessed pharmacokinetics, which is crucial for four essential processes: absorption, distribution, metabolism, and excretion. It is noteworthy that Withanolide A (WLA) and Withanolide D (WLD), along with Withaferin A (WFA), meet this requirement, as seen in Table 1 . Water solubility is another critical factor in ADMET analysis, as it is necessary for drug distribution and absorption. Swiss ADME estimates solubility using the Log S scale by combining several topological approaches (ESOL, Ali, and Silicos IT) [ 39 , 55 ]. These selected compounds are moderately soluble to soluble. In addition, due to their high gastrointestinal (GI) absorption, these three compounds (Table 2 ) are suitable for regulatory approval and can be taken orally. An essential step in the drug discovery process is toxicity prediction, which ensures that possible compounds don't exhibit any adverse side effects. Using pkCSM, an in silico toxicity evaluation was conducted to assess potential toxicological issues associated with the compounds. The AMES test (AT), oral rat acute toxicity (LD50), hepatotoxicity (HT), and skin sensitization are all covered by the pkCSM. A popular technique for determining a compound’s ability to cause bacterial mutations is the AT. If the test comes out positive, the substance is mutagenic and could potentially lead to cancer. It is clear from Table 2 that none of the selected 3 compounds are mutagenic. The liver-related side effects observed in human patients taking 531 medications serve as the basis for the HT predictor. If any compound causes one or more physiological or clinical liver events that are closely linked to the disruption of liver function, it is considered hepatotoxic. Interestingly, the shortlisted compounds are also non-hepatotoxic. Table 1 Binding affinity (BA) of the top 13 molecules. Sl. No. Compounds [Database ID] BA (kcal/mol) 1 2-[(2E,4E,6E,8E,10E,12E,14E)-15-(4,4,7a-trimethyl-2,5,6,7-tetrahydro-1-benzofuran-2-yl)-6,11-dimethylhexadeca-2,4,6,8,10,12,14-heptaen-2-yl]-4,4,7a-trimethyl-2,5,6,7-tetrahydro-1-benzofuran [IMPHY002618] -7.1 2 Cryptoflavin [IMPHY005981] -7.1 3 Zeaxanthin [IMPHY011785] -6.8 4 Withanolide A [IMPHY000090] -6.8 5 Withaferin A [265237] (Previous work) -6.8 6 alpha-Carotene [IMPHY011609] -6.7 7 Withasomidienone [IMPHY000630] -6.5 8 13-Amino-4-hydroxy-9,6a,8a-trimethyl(1,3,4,5,6,7,8,14,14a,14b,6a,6b,8a-trideca hydrobenzo[1''',2'''-3'',4'']benzo[1'',2''-4',3']benzo[1',2'-5,1]cyclopenta[3, 2-d]thiopheno[2,3-b]pyridin-12-yl) phenyl [IMPHY012701] -6.5 9 (2S,6S,7aR)-2-[(2Z,4E,6E,8E,10E,12E,14E,16E)-17-[(1R,4S)-4-hydroxy-2,6,6-trimethylcyclohex-2-en-1-yl]-6,11,15-trimethylheptadeca-2,4,6,8,10,12,14,16-octaen-2-yl]-4,4,7a-trimethyl-2,5,6,7-tetrahydro-1- [IMPHY004149] -6.5 10 Pamoic acid [IMPHY007087] -6.5 11 gamma-Carotene [IMPHY004383] -6.5 12 Pelankine [IMPHY000350] -6.5 13 Withanolide D [IMPHY003936] -6.4 Control Canagliflozin [24812758] -6.4 Table 2 In-silico ADMET parameters of selected molecules predicted by SWISS ADME and pkCSM. Compounds Physiological parameters Water solubility Log S Pharmacokinetic properties of selected molecules MW NRB NHA NHD TPSA Log P DL ESOL Ali SILICOS-IT GI Abs AT HT LD50 SS Withanolide A (WLA) 470.6 2 6 2 96.36 3.39 Yes -4.67 -4.95 -3.78 High No No 2.353 No Withaferin A (WFA) 470.6 3 6 2 96.36 3.42 Yes -4.97 -5.55 -3.79 High No No 2.294 No Withanolide D (WLD) 470.6 2 6 2 96.36 3.39 Yes -4.59 -4.81 -3.78 High No No 2.327 No MW: molecular weight, NRB: No. of rotatable bonds, NHA: No. of H-bond acceptors, NHD: No. of H-bond donors, TPSA: Topological polar surface area, DL: Drug likeness (Lipinski’s Rule), GI Abs: Gastrointestinal absorption, AT: AMES Toxicity, HT: Hepatotoxicity, LD50: Oral Rat Acute Toxicity, SS: Skin sensitization. Water solubility: solubility: highly soluble (> 0), very soluble (< 0), soluble ( < − 2), moderately soluble ( < − 4), poorly soluble ( < − 6), and insoluble ( < − 10). Before experimental validation, this study employed in silico strategies to identify compounds with minimal predicted toxicity, ensuring the safety and drug-likeness of the shortlisted candidates. Based on the binding affinity values obtained from molecular docking, Withaferin A (WFA) and Withanolide A (WLA) were identified as the most promising candidates among the three shortlisted compounds. Both showed promising drug-like qualities and the best binding affinity (-6.8 kcal/mol) for hIAPP. The binding poses and 2D interaction profiles of WFA and WLA with hIAPP are illustrated in Fig. 1 . We then performed classical molecular dynamics (MD) simulation to better examine the binding behaviour and structural stability of these molecules. The dynamic interactions, conformational changes, and temporal stability were all thoroughly investigated. 3.2. Interaction dynamics of the hIAPP monomer with selected top ligands Although virtual screening provides an initial assessment of the binding potential of lead compounds, it fails to account for the dynamic characteristics of protein-ligand interactions. This binding is governed by dynamic conformational changes and can be influenced by structural fluctuations of hIAPP. We therefore performed an MD simulation of 800 ns for both the Apo and holo forms of hIAPP to provide deeper insights into the interaction mechanism and validate the stability and inhibitory potential of the lead molecules with hIAPP under near-physiological conditions. First, to ensure equilibrium and system stability during the simulations, we have calculated the root-mean-square deviation (RMSD) over 800 ns. The time evolution of the RMSD plot illustrated in Fig. 2 (a) suggests that all the systems (only hIAPP, hIAPP + Withaferin A, and hIAPP + Withanolide A) converge and attain stability. The average RMSD of only hIAPP, hIAPP + Withaferin A, and hIAPP + Withanolide A are 1.133 ± 0.159 nm, 0.577 ± 0.153 nm, and 0.400 ± 0.100 nm, respectively. From the average RMSD values and the RMSD plot, it is evident that the ligand-bound forms exhibit lower RMSD values than the apo form. In fact, Withanolide A-bound hIAPP has the least RMSD, indicating the most stable structure. Further, to check the flexibility of hIAPP upon binding with the ligands, residue-wise root mean square fluctuation (RMSF) was calculated and plotted for apo hIAPP and its complexes with Withaferin A and Withanolide A [Fig. 2 (b) ]. The average RMSF value for apo hIAPP was 0.399 ± 0.152 nm, while in the presence of Withaferin A and Withanolide A, the values are 0.594 ± 0.227 nm and 0.430 ± 0.158 nm, respectively. The average RMSF values and the RMSF plot indicate that Withanolide A-bound hIAPP shows reduced fluctuation as compared to Withaferin A-bound form, suggesting less flexibility of hIAPP. Interestingly, in the case of Withanolide A, reduced fluctuation of the aggregation-prone region [20–29 amino acids (AA)] [ 10 ], indicating a lowering of the flexibility and aggregation propensity. During the simulation, this can also be linked to the helix content of the hIAPP. The helix content of 20–29 AA is higher than that of the apo and Withaferin A-bound form, as seen in Fig. 2 (c) , which could be the cause of the decrease in fluctuation around this region. To gain a better understanding of the structural stability of the aggregation-prone region 20–29 AA of hIAPP both before and during Withaferin A and Withanolide A binding, we next examined the compactness parameter of the structure by computing the radius of gyration (Rg) and solvent accessible surface area (SASA) of the aggregation-prone region 20–29 AA. The Rg plot in Fig. 2 (d) shows that the structural dynamics of hIAPP in the 20–29 AA region remain stable throughout the simulation. The average Rg values for apo, Withaferin A, and Withanolide A-bound forms are 0.558 ± 0.010 nm, 0.568 ± 0.015 nm, and 0.566 ± 0.011 nm, respectively. Additionally, stable structural dynamics are indicated by no significant change in the Rg values of hIAPP 20−29 upon complexation with Withaferin A and Withanolide A, suggesting the structural integrity of all three systems of hIAPP20-29 remained unaltered. We achieved a stable Rg equilibrium during the simulation period and did not detect any notable structural shift in hIAPP 20−29 when Withaferin A and Withanolide A were present. Moreover, to examine the effect of Withaferin A and Withanolide A binding on the aggregation-prone region and its solvent exposure, we have calculated SASA for hIAPP 20−29 throughout the simulation trajectory. There was a slight change to hIAPP 20−29 ’s SASA observed after the binding of Withaferin A and Withanolide A. The SASA values for hIAPP 20−29 , hIAPP 20−29 + Withaferin A complex, and hIAPP 20−29 + Withanolide A complex were estimated to be 12.183 ± 0.369, 11.720 ± 0.394, and 11.722 ± 0.383 nm 2 , respectively. The SASA for the 800 ns simulation trajectory plotted in Fig. 2 (e) and average SASA values suggest that the ligand-bound forms exhibit less solvent accessibility than the apo form. Overall, the SASA of ligand-bound systems appears to attain a stable equilibrium without any major peaks during the simulation, indicating the stability of hIAPP's compactness in the presence of Withaferin A and Withanolide A. Furthermore, to understand whether Withaferin A and Withanolide A bind to hIAPP in the same manner, as depicted by the docking study, the intermolecular H-bonds formed in the hIAPP + Withaferin A and hIAPP + Withanolide A complexes were calculated for the simulation trajectory. The H bonds formed between Withaferin A and Withanolide A, with hIAPP paired within 0.35 nm, were calculated and plotted as shown in Fig. 2 (f) . The analysis indicates that Withaferin A and Withanolide A form up to 8 and 7 H-bonds, respectively, during the simulation, suggesting strong and stable interactions with hIAPP. Overall, the RMSD, RMSF, Rg, SASA, and hydrogen bond analysis indicate that Withanolide A and Withaferin A form stable structures and interact strongly with hIAPP. Interestingly, Withanolide A causes a slight structural change in the hIAPP aggregation-prone area, making the protein less flexible and less prone to aggregation, indicating that it is the most potent hIAPP inhibitor. These computational findings provide a strong rationale for pursuing further experimental validation to substantiate the inhibitory activity and evaluate its therapeutic relevance. 3.3. Ligand-mediated suppression of hIAPP amyloid formation The in vitro complex kinetics of hIAPP, like those of other amyloidogenic polypeptides, exhibit a lag phase in which small aggregates form, followed by an exponential phase, also referred to as the elongation phase, and an equilibrium phase (plateau phase) in which amyloid fibrils are formed. The ThT, one of the most widely used dyes for determining the kinetics of amyloid fibril formation and for screening potential therapeutics to prevent fibril formation, tracked the rate of amyloid formation by hIAPP. As anticipated, ThT fluorescence profiles showed that hIAPP at a concentration of 15 µM displayed distinctive sigmoidal aggregation kinetics, characterized by three distinct phases: an initial lag phase (~ 0.51 min), a rapid elongation phase (~ 51 min to 85 min), and a final plateau phase (after 85 min). The three phases can be easily distinguished by the variation in ThT intensity, as shown in Fig. 3 (a) . Further, to evaluate the inhibitory potential of the top-ranked ligands (Withaferin A and Withanolide A) found through virtual screening, we carried out kinetic experiments using hIAPP-to-ligand molar ratios (1:1) at a constant peptide concentration (15 µM). Interestingly, Fig. 3 (a) shows that effective inhibition of fibril formation was demonstrated by the addition of ligands, which caused a noticeable delay in fibril nucleation (lag phase: ~3.22 hr in the case of Withaferin A and 4.8 + hours in Withanolide A), delayed the aggregation kinetics throughout the development phase, and eventually resulted in lower final ThT fluorescence. In fact, the fibril intensity illustrated in the bar plot [Fig. 3 (b) ], the Withaferin A and Withanolide A suppressed fibrill formation by 49.74% and 97.60%. Additionally, pure Withaferin A and Withanolide A did not produce any ThT signal during a 5-hour incubation, confirming that these ligands do not influence ThT fluorescence. The shift in kinetics suggests that both ligands prevent or reduce hIAPP aggregation by interfering with the nucleation and elongation stages of fibril formation, highlighting the ligands' potential as inhibitors of amyloid formation. 3.4. Disruption of hIAPP fibril morphology by WFA & WLA To complement the kinetic experiments and provide more profound morphological insights, we conducted a thorough analysis of hIAPP aggregation using a combination of confocal microscopy and TEM. Confocal microscopy images provide high-resolution, real-time visualisation of hIAPP aggregates, making them ideal for assessing fluorescence intensity and overall fibril distribution. From Fig. 4 (a-c) , at the fibril time point, a strong ThT fluorescence signal was observed in only hIAPP, indicating widespread fibril formation. In contrast, hIAPP co-incubated with ligands exhibited markedly reduced fluorescence intensity and aggregate distribution, especially showing the least fluorescence signal in the presence of Withanolide A. Similarly, TEM images [Fig. 4 (d-f) ] illustrate the density of amyloid aggregates. They clearly indicate that amyloid formation is reduced in the presence of ligands. Hence, both the ligands disrupt the morphology of hIAPP. Additionally, from both confocal and TEM images, Withanolide A exhibits the most potent inhibitory effect, with minimal fibril formation, which is also in accordance with the ThT assay (Fig. 3 ). 3.4. NBT assay reveals antioxidative effects of Withaferin A and Withanolide A against hIAPP-induced toxicity The NBT reduction test was used to determine intracellular ROS levels in the hemolymph of third-instar Drosophila larvae. This assay has been used as an indicator of superoxide anion (O₂⁻) generation in cells, as the yellow-coloured NBT dye is converted to the blue-coloured formazan upon binding superoxide radicals. NBT, as an electrophilic dicationic molecule, readily accepts electrons from intracellular electron donors. Superoxide anions in anhydrous solution convert NBT to monoformazan, which is detected quantitatively at 595 nm [ 56 ]. A bar plot of the absorbance values for all experimental groups: control, Withaferin A (WFA), Withanolide A (WLA), and hIAPP-treated (in the presence and absence of WFA and WLA) is illustrated in Fig. 5 . The control group exhibited a mean absorbance of 0.325 ± 0.022, whereas hIAPP-treated larvae had a considerably higher absorbance of 0.626 ± 0.025 (p < 0.001) with the same sample volume, indicating enhanced superoxide production. However, the absorbance values for the hIAPP + WFA and hIAPP + WLA groups were 0.466 ± 0.015 (p < 0.001) and 0.421 ± 0.010 (p < 0.001), respectively, indicating a considerable reduction of hIAPP-induced ROS. Additionally, we evaluated the antioxidant potential of only WFA and WLA (at the same working concentration and for the same duration in PBS medium) in non-treated third-instar larvae grown in standard food medium, and considered them as positive controls. Here, the positive control groups, WFA and WLA-treated larvae, showed no significant increase in the absorbance values, which are 0.380 ± 0.010 (p < 0.05) and 0.300 ± 0.010 (p = ns), respectively, as compared to the non-treated larvae, indicating that these chemicals did not generate oxidative stress under normal physiological conditions. Thus, the NBT assay quantitatively estimates oxidative stress in hIAPP-treated Drosophila larvae, giving biochemical proof of the destructive effects of hIAPP aggregation in the gut. The hIAPP-treated larvae had significantly higher ROS levels than the control group. The findings indicate that both WFA and WLA possess potent antioxidative properties that counteract hIAPP-induced ROS elevation in Drosophila larvae, with WLA exhibiting slightly greater efficacy. 3.5. WFA & WLA reduced nuclear fragmentation and ROS production detected by DAPI-DCFH-DA staining To evaluate DNA damage or nuclear fragmentation due to intracellular ROS accumulation in Drosophila larvae, DAPI and DCFH-DA staining were performed on dissected larval gut tissues for control, Withaferin A, Withanolide A, and hIAPP-treated (in the presence and absence of Withaferin A and Withanolide A). DAPI is a fluorescent-based DNA-binding dye that selectively binds with adenine-thymine (A–T)-rich regions within the minor groove of double-stranded DNA [ 57 ]. Upon binding, DAPI exhibits enhanced fluorescence intensity, producing a distinct blue emission when excited at 358 nm with an emission maximum around 461 nm [ 58 ]. This property enables sensitive visualization of nuclear structure and chromatin condensation, hallmarks of apoptosis or nuclear damage. When DNA is damaged or fragmented, the nuclear morphology and fluorescence pattern change, allowing qualitative visualization of nuclear integrity. Uniform arrangement of nucleus, round or oval nuclei shape with homogenous DAPI staining indicates a healthy nucleus and no DNA damage. Irregularity in nucleus shape and non-uniform or fragmented nucleus arrangement indicate DNA damage associated with early or late apoptosis. In contrast, DCFH-DA is a non-fluorescent probe that is cell-permeable, allowing it to assess intracellular ROS. Once internalized, DCFH-DA is cleaved by cytosolic esterases into non-fluorescent DCFH, which remains trapped within cells. ROS subsequently oxidize DCFH to form the highly fluorescent compound 2′,7′-dichlorofluorescein (DCF), exhibiting green fluorescence upon excitation at 488 nm with emission near 525 nm [ 53 ]. The fluorescence intensity of DCF directly correlates with the level of intracellular ROS, providing a sensitive readout of oxidative stress [ 59 ]. Representative confocal images corresponding to different treatment groups are shown in Fig. 6 . As depicted in Figs. 6 (a-aʺ) , the control larval gut exhibited intact nuclear morphology with low DCFH-DA fluorescence, indicating preserved nuclear integrity and negligible oxidative stress. Similarly, treatment with Withaferin A [Figs. 6 (b-bʺ) ] and Withanolide A [Figs. 6 (c-cʺ) ] alone did not result in noticeable nuclear fragmentation or ROS accumulation, suggesting that these compounds are non-toxic under the same experimental conditions. In contrast, as evident from Fig. 6 (d) , DAPI staining revealed pronounced nuclear fragmentation and chromatin condensation throughout the gut epithelium of hIAPP-treated larvae, indicating elevated nuclear damage and apoptosis. Furthermore, DCFH-DA staining demonstrated markedly higher green fluorescence intensity in the hIAPP-treated larval gut [Fig. 6 (d’) ], signifying excessive ROS accumulation. Conversely, larvae co-treated with hIAPP + Withaferin A and hIAPP + Withanolide A groups exhibited more intact and uniformly stained nuclei and displayed substantially reduced nuclear damage [Figs. 6 (e, f) ] and reduced green fluorescence [Figs. 6 (e’, f’) ]. The quantitative analysis of mean DCFH-DA fluorescence intensity is shown in Fig. 6 (g) , which corroborates these observations, showing significantly elevated ROS levels in the hIAPP-treated group that were substantially reduced upon co-treatment with Withaferin A or Withanolide A. Collectively, the observations from merged gut images [Figs. 6 (a’’-f’’) ] substantiate that hIAPP induces significant oxidative stress and nuclear damage in Drosophila gut tissues, while treatment with Withaferin A and Withanolide A effectively ameliorates these cytotoxic effects by reducing ROS accumulation and preserving nuclear integrity. 3.6. WFA & WLA reduced apoptotic cell death detected by AO staining To check the pro-apoptotic effect of hIAPP feeding in the 3rd instar Drosophila larval gut, Acridine Orange (AO) staining was performed. AO is a nucleic acid-selective fluorescent dye that readily penetrates cell membranes and intercalates into DNA and RNA. In apoptotic cells, AO preferentially binds to condensed chromatin, exploiting its differential staining of nucleic acids, appearing as bright green dots or crescent shapes within a green nucleus (due to DNA binding) in early stages, resulting in nuclei that appear bright green with highly condensed or fragmented morphology under fluorescence microscopy. Regions of cell death are thus visualized as distinct circular foci exhibiting intense green fluorescence [ 60 , 61 ]. Figure 7 illustrates confocal images of AO-stained larval gut tissues. As observed in Figs. 7 (a, b, c) , the control, Withaferin A-treated, and Withanolide A-treated, respectively, exhibited AO fluorescence with a uniform staining pattern, indicative of intact cellular and lysosomal integrity. Notably, larvae treated with hIAPP exhibited a marked increase in fluorescent apoptotic foci across various gut regions, indicating increased cell death and nuclear fragmentation, as illustrated in Fig. 7 (d) . In contrast, co-treatment of hIAPP with Withaferin A [Fig. 7 (e) ] and Withanolide A [Fig. 7 (f) ] led to a pronounced reduction in AO-positive apoptotic nuclei, suggesting adequate protection against hIAPP-induced cytotoxicity. 3.7. WFA & WLA reduced necrotic cell death detected by DAPI-PI staining To assess whether hIAPP aggregation induces oxidative damage, leading to loss of membrane integrity and necrotic cell death, particularly in metabolically active tissues such as the larval gut, DAPI-PI dual staining was performed. DAPI labels the nuclei of both viable and non-viable cells. Whereas propidium iodide (PI) is membrane-impermeable and selectively enters cells with compromised plasma membranes, binding to DNA and emitting red fluorescence. PI is a cationic, fluorescent, intercalating dye with a strong affinity for nucleic acids; however, its membrane-impermeability allows it to selectively stain cells with compromised plasma membranes. Upon entry, PI binds to DNA and RNA, emitting bright red fluorescence upon excitation at approximately 535 nm, with an emission maximum near 617 nm, making it a reliable marker for detecting necrotic or late apoptotic cells with lost membrane integrity [ 62 ]. Thus, DAPI-PI dual staining provides a powerful means to distinguish between normal, apoptotic, and necrotic cells. The gut tissues co-stained with DAPI-PI confocal images are shown in Fig. 8 . The DAPI-stained [Figs. 8 (a-f) ] gut tissue images, nuclear damages induced by hIAPP, and the protective effect of co-incubation with Withaferin A and Withanolide A are explained in detail in Section 3.5 . Further, as evident from the PI-stained gut images, the control larval gut and gut tissues treated with Withaferin A or Withanolide A exhibited no PI uptake [ Figs. 8 (a’-c’)] . Whereas, the larvae fed with hIAPP exhibited intense red fluorescence, indicative of necrotic cell death [Fig. 8 (d’) ]. Here, the necrotic regions appeared as bright red puncta localised around fragmented or condensed nuclei, confirming extensive membrane damage and cell death. Conversely, larvae co-treated with hIAPP + Withaferin A, and hIAPP + Withanolide A displayed an absence of red fluorescence, suggesting preservation of membrane integrity and a lack of necrotic damage [Figs. 8 (e’, f’) ]. Overall, the merged DAPI-PI images [Figs. 8 (a’’-f’’) ] corroborate the cytoprotective role of Withaferin A and Withanolide A against hIAPP-induced membrane disruption, highlighting their potential in mitigating necrotic cell death in Drosophila gut tissues. 3.8. WFA & WLA have a glucose-lowering effect in diabetic flies The hemolymph free glucose level of adult Drosophila melanogaster was quantified using the Glucose Oxidase-Peroxidase (GOD-POD) colourimetric enzymatic assay. This method is based on the oxidation of D-glucose to gluconic acid and hydrogen peroxide (H₂O₂) catalysed by the enzyme glucose oxidase [ 63 ]. The generated H₂O₂ subsequently reacts with the chromogenic substrate o -dianisidine in the presence of peroxidase to yield a pink-coloured product, the intensity of which is directly proportional to the glucose concentration. The absorbance of the reaction product was measured spectrophotometrically at 540 nm [ 51 ]. Previously, this method has been used to confirm type 2 diabetes in Drosophila fed with a high-sugar diet and a high-fat diet [ 64 ]. According to previous reports, several phytocompounds exhibiting pronounced anti diabetic potential were tested in the Drosophila diabetic model induced by a high-sucrose diet [ 65 , 66 ]. Hence, this experimental approach will also help us determine the anti-diabetic efficacy of Withaferin A and Withanolide A. Figure 9 displays a bar plot of the mean hemolymph-free glucose concentration. The mean hemolymph-free glucose concentration in 15-day-old adult control flies was 0.621 ± 0.029 mg/mL. Flies treated with a high-sucrose diet (HSD) exhibited a significant elevation in free glucose levels, reaching 0.962 ± 0.060 mg/mL (p < 0.001), confirming a diabetic-like metabolic phenotype. Next, to check the anti-diabetic potential of Withaferin A and Withanolide A, HSD-fed flies were treated with Withaferin A and Withanolide A for another 7 days on a standard diet. Treatment with Withaferin A significantly reduced glucose levels to 0.605 ± 0.059 mg/mL (p < 0.0001), while Withanolide A produced a more pronounced decrease to 0.564 ± 0.123 mg/mL (p = 0.0001). In contrast, flies transferred from the HSD group to non-treated standard food medium did not exhibit a statistically significant reduction in glucose concentration (0.916 ± 0.0341 mg/mL, p = ns). These results indicate that Withaferin A and Withanolide A effectively ameliorate HSD-induced hyperglycemia in Drosophila adults, with Withanolide A exhibiting superior glucose-lowering efficacy. This suggests that Withanolide A may be a better choice to improve metabolic homeostasis by enhancing insulin sensitivity or modulating oxidative stress and amyloid burden. 4. Conclusion The development and progression of over 50 protein diseases, including Alzheimer's disease, Parkinson's disease, prion disease, and Type 2 diabetes, are intimately linked to the assembly of amyloidogenic proteins and peptides into toxic oligomeric and fibrillar aggregates. The prevention and inhibition of pathogenic protein aggregation by potential molecules is currently the focus of significant research efforts aimed at developing therapeutic options against these diseases. In this study, from in-silico screening and MD Simulation, we found Withaferin A and Withanolide A derived from Ashwagandha have better binding affinity and stable interaction with hIAPP. Withanolide A induced structural change in the aggregation-prone region (20–29 AA). The ThT Assay clearly indicates that both molecules (ideally, Withanolide A) significantly slowed the aggregation kinetics, suggesting that they suppress the development of hIAPP fibrils. The morphological images from confocal and TEM suggest that Withanolide A has reduced the formation of hIAPP fibrils. Additionally, the in vivo study is noteworthy for its observation that both Withaferin A and Withanolide A mitigate hIAPP-induced toxicity in the Drosophila gut, reducing ROS generation, preserving nuclear integrity, and preventing necrotic cell death. Further, we also evaluated the antidiabetic activity of these molecules in diabetic flies. Although both molecules demonstrated glucose-lowering effects, it is worth noting that Withanolide A outperformed Withaferin A. To sum up, our integrated in silico , in vitro , and in vivo studies demonstrate that Withanolide A is a potent natural inhibitor of hIAPP toxicity and aggregation. It also shows glucose-lowering effects in Drosophila models with diabetes. To the best of our knowledge, this is the first report showing that Withanolide A is an inhibitor of hIAPP. Building on our in-silico , in-vitro, and in-vivo findings presented here, future research should extend to mammalian models to confirm the anti-diabetic potential of Withanolide A and explore its suitability for preclinical development. Declarations The authors declare no competing interests. Funding We acknowledge the Science and Engineering Research Board (SERB), DST, New Delhi, India (EMR/2017/003759) for funding. KD is thankful to UGC, New Delhi, India, for the financial support (Application number 211610018329) she has received for her PhD work. Author Contribution SMP: Conceptualization, methodology, data curation, data analysis, investigation, visualization, writing– original draft, writing– review & editing. KD: Investigation, data curation, visualization, data curation, writing– original draft, writing– review & editing. DPB: Investigation, visualization, data curation, formal analysis. MM: Supervision, resources, validation, writing– review & editing. HS: Supervision, resources, validation, writing– review & editing. UT: Conceptualization, supervision, validation, resources, funding acquisition, project administration, writing– review & editing. Acknowledgements SMP and UT thank the IIT (ISM), Dhanbad, for providing the required HPC facility and financial support. We also acknowledge the Science and Engineering Research Board (SERB), DST, New Delhi, India (EMR/2017/003759) for funding. 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Chem. 58 , 4066–4072 (2015). Panda, S. M., Tripathy, U. & Nandeshwar & In silico screening and identifying phytoconstituents of Withania somnifera as potent inhibitors of BRCA1 mutants: A therapeutic against breast cancer. Int. J. Biol. Macromol. 282 , 136977 (2024). Abraham, M. J. et al. High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2 . GROMACS , 19–25 (2015). Vanommeslaeghe, K. & MacKerell, A. D. Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing. J. Chem. Inf. Model. 52 , 3144–3154 (2012). Huang, J. & MacKerell, A. D. CHARMM36 all-atom additive protein force field: Validation based on comparison to NMR data. J. Comput. Chem. 34 , 2135–2145 (2013). Price, D. J. & Brooks, C. L. A modified TIP3P water potential for simulation with Ewald summation. J. Chem. Phys. 121 , 10096–10103 (2004). Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems. J. Chem. Phys. 98 , 10089–10092 (1993). Berendsen, H. J. C., Postma, J. P. M., Van Gunsteren, W. F., DiNola, A. & Haak, J. R. Molecular dynamics with coupling to an external bath. J. Chem. Phys. 81 , 3684–3690 (1984). Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 52 , 7182–7190 (1981). Xue, C., Lin, T. Y., Chang, D. & Guo, Z. Thioflavin T as an amyloid dye: fibril quantification, optimal concentration and effect on aggregation. R Soc. open. sci. 4 , 160696 (2017). Nayak, N. & Mishra, M. High fat diet induced abnormalities in metabolism, growth, behavior, and circadian clock in Drosophila melanogaster. Life Sci. 281 , 119758 (2021). Dash, K., Panda, D. K., Yadav, K., Meher, S. & Mishra M. 2D material graphene as a potential antidiabetic and nontoxic compound in Drosophila melanogaster. Appl. Nanosci. 14 , 423–439 (2024). Springer, U. S. Fundamental Approaches to Screen Abnormalities in Drosophila. (New York, NY, (2020). 10.1007/978-1-4939-9756-5 Dash, K. & Mishra, M. Combined supplementation of leucine and glutamine acts as a novel therapeutic approach to alleviate hyperglycemia and oxidative stress by targeting insulin signalling genes in a drosophila model of type 2 diabetes. Mol. Biol. Rep. 53 , 8 (2026). Lipinski, C. A., Lombardo, F., Dominy, B. W. & Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 3–25. 1. Advanced Drug Delivery Reviews 46, 3–26 (2001). (1997). Ali, J., Camilleri, P., Brown, M. B., Hutt, A. J. & Kirton, S. B. Revisiting the General Solubility Equation: In Silico Prediction of Aqueous Solubility Incorporating the Effect of Topographical Polar Surface Area. J. Chem. Inf. Model. 52 , 420–428 (2012). Rook, G. A. W., Steele, J., Umar, S. & Dockrell, H. M. A simple method for the solubilisation of reduced NBT, and its use as a colorimetric assay for activation of human macrophages by γ-interferon. J. Immunol. Methods . 82 , 161–167 (1985). Kapuscinski, J. DAPI: a DNA-Specific Fluorescent Probe. Biotech. Histochem. 70 , 220–233 (1995). Tanious, F. A., Veal, J. M., Buczak, H., Ratmeyer, L. S. & Wilson, W. D. DAPI (4’,6-diamidino-2-phenylindole) binds differently to DNA and RNA: minor-groove binding at AT sites and intercalation at AU sites. Biochemistry 31 , 3103–3112 (1992). Wang, H. & Joseph, J. A. Quantifying cellular oxidative stress by dichlorofluorescein assay using microplate reader11Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee by the United States Department of Agriculture and does not imply its approval to the exclusion of other products that may be suitable. Free Radic. Biol. Med. 27 , 612–616 (1999). Behera, D. P., Hota, P. R., Dash, K., Mishra, M. & Sahoo, H. Regulation of protein disaggregation by the hydrophobic chain length of ammonium-based ionic liquids. Phys. Chem. Chem. Phys. 27 , 16820–16830 (2025). Sarkar, A. et al. Role of cerium oxide nanoparticles in improving oxidative stress and developmental delays in Drosophila melanogaster as an in-vivo model for bisphenol a toxicity. Chemosphere 284 , 131363 (2021). Casas-Tintó, S. Drosophila as a Model for Human Disease: Insights into Rare and Ultra-Rare Diseases. Insects 15 , 870 (2024). Mukherjee, S. et al. Strontium ferrite as a nontoxic nanomaterial to improve metabolism in a diabetic model of Drosophila melanogaster. Mater. Chem. Phys. 281 , 125906 (2022). Palanker Musselman, L. et al. A high-sugar diet produces obesity and insulin resistance in wild-type Drosophila . Dis. Models Mech. 4 , 842–849 (2011). Abdullahi, S. U., Aliyu, M., Antidiabetic Research & Protocols, E. A Review of Drosophila melanogaster Models, Molecular Mechanisms, and FNAS-JABS 2, 53–60 (2025). Omoboyowa, D. A., Agoi, M. D., Shodehinde, S. A., Saibu, O. A. & Saliu, J. A. Antidiabetes study of Spondias mombin (Linn) stem bark fractions in high-sucrose diet-induced diabetes in Drosophila melanogaster. J. Taibah Univ. Med. Sci. 18 , 663–675 (2023). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers agreed at journal 18 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor invited by journal 07 Apr, 2026 Editor assigned by journal 27 Mar, 2026 Submission checks completed at journal 27 Mar, 2026 First submitted to journal 24 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9208858","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":624749577,"identity":"1d14b664-4298-4542-a03b-083798dd56d7","order_by":0,"name":"Smita Manjari Panda","email":"","orcid":"","institution":"Indian Institute of Technology (Indian School of Mines) Dhanbad","correspondingAuthor":false,"prefix":"","firstName":"Smita","middleName":"Manjari","lastName":"Panda","suffix":""},{"id":624749578,"identity":"2deb143b-1724-4f48-8955-8ded190d6c8b","order_by":1,"name":"Kalpanarani Dash","email":"","orcid":"","institution":"National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Kalpanarani","middleName":"","lastName":"Dash","suffix":""},{"id":624749579,"identity":"ec19a41c-1368-4077-ae52-f5ed53b59616","order_by":2,"name":"Devi Prashanna Behera","email":"","orcid":"","institution":"National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Devi","middleName":"Prashanna","lastName":"Behera","suffix":""},{"id":624749580,"identity":"8c9a0e8b-83cf-4853-ad35-1602aa88cd19","order_by":3,"name":"Monalisa Mishra","email":"","orcid":"","institution":"National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Monalisa","middleName":"","lastName":"Mishra","suffix":""},{"id":624749581,"identity":"fc2a2b5b-94af-4736-abec-0af8d647b2fe","order_by":4,"name":"Harekrushna Sahoo","email":"","orcid":"","institution":"National Institute of Technology Rourkela","correspondingAuthor":false,"prefix":"","firstName":"Harekrushna","middleName":"","lastName":"Sahoo","suffix":""},{"id":624749582,"identity":"97b84d06-b25e-48c9-acaf-3326d1727537","order_by":5,"name":"Umakanta Tripathy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYJCCA0CcwMDe2HCAwQAqlIBPPRtYi0ECA8/BhgMHiNXCANYikQCxjyAwuN/78HBBzZ88g5uPGw9/KKiLZmA//IDh4Q48Wo6xGxyeccyg2OB2Ishhh3MbeNIMGBLP4NPCxnCYh80gcQNEy4HcBoYcBobENkJa/gG13AR7vy63gf8NEVp424BabjCCtDDnNkgQsEXyWBrD4Zl9xokzzwAddgbolzaJZwYH8GnhO3yM+XPBN7nEvuPHH3+o+FOX28+f/PDhTzxaQIAZRCgcgPJAEXUAl1IULfINhJSNglEwCkbBiAUA82Ree6l+o2EAAAAASUVORK5CYII=","orcid":"","institution":"Indian Institute of Technology (Indian School of Mines) Dhanbad","correspondingAuthor":true,"prefix":"","firstName":"Umakanta","middleName":"","lastName":"Tripathy","suffix":""}],"badges":[],"createdAt":"2026-03-24 08:23:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9208858/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9208858/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107173181,"identity":"247f5527-7000-40af-9cb8-56b3a18e75e6","added_by":"auto","created_at":"2026-04-17 15:11:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":206973,"visible":true,"origin":"","legend":"\u003cp\u003eBest binding poses of top ligands (a) Withaferin A (WFA), (b) Withanolide A (WLA) with hIAPP and their 2D interaction diagrams.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/fbbcfb672d405ae274634c17.png"},{"id":107173214,"identity":"49b2304d-5164-40dd-b7a4-0cf0ff1e9d9a","added_by":"auto","created_at":"2026-04-17 15:12:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":319387,"visible":true,"origin":"","legend":"\u003cp\u003eStructural parameters of hIAPP in the absence and presence of Withaferin A (WFA) and Withanolide A (WLA): (a) Root mean square deviation (RMSD) of backbone of hIAPP, (b) Per-residue Root mean square fluctuation (RMSF) of c-alpha atoms of hIAPP, (c) Helix percentage, (d) Radius of gyration (Rg) of amyloidogenic region (20-29 AA), (e) Solvent accessible surface area (SASA) of amyloidogenic region (20-29 AA), (f) No. of hydrogen bonds between hIAPP and WFA and WLA.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/e76aefa03b970fa1845a75c0.png"},{"id":107173208,"identity":"0f1bd668-1ffa-4027-9194-cae717745910","added_by":"auto","created_at":"2026-04-17 15:12:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":124958,"visible":true,"origin":"","legend":"\u003cp\u003eTime-dependent ThT fluorescence profiles for hIAPP (15 μM) aggregation in the absence (control) and presence of both the ligands: Withaferin A (WFA) and Withanolide A (WLA) at a molar ratio of peptide/ligand (1:1), (b) Comparative bar plot of ThT fluorescence intensity recorded for fibril for ThT alone, ThT + WFA, ThT + WLA, ThT + hIAPP, and ThT + hIAPP co-incubated with WFA as well as WLA.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/b72c3d84521a5dc5015a9336.png"},{"id":107173190,"identity":"8a2f2170-c6f7-4de8-8a80-33ff019b7585","added_by":"auto","created_at":"2026-04-17 15:11:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":541519,"visible":true,"origin":"","legend":"\u003cp\u003eMorphology of hIAPP fibrils in the absence and presence of Withaferin A (WFA) and Withanolide A (WLA).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/53fa8d0d26325d67d4173b59.png"},{"id":107173211,"identity":"3a981280-5078-4093-add1-e9ca3e9bd552","added_by":"auto","created_at":"2026-04-17 15:12:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":20557,"visible":true,"origin":"","legend":"\u003cp\u003eQuantitative estimation of ROS levels in the hemolymph of third-instar \u003cem\u003eDrosophila melanogaster\u003c/em\u003elarvae for various experimental groups: Control, and treated with Withaferin A (WFA), Withanolide A (WLA), hIAPP, hIAPP + WFA, and hIAPP + WLA.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/3ddfc0727a5fce5928da88ad.png"},{"id":107173212,"identity":"693d46a1-e924-4961-ad48-baa04e2207fa","added_by":"auto","created_at":"2026-04-17 15:12:05","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1063201,"visible":true,"origin":"","legend":"\u003cp\u003eDAPI-DCFH-DA staining of 3\u003csup\u003erd\u003c/sup\u003e instar larval gut to detect nuclear damage induced by ROS accumulation: (a-a’’) control, (b-b’’) Withaferin A (WFA), (c-c’’) Withanolide A (WLA), (d-d’’) hIAPP, (e-e’’) hIAPP + WFA, (f-f’’) hIAPP + WLA treatment group, (g) Mean fluorescence intensity of DCFH-DA for all groups.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/fa00a4d6975193deae9d6de6.png"},{"id":107173180,"identity":"1871d2dc-f984-4179-ad20-cc7a397ee36e","added_by":"auto","created_at":"2026-04-17 15:11:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":547307,"visible":true,"origin":"","legend":"\u003cp\u003eAcridine Orange (AO) staining to detect apoptotic cell death after hIAPP feeding for 1.5 hrs and the cytoprotective effect of Withaferin A (WFA) and Withanolide A (WLA): (a) control (b) WFA positive control, (c) WLA positive control, (d) hIAPP treatment group, (e) hIAPP + WFA treatment group, (f) hIAPP + WLA treatment group.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/795a550f7052712079c7f897.png"},{"id":107173213,"identity":"c31d79cc-fcc2-446c-a520-5ea219034198","added_by":"auto","created_at":"2026-04-17 15:12:05","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":671062,"visible":true,"origin":"","legend":"\u003cp\u003eDAPI-PI staining to detect necrotic cell death in larvae gut: (a-a’’) control, (b-b’’) Withaferin A (WFA), (c-c’’) Withanolide A (WLA), (d-d’’) hIAPP treatment group, (e-e’’) hIAPP + WFA treatment group, (f-f’’) hIAPP + WLA treatment group.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/3aa426465be8b9c68f0e9bdd.png"},{"id":107173193,"identity":"8ab5cda6-00c0-4094-9155-d156622ba9a8","added_by":"auto","created_at":"2026-04-17 15:11:58","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":190939,"visible":true,"origin":"","legend":"\u003cp\u003eBiochemical estimation of free glucose level to check the anti-diabetic efficacy of Withaferin A (WFA) and Withanolide A (WLA) in HSD-induced diabetic flies and non-treated standard food medium (PC).\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/1b8c212f8fcc7651c050c9cf.png"},{"id":107483357,"identity":"aa7f1664-f6a9-4e68-aec0-d0145d9165be","added_by":"auto","created_at":"2026-04-22 02:27:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4141012,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9208858/v1/e3db11a5-6aa3-4303-8e26-e764b0cffe61.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Withanolide A Inhibits hIAPP aggregation: An In silico, Biophysical, and Drosophila-Based In Vivo Validation","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSeveral chronic and neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and type 2 diabetes mellitus (T2DM), are linked to amyloidogenesis, which collectively contribute to rising global morbidity and mortality[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. About 36 different human proteins misfold and turn into morphologically similar β-sheet-rich aggregates, also referred to as amyloid fibrils, that are linked to more than 50 diseases [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. A complicated nucleation-polymerization process that involves several structural intermediates and changes from unstructured monomers to oligomers, protofilaments, and finally mature fibrils underlies amyloid aggregation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and the most significant approach for treating amyloid-associated disorders is to prevent misfolded peptides from aggregating. Human Islet Amyloid Polypeptide (hIAPP), also known as Amylin, a 37-residue neuroendocrine hormone peptide, is secreted from the pancreatic β-cell alongside insulin and ranks among the most amyloidogenic proteins [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Numerous scientific studies have demonstrated that aggregation of hIAPP leads to amyloid deposition in the pancreatic tissue of ~\u0026thinsp;90% T2DM patients, making it a key pathological hallmark of T2DM [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A correlation was observed between hIAPP deposition and β-cell death in pancreatic islets of Langerhans. These findings suggest that the cytotoxic properties of hIAPP directly contribute to the cellular dysfunction in T2DM [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Besides, the β-cell dysfunction of T2DM patients is associated with various pathogenic mechanisms, including membrane disruption, mitochondrial impairment, ER stress with UPR (unfolded protein response) activation, inflammatory cascades, hIAPP-induced reactive oxygen species (ROS)-mediated, and programmed cell death [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given this, hIAPP is an appealing molecular target for drug development and combating the progression of T2DM [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA significant amount of work has been invested in identifying various types of amyloid inhibitors that prevent misfolded amyloid peptides from clumping together, including small natural molecules [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These molecules target either the monomeric or intermediate state of the amyloid precursor, aiming to inhibit amyloid production at an early stage [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. For instance, naturally occurring organic compounds, such as polyphenols, have been shown to prevent hIAPP aggregation [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Similarly, it has been demonstrated that morin hydrate breaks the IAPP fibrils [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Substantial evidence suggests that resveratrol is the most potent anti-aggregative polyphenol, owing to its significantly higher binding affinity for the hIAPP pentamer [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A well-known natural molecule, the polyphenol epigallocatechin gallate [EGCG], binds to various amyloid peptides such as α-synuclein, amyloid beta, and κ-casein to disrupt their misfolding and aggregation pathways [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Similarly, curcumin, derived from turmeric, can inhibit the production of Aβ and α-synuclein fibrils in a dose-dependent manner [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These findings underscore the relevance and therapeutic potential of naturally occurring molecules.\u003c/p\u003e \u003cp\u003eIn light of this, the foundation of our study builds upon our previous computational work, where we identified two phytoconstituents of Withania Somnifera (Withaferin A and Withacoagulin) as inhibitors of hIAPP after screening our lab-made library of 1000 natural compounds [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, MD simulation analysis showed that Withaferin A exhibits stable binding to hIAPP, whereas Withacoagulin induces greater flexibility (higher RMSF) in hIAPP and an aggregation-prone structural change. Therefore, we prioritize Withaferin A, and expanded the virtual screening to 2,000 natural compounds to identify additional effective inhibitors. Following this, we have also adopted an experimental approach to confirm the inhibitory potential of the selected compounds. Every experiment was conducted with and without the inhibitors. The well-known Thioflavin T (ThT) fluorescence assay was used to track the kinetics of amyloid aggregation. Additionally, the morphological characteristics of hIAPP aggregates were characterized using confocal microscopy and transmission electron microscopy (TEM). \u003cem\u003eDrosophila melanogaster\u003c/em\u003e has evolved into a fundamental model organism for investigating cell death associated with protein aggregation, due to the remarkable conservation of its genome and the parallels between Drosophila and human biology. Their genetic traceability and short lifespan make them ideal for investigating the processes behind protein aggregation and its effects on cellular and tissue levels [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, to assess biological relevance, we have used \u003cem\u003eDrosophila melanogaster\u003c/em\u003e as an \u003cem\u003ein vivo\u003c/em\u003e model. We also tested the anti-diabetic effects of lead compounds on the free glucose levels of diabetic Drosophila. The study will yield a potential drug candidate for the treatment of T2DM.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Virtual screening and lead optimization\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. hIAPP and ligands preparation\u003c/h2\u003e \u003cp\u003eThe crystal structure of the hIAPP was retrieved from the RCSB Protein Data Bank (PDB ID: 2KB8) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/structure/2KB8\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/structure/2KB8\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Autodock tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ccsb.scripps.edu/mgltools/1-5-7/\u003c/span\u003e\u003cspan address=\"https://ccsb.scripps.edu/mgltools/1-5-7/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to compute partial charges using Gasteiger\u0026rsquo;s method, and polar hydrogen atoms were added and then converted to .pdbqt format. We have created a homemade database of 2000 phytoconstituents of natural products, and the structures of the molecules were obtained from the PubChem (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database, LOTUS (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://lotus.naturalproducts.net/\u003c/span\u003e\u003cspan address=\"https://lotus.naturalproducts.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and IMPATT2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cb.imsc.res.in/imppat/\u003c/span\u003e\u003cspan address=\"https://cb.imsc.res.in/imppat/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Using the Open Babel toolbox [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], these ligand molecules were then optimized and converted to the .pdbqt format.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. Molecular docking\u003c/h2\u003e \u003cp\u003eThe best binding poses and interactions between ligand molecules and target receptors can be predicted using molecular docking. The popular and reliable program Autodock Vina is used in this work to investigate the binding interaction of ligand molecules with the hIAPP [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The lowest energy conformation was determined using a quasi-Newtonian optimization technique and a hybrid scoring function. In the docking study, a grid box was generated with a grid box center at (-8.734, -2.184, -2.885) with a grid spacing of 14 \u0026Aring;, 88 \u0026Aring;, and 16 \u0026Aring; in the X, Y, and Z dimensions, respectively. The exhaustiveness of the search was set to 10. For each docking simulation, nine docking conformations are generated, and the conformation with the lowest docking energy is selected as the preferred docking conformation. The maximum energy difference between the best and worst binding modes was set to 3 kcal/mol. The docking results are analyzed using Pymol 2.5.4 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pymol.org/2/\u003c/span\u003e\u003cspan address=\"https://pymol.org/2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), ligplot+, and Discovery Studio (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://discover.3ds.com/\u003c/span\u003e\u003cspan address=\"https://discover.3ds.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3. \u003cem\u003eIn-Silico\u003c/em\u003e ADMET analysis\u003c/h2\u003e \u003cp\u003eEvaluation of pharmacokinetic properties is essential in the early stages of drug development and screening. Several essential processes, including absorption, distribution, metabolism, excretion, and Toxicity (ADMET), are involved in pharmacokinetics. The SwissADME tool was used to calculate the physiological and pharmacokinetic properties from the SMILES structures of the compounds (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Furthermore, to predict toxicity, we utilized a novel, freely accessible web server, pkCSM (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://biosig.lab.uq.edu.au/pkcsm/\u003c/span\u003e\u003cspan address=\"https://biosig.lab.uq.edu.au/pkcsm/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In the early stages of drug discovery, \u003cem\u003ein silico\u003c/em\u003e ADMET analysis significantly reduces the risk of failure in clinical trials. The virtual screening, including the ADMET evaluation protocol used here, is established and reported in our previous literature [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Classical molecular dynamics for hIAPP-ligand interaction\u003c/h2\u003e \u003cp\u003eThe time-dependent dynamics of hIAPP (in free and bound form) were carried out using classical molecular dynamics (MD) simulation using Gromacs 2022.2 with the CHARMM 36 force field [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The CGENFF server was used to generate parameters of Withaferin A and Withanolide A [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Every protein-ligand combination was solvated in the TIP3P model [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. For neutralization, the proper quantity of counterions (Na\u003csup\u003e+\u003c/sup\u003e and Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e) was added. To prevent any steric clashes, the resulting systems were energy-minimized in several steps, using a combination of steepest descent and conjugate gradient methods. Equilibration of the NVT and NPT ensembles was carried out for 20 ns for each system at 300 K. The particle mesh Ewald and force-switching methods were implemented for electrostatic and van der Waals interactions[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The velocity-rescaling scheme from the Berendsen thermostat and the isotropic-rescaling scheme from the Parrinello-Rahman barostat maintained the temperature and pressure during the simulation [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. A final production run of 800 ns was performed for all the systems with a time step of 2 fs, and the frames from the trajectory were extracted at 20 ps intervals. The resulting MD trajectories were analyzed using the built-in tools of GROMACS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Experimental\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Materials\u003c/h2\u003e \u003cp\u003ehIAPP (with purity\u0026thinsp;\u0026ge;\u0026thinsp;95%): purchased from Anaspec, USA (AS-60804). Withaferin A (\u0026ge;\u0026thinsp;98%) (CFN91895) and Withanolide A (\u0026ge;\u0026thinsp;98%) (CFN91964): purchased from ChemFaces, China. Dimethyl sulfoxide (DMSO, \u0026ge; 99.9%): purchased from HiMedia, India (MB058); thioflavin T (ThT, \u0026ge; 98%): purchased from Sigma Aldrich Merck, Germany (2390-54-7). Sucrose: purchased from HiMedia, India (GRM601), Cornmeal: purchased from local store, Yeast: purchased from local store, Type I Agar: purchased from HiMedia, India (GRM666), Methyl paraben: purchased from HiMedia, India (GRM1899), Propionic acid: purchased from HiMedia, India (GRM3658), Paraformaldehyde: purchased from Sigma Aldrich Merck, Germany (STBK4638) purity 95%, Anhydrous glucose; purchased from HiMedia, India (MB037), Glucose oxidase reagent; purchased from Sigma-Aldrich, Merck Germany (G7793), O-dianisidine; purchased from Sigma Aldrich Merck, Germany (D2679), Acridine orange: purchased from HiMedia, India (GRM3087), Glycerol: purchased from HiMedia, India (MB060), Propidium Iodide: purchased from HiMedia, India (TC252), DAPI: purchased from HiMedia, India (MB097), DCFH-DA: purchased from Sigma-Aldrich Merck, Germany (35845), Nitro blue tetrazolium (NBT): purchased from HiMedia, India (RM578), Glacial acetic acid: purchased from HiMedia, India (AS001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. hIAPP and ligands solution preparation\u003c/h2\u003e \u003cp\u003eThe hIAPP stock was prepared by dissolving 1 mg of the original packaged peptide into 500 \u0026micro;l of DMSO. Alliquots were made of 15 \u0026micro;l and stored at -80\u0026deg;C. The stock aliquots were dissolved in 20 mM phosphate buffer (PBS, pH 7.4) before the experiments. For ligands\u0026rsquo; solution, primary stock of Withaferin A (11 mM) and Withanolide A (8 mM) were prepared by dissolving 0.4 \u0026micro;g and 0.5 \u0026micro;g, respectively, in DMSO. These primary stocks were aliquoted and stored at -20\u0026deg;C until use. Secondary stocks (100 \u0026micro;M) were freshly made in 20 mM PBS (pH 7.4) prior to each experiment, and final working concentrations were adjusted to achieve a 1:1 molar ratio with hIAPP.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Thioflavin T (ThT) aggregation assay\u003c/h2\u003e \u003cp\u003eTo monitor the aggregation of hIAPP and evaluate the inhibitory effects of selected lead molecules (Withaferin A and Withanolide A), we performed Thioflavin T (ThT) fluorescence assay[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. ThT produces enhanced fluorescence after binding specifically with amyloid fibrils, enabling real-time tracking of fibrillation kinetics. 5 mg ThT Powder was first dissolved in 1 ml of PBS (pH 7.4). The stock solution was kept in the dark, and prior to the experiment, a working solution of 10 \u0026micro;M was prepared by appropriate dilution. The FluoroMax-4P spectrofluorimeter (Horiba Jobin Yvon, USA) with a 1 cm quartz cuvette was used to record the fluorescence intensity. The readings were continuously recorded for the mixture containing 15 \u0026micro;M hIAPP (with or without inhibitor) and 10 \u0026micro;M ThT in PBS at excitation/emission wavelengths of 440/480 nm at regular intervals until the aggregation curve reached a plateau, indicating saturation of fibril production.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4. Transmission electron microscopy (TEM)\u003c/h2\u003e \u003cp\u003eThe hIAPP was incubated with or without inhibitors in 20 mM phosphate buffer (pH 7.4) at room temperature for 2 hours, and the samples were imaged by TEM to assess ligand-mediated inhibition of fibril formation. For TEM grid preparation, 5 \u0026micro;L of each sample was carefully deposited onto 200-mesh carbon-coated copper grids and incubated at room temperature for 10 minutes to ensure adequate adsorption. Excess liquid was washed out gently with DI water. High-resolution TEM images of these samples were then taken using a FEI, Tecnai G2 TF30-ST instrument operated at 300 kV, enabling detailed visualization of hIAPP aggregate morphology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.3.5. Confocal microscopy\u003c/h2\u003e \u003cp\u003eMorphological differences in hIAPP aggregates, with or without inhibitors (1:1 molar ratio), were assessed using confocal fluorescence microscopy (Leica STELLARIS 5). hIAPP samples were prepared by ageing 15 \u0026micro;M hIAPP with 10 \u0026micro;M ThT in 20 mM PBS and kept at room temperature for 2 hours. Then the solution was drop-casted onto a glass slide covered with a coverslip and left to dry before imaging. Excitation was set to 440 nm, the ThT maximum, to ensure optimal contrast and enable high-resolution imaging of aggregate morphology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e2.3.6. \u003cem\u003eIn vivo\u003c/em\u003e assay in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.1. Fly maintenance and standard doses of drugs\u003c/h2\u003e \u003cp\u003eThe experiments used the Oregon R strain of Drosophila melanogaster, obtained from the C-CAMP Fly Facility in Bangalore, India. The flies were reared on a standard diet consisting of 0.15 M sucrose, cornmeal, yeast, and Type I agar, supplemented with methyl paraben and propionic acid to prevent microbial and fungal contamination. Flies were housed in vials at a ratio of five females to three males and maintained under controlled environmental conditions of 60% relative humidity, a constant temperature of 25\u0026deg;C, and a 12-hour light/dark cycle. The flies were transferred to freshly prepared food in a male-to-female ratio of 3:5. After seven days, third-instar larvae were collected from the control food medium for subsequent experiments. After the larvae were collected from the control food medium, they were correctly washed in 1X PBS and treated with the drug for 1.5 hours.\u003c/p\u003e \u003cp\u003eGroup1-(10\u0026ndash;15) control larvae were treated with 1X PBS\u003c/p\u003e \u003cp\u003eGroup 2-(10\u0026ndash;15) control larvae were treated with 15 \u0026micro;M hIAPP\u003c/p\u003e \u003cp\u003eGroup 3-(10\u0026ndash;15) control larvae were treated with 15 \u0026micro;M hIAPP\u0026thinsp;+\u0026thinsp;15 \u0026micro;M Withaferin A\u003c/p\u003e \u003cp\u003eGroup 4-(10\u0026ndash;15) control larvae were treated with 15 \u0026micro;M hIAPP\u0026thinsp;+\u0026thinsp;15 \u0026micro;M Withanolide A\u003c/p\u003e \u003cp\u003eGroup 5-(10\u0026ndash;15) control larvae were treated with 15 \u0026micro;M Withaferin A in 1X PBS\u003c/p\u003e \u003cp\u003eGroup 6-(10\u0026ndash;15) control larvae were treated with 15 \u0026micro;M Withanolide A in 1X PBS\u003c/p\u003e \u003cp\u003eAfter 1.5 hours, larvae were collected from all groups and washed thoroughly with 1X PBS; all subsequent experiments were then performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.2. NBT assay to detect ROS\u003c/h2\u003e \u003cp\u003eThe nitro blue tetrazolium (NBT) assay assessed intracellular ROS levels in third-instar larvae. A total of 15 larvae per group were used for the assay. The larvae were first rinsed in 1X phosphate-buffered saline (PBS) and transferred to a 0.5 mL microcentrifuge tube with a bottom incision for hemolymph collection. This tube was placed inside a 1.5 mL collection tube. Each larva was punctured in the thoracic region to extract hemolymph using a pre-sterilized needle while on ice to prevent melanization. The tubes were centrifuged at 8000 rpm for 5 minutes at 4\u0026deg;C to separate the hemolymph. A 5 \u0026micro;L aliquot of the isolated hemolymph was transferred to a fresh tube and diluted with 10 \u0026micro;L of 1X PBS. An equal volume (15 \u0026micro;L) of 1.6 mM NBT solution was added, and the mixture was incubated in the dark for 30 minutes. Following incubation, the reaction was terminated by adding 30 \u0026micro;L of 100% glacial acetic acid for 5 minutes, followed by 150 \u0026micro;L of 50% glacial acetic acid. The optical density (OD) was measured at 595 nm, and the absorbance values were used to quantify ROS levels, with higher absorbance indicating increased ROS concentrations [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.3. DAPI-DCFH-DA staining to detect nuclear fragmentation\u003c/h2\u003e \u003cp\u003eThird-instar larval gut tissues were subjected to staining with 4',6-diamidino-2-phenylindole (DAPI) and 2',7\u0026rsquo;-dichlorodihydrofluorescein diacetate (DCFDA). DAPI binds to the major groove of DNA at A: T-rich regions, enabling the detection of nuclear damage. Meanwhile, DCFDA interacts with intracellular ROS, emitting green fluorescence proportional to ROS levels [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Larvae were dissected in cold 1X phosphate-buffered saline (PBS) under a stereomicroscope (Motic 3Plus, India) to isolate the gut tissues. The samples were then fixed in 4% paraformaldehyde (PFA) at 4\u0026deg;C overnight. Following fixation, PFA was removed, and the tissues were washed three times with 1X PBS. Subsequently, the samples were rinsed twice with 1X PBST (PBS containing Tween-20) for 10 minutes. The gut tissues were then placed on a clean, grease-free slide and simultaneously stained with DCFDA and DAPI for 30 minutes and 5 minutes in the dark. To remove excess dye, samples were washed once with PBS and mounted using 20% glycerol before being covered with a coverslip. Fluorescent imaging was performed using a confocal microscope (Leica DMI8).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.4. DAPI-PI staining to detect necrosis\u003c/h2\u003e \u003cp\u003eTo quantify the extent of necrotic cell death induced by hIAPP protein, DAPI-PI (Propidium Iodide) staining was performed [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. We administered hIAPP protein (15 \u0026micro;L) diluted in 1X PBS to third-instar Drosophila larvae for 1.5 hours. Throughout the incubation phase, the larvae only consumed the protein solution. We excised the gut from third-instar larvae after incubation and preserved them in 4% paraformaldehyde (PFA) for 30 minutes. Following fixation, the samples were rinsed in 1X PBS twice for 10 minutes each. The samples were treated with 20 \u0026micro;L of PI (1 \u0026micro;g/mL) for 5 minutes, followed by 20 \u0026micro;L of DAPI (1 \u0026micro;g/mL) for 5 minutes. After incubation, the samples were washed with 1X PBS and mounted using 20% glycerol. Gut images showing the region of necrotic spots were acquired using a confocal microscope (Leica DMI8).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.5. Acridine orange (AO) staining to detect apoptosis\u003c/h2\u003e \u003cp\u003eTo quantify the extent of cell death induced by hIAPP protein, we administered hIAPP protein (15 \u0026micro;l) diluted in 1X PBS to third instar Drosophila larvae for 1.5 hours. Throughout the incubation phase, the larvae only consumed the protein solution. We excised the gut from third-instar larvae after incubation and preserved them in 4% paraformaldehyde (PFA) for 30 minutes. Following fixation, the samples were rinsed in 1X PBS twice for 10 minutes each. The samples were subsequently treated with 1% PBST for 10 minutes, followed by a 10-minute interval. The samples were treated with 20 \u0026micro;l of Acridine orange (1 \u0026micro;g/ml) for 15 minutes in the dark. After incubation, the samples were washed with 1X PBS and mounted using 20% glycerol. Gut images showing a region of cell death were acquired using a confocal microscope (Leica DMI8) at emission wavelengths of 520 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.6. Free glucose assay\u003c/h2\u003e \u003cp\u003eControl flies were cultivated on a conventional diet containing 0.15 M sucrose, cornmeal, yeast, and type I agar, supplemented with methyl paraben and propionic acid to inhibit microbial and fungal contamination. Diabetic flies were cultivated on a High Sucrose diet of 1.5 M sucrose, while maintaining all other ingredients constant. Drugs Withaferin A and Withanolide A were administered to the control food medium at a concentration of 15 \u0026micro;M. Flies subjected to a high sugar diet for 15 days were classified as diabetic flies. Diabetic flies were subsequently transferred to a diet containing Withaferin A and Withanolide A for an additional 7 days. Diabetic flies fed a standard diet for 7 days served as the positive control group. Following a 7-day treatment, the hemolymph glucose levels of 21-day-old adult flies were measured to evaluate the anti-diabetic efficacy of Withaferin A and Withanolide A.\u003c/p\u003e \u003cp\u003eFlies from all experimental mediums (n\u0026thinsp;=\u0026thinsp;10) were homogenized with 100 \u0026micro;L of chilled 1X PBS and stored in a mini cooler at -20\u0026deg;C. Glucose standards were prepared from a 1 mg/mL D-glucose stock and stored at -20\u0026deg;C. Thirty microliters of supernatants, glucose standards, and PBS blank solution were added to distinct wells of a 96-well plate, with each concentration represented in triplicate. The enzymatic reaction that converts D-glucose to gluconic acid commenced upon the addition of 100 \u0026micro;L of glucose oxidase/peroxidase reagent to each well. The plate was subsequently incubated at 37\u0026deg;C for one hour. Subsequently, 100 \u0026micro;L of 12N H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e was introduced to halt the reaction, resulting in a pinkish to purple coloration. The final absorbance was measured with a microplate reader at 540 nm [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section4\"\u003e \u003ch2\u003e2.3.6.7. Statistics\u003c/h2\u003e \u003cp\u003eData were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard deviation (SD). Statistical analyses were conducted using GraphPad Prism (GraphPad, San Diego, CA, USA). Single-parameter-based comparisons were made using one-way ANOVA. The Probability (P) values *P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 were considered to be significant, and P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 is non-significant (ns).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Virtual screening combined with ADMET filtering identifies potential candidates\u003c/h2\u003e \u003cp\u003eOur goal was to identify drug-like small molecules that could prevent hIAPP from forming amyloid, building on previous work targeting hIAPP. To this, we employed two-stage computational approaches: (1) molecular docking of our in-house natural compound library using cagnizifinol as a control inhibitor and (2) \u003cem\u003ein-silico\u003c/em\u003e ADMET profiling of top-ranked compounds to shortlist the most promising candidates. Canagliflozin, a well-known FDA-approved anti-diabetic drug [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], had a docking score of -6.4 kcal/mol, which was the screening cut-off. We identified 13 molecules (listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) with binding values above the cut-off and selected them for further study. As Lipinski\u0026rsquo;s rule of five [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] [molecular mass less than 500 Dalton, high lipophilicity (Log P\u0026thinsp;\u0026lt;\u0026thinsp;5), hydrogen bond donors\u0026thinsp;\u0026le;\u0026thinsp;5, and hydrogen bond acceptors\u0026thinsp;\u0026le;\u0026thinsp;10] served as the primary filter for the drug-likeness, the compounds that satisfy this were considered for further evaluation. Furthermore, after excluding molecules that lacked essential drug-likeness characteristics based on Lipinski\u0026rsquo;s rule and other drug-likeness criteria, we assessed pharmacokinetics, which is crucial for four essential processes: absorption, distribution, metabolism, and excretion. It is noteworthy that Withanolide A (WLA) and Withanolide D (WLD), along with Withaferin A (WFA), meet this requirement, as seen in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Water solubility is another critical factor in ADMET analysis, as it is necessary for drug distribution and absorption. Swiss ADME estimates solubility using the Log S scale by combining several topological approaches (ESOL, Ali, and Silicos IT) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. These selected compounds are moderately soluble to soluble. In addition, due to their high gastrointestinal (GI) absorption, these three compounds (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) are suitable for regulatory approval and can be taken orally. An essential step in the drug discovery process is toxicity prediction, which ensures that possible compounds don't exhibit any adverse side effects. Using pkCSM, an \u003cem\u003ein silico\u003c/em\u003e toxicity evaluation was conducted to assess potential toxicological issues associated with the compounds. The AMES test (AT), oral rat acute toxicity (LD50), hepatotoxicity (HT), and skin sensitization are all covered by the pkCSM. A popular technique for determining a compound\u0026rsquo;s ability to cause bacterial mutations is the AT. If the test comes out positive, the substance is mutagenic and could potentially lead to cancer. It is clear from Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e that none of the selected 3 compounds are mutagenic. The liver-related side effects observed in human patients taking 531 medications serve as the basis for the HT predictor. If any compound causes one or more physiological or clinical liver events that are closely linked to the disruption of liver function, it is considered hepatotoxic. Interestingly, the shortlisted compounds are also non-hepatotoxic.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinding affinity (BA) of the top 13 molecules.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSl. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompounds [Database ID]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBA\u003c/p\u003e \u003cp\u003e(kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2-[(2E,4E,6E,8E,10E,12E,14E)-15-(4,4,7a-trimethyl-2,5,6,7-tetrahydro-1-benzofuran-2-yl)-6,11-dimethylhexadeca-2,4,6,8,10,12,14-heptaen-2-yl]-4,4,7a-trimethyl-2,5,6,7-tetrahydro-1-benzofuran [IMPHY002618]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCryptoflavin [IMPHY005981]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZeaxanthin [IMPHY011785]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWithanolide A [IMPHY000090]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-6.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWithaferin A [265237] (Previous work)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-6.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ealpha-Carotene [IMPHY011609]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithasomidienone [IMPHY000630]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13-Amino-4-hydroxy-9,6a,8a-trimethyl(1,3,4,5,6,7,8,14,14a,14b,6a,6b,8a-trideca hydrobenzo[1''',2'''-3'',4'']benzo[1'',2''-4',3']benzo[1',2'-5,1]cyclopenta[3, 2-d]thiopheno[2,3-b]pyridin-12-yl) phenyl [IMPHY012701]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2S,6S,7aR)-2-[(2Z,4E,6E,8E,10E,12E,14E,16E)-17-[(1R,4S)-4-hydroxy-2,6,6-trimethylcyclohex-2-en-1-yl]-6,11,15-trimethylheptadeca-2,4,6,8,10,12,14,16-octaen-2-yl]-4,4,7a-trimethyl-2,5,6,7-tetrahydro-1- [IMPHY004149]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePamoic acid [IMPHY007087]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egamma-Carotene [IMPHY004383]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePelankine [IMPHY000350]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWithanolide D [IMPHY003936]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-6.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanagliflozin [24812758]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eIn-silico ADMET parameters of selected molecules predicted by SWISS ADME and pkCSM.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCompounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003ePhysiological parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eWater solubility\u003c/p\u003e \u003cp\u003eLog S\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c16\" namest=\"c12\"\u003e \u003cp\u003ePharmacokinetic properties of selected molecules\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNRB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNHA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNHD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTPSA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLog P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eESOL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAli\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSILICOS-IT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eGI Abs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eHT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eLD50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithanolide A (WLA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e470.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e96.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-4.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e2.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithaferin A (WFA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e470.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e96.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-3.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e2.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithanolide D (WLD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e470.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e96.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-4.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e2.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMW: molecular weight, NRB: No. of rotatable bonds, NHA: No. of H-bond acceptors, NHD: No. of H-bond donors, TPSA: Topological polar surface area, DL: Drug likeness (Lipinski\u0026rsquo;s Rule), GI Abs: Gastrointestinal absorption, AT: AMES Toxicity, HT: Hepatotoxicity, LD50: Oral Rat Acute Toxicity, SS: Skin sensitization.\u003c/p\u003e \u003cp\u003eWater solubility: solubility: highly soluble (\u0026gt;\u0026thinsp;0), very soluble (\u0026lt;\u0026thinsp;0), soluble (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2), moderately soluble (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;4), poorly soluble (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;6), and insoluble (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;10).\u003c/p\u003e \u003cp\u003eBefore experimental validation, this study employed \u003cem\u003ein silico\u003c/em\u003e strategies to identify compounds with minimal predicted toxicity, ensuring the safety and drug-likeness of the shortlisted candidates. Based on the binding affinity values obtained from molecular docking, Withaferin A (WFA) and Withanolide A (WLA) were identified as the most promising candidates among the three shortlisted compounds. Both showed promising drug-like qualities and the best binding affinity (-6.8 kcal/mol) for hIAPP. The binding poses and 2D interaction profiles of WFA and WLA with hIAPP are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. We then performed classical molecular dynamics (MD) simulation to better examine the binding behaviour and structural stability of these molecules. The dynamic interactions, conformational changes, and temporal stability were all thoroughly investigated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Interaction dynamics of the hIAPP monomer with selected top ligands\u003c/h2\u003e \u003cp\u003eAlthough virtual screening provides an initial assessment of the binding potential of lead compounds, it fails to account for the dynamic characteristics of protein-ligand interactions. This binding is governed by dynamic conformational changes and can be influenced by structural fluctuations of hIAPP. We therefore performed an MD simulation of 800 ns for both the Apo and holo forms of hIAPP to provide deeper insights into the interaction mechanism and validate the stability and inhibitory potential of the lead molecules with hIAPP under near-physiological conditions. First, to ensure equilibrium and system stability during the simulations, we have calculated the root-mean-square deviation (RMSD) over 800 ns. The time evolution of the RMSD plot illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e suggests that all the systems (only hIAPP, hIAPP\u0026thinsp;+\u0026thinsp;Withaferin A, and hIAPP\u0026thinsp;+\u0026thinsp;Withanolide A) converge and attain stability. The average RMSD of only hIAPP, hIAPP\u0026thinsp;+\u0026thinsp;Withaferin A, and hIAPP\u0026thinsp;+\u0026thinsp;Withanolide A are 1.133\u0026thinsp;\u0026plusmn;\u0026thinsp;0.159 nm, 0.577\u0026thinsp;\u0026plusmn;\u0026thinsp;0.153 nm, and 0.400\u0026thinsp;\u0026plusmn;\u0026thinsp;0.100 nm, respectively. From the average RMSD values and the RMSD plot, it is evident that the ligand-bound forms exhibit lower RMSD values than the apo form. In fact, Withanolide A-bound hIAPP has the least RMSD, indicating the most stable structure. Further, to check the flexibility of hIAPP upon binding with the ligands, residue-wise root mean square fluctuation (RMSF) was calculated and plotted for apo hIAPP and its complexes with Withaferin A and Withanolide A [Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(b)\u003c/b\u003e]. The average RMSF value for apo hIAPP was 0.399\u0026thinsp;\u0026plusmn;\u0026thinsp;0.152 nm, while in the presence of Withaferin A and Withanolide A, the values are 0.594\u0026thinsp;\u0026plusmn;\u0026thinsp;0.227 nm and 0.430\u0026thinsp;\u0026plusmn;\u0026thinsp;0.158 nm, respectively. The average RMSF values and the RMSF plot indicate that Withanolide A-bound hIAPP shows reduced fluctuation as compared to Withaferin A-bound form, suggesting less flexibility of hIAPP. Interestingly, in the case of Withanolide A, reduced fluctuation of the aggregation-prone region [20\u0026ndash;29 amino acids (AA)] [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], indicating a lowering of the flexibility and aggregation propensity. During the simulation, this can also be linked to the helix content of the hIAPP. The helix content of 20\u0026ndash;29 AA is higher than that of the apo and Withaferin A-bound form, as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(c)\u003c/b\u003e, which could be the cause of the decrease in fluctuation around this region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo gain a better understanding of the structural stability of the aggregation-prone region 20\u0026ndash;29 AA of hIAPP both before and during Withaferin A and Withanolide A binding, we next examined the compactness parameter of the structure by computing the radius of gyration (Rg) and solvent accessible surface area (SASA) of the aggregation-prone region 20\u0026ndash;29 AA. The Rg plot in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(d)\u003c/b\u003e shows that the structural dynamics of hIAPP in the 20\u0026ndash;29 AA region remain stable throughout the simulation. The average Rg values for apo, Withaferin A, and Withanolide A-bound forms are 0.558\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 nm, 0.568\u0026thinsp;\u0026plusmn;\u0026thinsp;0.015 nm, and 0.566\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011 nm, respectively. Additionally, stable structural dynamics are indicated by no significant change in the Rg values of hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e upon complexation with Withaferin A and Withanolide A, suggesting the structural integrity of all three systems of hIAPP20-29 remained unaltered. We achieved a stable Rg equilibrium during the simulation period and did not detect any notable structural shift in hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e when Withaferin A and Withanolide A were present. Moreover, to examine the effect of Withaferin A and Withanolide A binding on the aggregation-prone region and its solvent exposure, we have calculated SASA for hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e throughout the simulation trajectory. There was a slight change to hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e\u0026rsquo;s SASA observed after the binding of Withaferin A and Withanolide A. The SASA values for hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e, hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e + Withaferin A complex, and hIAPP\u003csub\u003e20\u0026minus;29\u003c/sub\u003e + Withanolide A complex were estimated to be 12.183\u0026thinsp;\u0026plusmn;\u0026thinsp;0.369, 11.720\u0026thinsp;\u0026plusmn;\u0026thinsp;0.394, and 11.722\u0026thinsp;\u0026plusmn;\u0026thinsp;0.383 nm\u003csup\u003e2\u003c/sup\u003e, respectively. The SASA for the 800 ns simulation trajectory plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(e)\u003c/b\u003e and average SASA values suggest that the ligand-bound forms exhibit less solvent accessibility than the apo form. Overall, the SASA of ligand-bound systems appears to attain a stable equilibrium without any major peaks during the simulation, indicating the stability of hIAPP's compactness in the presence of Withaferin A and Withanolide A.\u003c/p\u003e \u003cp\u003eFurthermore, to understand whether Withaferin A and Withanolide A bind to hIAPP in the same manner, as depicted by the docking study, the intermolecular H-bonds formed in the hIAPP\u0026thinsp;+\u0026thinsp;Withaferin A and hIAPP\u0026thinsp;+\u0026thinsp;Withanolide A complexes were calculated for the simulation trajectory. The H bonds formed between Withaferin A and Withanolide A, with hIAPP paired within 0.35 nm, were calculated and plotted as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(f)\u003c/b\u003e. The analysis indicates that Withaferin A and Withanolide A form up to 8 and 7 H-bonds, respectively, during the simulation, suggesting strong and stable interactions with hIAPP. Overall, the RMSD, RMSF, Rg, SASA, and hydrogen bond analysis indicate that Withanolide A and Withaferin A form stable structures and interact strongly with hIAPP. Interestingly, Withanolide A causes a slight structural change in the hIAPP aggregation-prone area, making the protein less flexible and less prone to aggregation, indicating that it is the most potent hIAPP inhibitor. These computational findings provide a strong rationale for pursuing further experimental validation to substantiate the inhibitory activity and evaluate its therapeutic relevance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Ligand-mediated suppression of hIAPP amyloid formation\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003ein vitro\u003c/em\u003e complex kinetics of hIAPP, like those of other amyloidogenic polypeptides, exhibit a lag phase in which small aggregates form, followed by an exponential phase, also referred to as the elongation phase, and an equilibrium phase (plateau phase) in which amyloid fibrils are formed. The ThT, one of the most widely used dyes for determining the kinetics of amyloid fibril formation and for screening potential therapeutics to prevent fibril formation, tracked the rate of amyloid formation by hIAPP. As anticipated, ThT fluorescence profiles showed that hIAPP at a concentration of 15 \u0026micro;M displayed distinctive sigmoidal aggregation kinetics, characterized by three distinct phases: an initial lag phase (~\u0026thinsp;0.51 min), a rapid elongation phase (~\u0026thinsp;51 min to 85 min), and a final plateau phase (after 85 min). The three phases can be easily distinguished by the variation in ThT intensity, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e. Further, to evaluate the inhibitory potential of the top-ranked ligands (Withaferin A and Withanolide A) found through virtual screening, we carried out kinetic experiments using hIAPP-to-ligand molar ratios (1:1) at a constant peptide concentration (15 \u0026micro;M). Interestingly, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e shows that effective inhibition of fibril formation was demonstrated by the addition of ligands, which caused a noticeable delay in fibril nucleation (lag phase: ~3.22 hr in the case of Withaferin A and 4.8\u0026thinsp;+\u0026thinsp;hours in Withanolide A), delayed the aggregation kinetics throughout the development phase, and eventually resulted in lower final ThT fluorescence. In fact, the fibril intensity illustrated in the bar plot [Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(b)\u003c/b\u003e], the Withaferin A and Withanolide A suppressed fibrill formation by 49.74% and 97.60%. Additionally, pure Withaferin A and Withanolide A did not produce any ThT signal during a 5-hour incubation, confirming that these ligands do not influence ThT fluorescence. The shift in kinetics suggests that both ligands prevent or reduce hIAPP aggregation by interfering with the nucleation and elongation stages of fibril formation, highlighting the ligands' potential as inhibitors of amyloid formation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Disruption of hIAPP fibril morphology by WFA \u0026amp; WLA\u003c/h2\u003e \u003cp\u003eTo complement the kinetic experiments and provide more profound morphological insights, we conducted a thorough analysis of hIAPP aggregation using a combination of confocal microscopy and TEM. Confocal microscopy images provide high-resolution, real-time visualisation of hIAPP aggregates, making them ideal for assessing fluorescence intensity and overall fibril distribution. From Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e(a-c)\u003c/b\u003e, at the fibril time point, a strong ThT fluorescence signal was observed in only hIAPP, indicating widespread fibril formation. In contrast, hIAPP co-incubated with ligands exhibited markedly reduced fluorescence intensity and aggregate distribution, especially showing the least fluorescence signal in the presence of Withanolide A. Similarly, TEM images [Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e(d-f)\u003c/b\u003e] illustrate the density of amyloid aggregates. They clearly indicate that amyloid formation is reduced in the presence of ligands. Hence, both the ligands disrupt the morphology of hIAPP. Additionally, from both confocal and TEM images, Withanolide A exhibits the most potent inhibitory effect, with minimal fibril formation, which is also in accordance with the ThT assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e3.4. NBT assay reveals antioxidative effects of Withaferin A and Withanolide A against hIAPP-induced toxicity\u003c/h2\u003e \u003cp\u003eThe NBT reduction test was used to determine intracellular ROS levels in the hemolymph of third-instar Drosophila larvae. This assay has been used as an indicator of superoxide anion (O₂⁻) generation in cells, as the yellow-coloured NBT dye is converted to the blue-coloured formazan upon binding superoxide radicals. NBT, as an electrophilic dicationic molecule, readily accepts electrons from intracellular electron donors. Superoxide anions in anhydrous solution convert NBT to monoformazan, which is detected quantitatively at 595 nm [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. A bar plot of the absorbance values for all experimental groups: control, Withaferin A (WFA), Withanolide A (WLA), and hIAPP-treated (in the presence and absence of WFA and WLA) is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The control group exhibited a mean absorbance of 0.325\u0026thinsp;\u0026plusmn;\u0026thinsp;0.022, whereas hIAPP-treated larvae had a considerably higher absorbance of 0.626\u0026thinsp;\u0026plusmn;\u0026thinsp;0.025 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with the same sample volume, indicating enhanced superoxide production. However, the absorbance values for the hIAPP\u0026thinsp;+\u0026thinsp;WFA and hIAPP\u0026thinsp;+\u0026thinsp;WLA groups were 0.466\u0026thinsp;\u0026plusmn;\u0026thinsp;0.015 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 0.421\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively, indicating a considerable reduction of hIAPP-induced ROS.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdditionally, we evaluated the antioxidant potential of only WFA and WLA (at the same working concentration and for the same duration in PBS medium) in non-treated third-instar larvae grown in standard food medium, and considered them as positive controls. Here, the positive control groups, WFA and WLA-treated larvae, showed no significant increase in the absorbance values, which are 0.380\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and 0.300\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 (p\u0026thinsp;=\u0026thinsp;ns), respectively, as compared to the non-treated larvae, indicating that these chemicals did not generate oxidative stress under normal physiological conditions. Thus, the NBT assay quantitatively estimates oxidative stress in hIAPP-treated Drosophila larvae, giving biochemical proof of the destructive effects of hIAPP aggregation in the gut. The hIAPP-treated larvae had significantly higher ROS levels than the control group. The findings indicate that both WFA and WLA possess potent antioxidative properties that counteract hIAPP-induced ROS elevation in Drosophila larvae, with WLA exhibiting slightly greater efficacy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e3.5. WFA \u0026amp; WLA reduced nuclear fragmentation and ROS production detected by DAPI-DCFH-DA staining\u003c/h2\u003e \u003cp\u003eTo evaluate DNA damage or nuclear fragmentation due to intracellular ROS accumulation in Drosophila larvae, DAPI and DCFH-DA staining were performed on dissected larval gut tissues for control, Withaferin A, Withanolide A, and hIAPP-treated (in the presence and absence of Withaferin A and Withanolide A). DAPI is a fluorescent-based DNA-binding dye that selectively binds with adenine-thymine (A\u0026ndash;T)-rich regions within the minor groove of double-stranded DNA [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Upon binding, DAPI exhibits enhanced fluorescence intensity, producing a distinct blue emission when excited at 358 nm with an emission maximum around 461 nm [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. This property enables sensitive visualization of nuclear structure and chromatin condensation, hallmarks of apoptosis or nuclear damage. When DNA is damaged or fragmented, the nuclear morphology and fluorescence pattern change, allowing qualitative visualization of nuclear integrity. Uniform arrangement of nucleus, round or oval nuclei shape with homogenous DAPI staining indicates a healthy nucleus and no DNA damage. Irregularity in nucleus shape and non-uniform or fragmented nucleus arrangement indicate DNA damage associated with early or late apoptosis. In contrast, DCFH-DA is a non-fluorescent probe that is cell-permeable, allowing it to assess intracellular ROS. Once internalized, DCFH-DA is cleaved by cytosolic esterases into non-fluorescent DCFH, which remains trapped within cells. ROS subsequently oxidize DCFH to form the highly fluorescent compound 2\u0026prime;,7\u0026prime;-dichlorofluorescein (DCF), exhibiting green fluorescence upon excitation at 488 nm with emission near 525 nm [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The fluorescence intensity of DCF directly correlates with the level of intracellular ROS, providing a sensitive readout of oxidative stress [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Representative confocal images corresponding to different treatment groups are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(a-aʺ)\u003c/b\u003e, the control larval gut exhibited intact nuclear morphology with low DCFH-DA fluorescence, indicating preserved nuclear integrity and negligible oxidative stress. Similarly, treatment with Withaferin A [Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(b-bʺ)\u003c/b\u003e] and Withanolide A [Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(c-cʺ)\u003c/b\u003e] alone did not result in noticeable nuclear fragmentation or ROS accumulation, suggesting that these compounds are non-toxic under the same experimental conditions. In contrast, as evident from Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(d)\u003c/b\u003e, DAPI staining revealed pronounced nuclear fragmentation and chromatin condensation throughout the gut epithelium of hIAPP-treated larvae, indicating elevated nuclear damage and apoptosis. Furthermore, DCFH-DA staining demonstrated markedly higher green fluorescence intensity in the hIAPP-treated larval gut [Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(d\u0026rsquo;)\u003c/b\u003e], signifying excessive ROS accumulation. Conversely, larvae co-treated with hIAPP\u0026thinsp;+\u0026thinsp;Withaferin A and hIAPP\u0026thinsp;+\u0026thinsp;Withanolide A groups exhibited more intact and uniformly stained nuclei and displayed substantially reduced nuclear damage [Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(e, f)\u003c/b\u003e] and reduced green fluorescence [Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(e\u0026rsquo;, f\u0026rsquo;)\u003c/b\u003e]. The quantitative analysis of mean DCFH-DA fluorescence intensity is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(g)\u003c/b\u003e, which corroborates these observations, showing significantly elevated ROS levels in the hIAPP-treated group that were substantially reduced upon co-treatment with Withaferin A or Withanolide A. Collectively, the observations from merged gut images [Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e(a\u0026rsquo;\u0026rsquo;-f\u0026rsquo;\u0026rsquo;)\u003c/b\u003e] substantiate that hIAPP induces significant oxidative stress and nuclear damage in Drosophila gut tissues, while treatment with Withaferin A and Withanolide A effectively ameliorates these cytotoxic effects by reducing ROS accumulation and preserving nuclear integrity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e3.6. WFA \u0026amp; WLA reduced apoptotic cell death detected by AO staining\u003c/h2\u003e \u003cp\u003eTo check the pro-apoptotic effect of hIAPP feeding in the 3rd instar Drosophila larval gut, Acridine Orange (AO) staining was performed. AO is a nucleic acid-selective fluorescent dye that readily penetrates cell membranes and intercalates into DNA and RNA. In apoptotic cells, AO preferentially binds to condensed chromatin, exploiting its differential staining of nucleic acids, appearing as bright green dots or crescent shapes within a green nucleus (due to DNA binding) in early stages, resulting in nuclei that appear bright green with highly condensed or fragmented morphology under fluorescence microscopy. Regions of cell death are thus visualized as distinct circular foci exhibiting intense green fluorescence [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e illustrates confocal images of AO-stained larval gut tissues. As observed in Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cb\u003e(a, b, c)\u003c/b\u003e, the control, Withaferin A-treated, and Withanolide A-treated, respectively, exhibited AO fluorescence with a uniform staining pattern, indicative of intact cellular and lysosomal integrity. Notably, larvae treated with hIAPP exhibited a marked increase in fluorescent apoptotic foci across various gut regions, indicating increased cell death and nuclear fragmentation, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cb\u003e(d)\u003c/b\u003e. In contrast, co-treatment of hIAPP with Withaferin A [Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e \u003cb\u003e(e)\u003c/b\u003e] and Withanolide A [Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e \u003cb\u003e(f)\u003c/b\u003e] led to a pronounced reduction in AO-positive apoptotic nuclei, suggesting adequate protection against hIAPP-induced cytotoxicity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e3.7. WFA \u0026amp; WLA reduced necrotic cell death detected by DAPI-PI staining\u003c/h2\u003e \u003cp\u003eTo assess whether hIAPP aggregation induces oxidative damage, leading to loss of membrane integrity and necrotic cell death, particularly in metabolically active tissues such as the larval gut, DAPI-PI dual staining was performed. DAPI labels the nuclei of both viable and non-viable cells. Whereas propidium iodide (PI) is membrane-impermeable and selectively enters cells with compromised plasma membranes, binding to DNA and emitting red fluorescence. PI is a cationic, fluorescent, intercalating dye with a strong affinity for nucleic acids; however, its membrane-impermeability allows it to selectively stain cells with compromised plasma membranes. Upon entry, PI binds to DNA and RNA, emitting bright red fluorescence upon excitation at approximately 535 nm, with an emission maximum near 617 nm, making it a reliable marker for detecting necrotic or late apoptotic cells with lost membrane integrity [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Thus, DAPI-PI dual staining provides a powerful means to distinguish between normal, apoptotic, and necrotic cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe gut tissues co-stained with DAPI-PI confocal images are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The DAPI-stained [Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e \u003cb\u003e(a-f)\u003c/b\u003e] gut tissue images, nuclear damages induced by hIAPP, and the protective effect of co-incubation with Withaferin A and Withanolide A are explained in detail in Section \u003cspan refid=\"Sec28\" class=\"InternalRef\"\u003e3.5\u003c/span\u003e. Further, as evident from the PI-stained gut images, the control larval gut and gut tissues treated with Withaferin A or Withanolide A exhibited no PI uptake \u003cb\u003e[\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e(a\u0026rsquo;-c\u0026rsquo;)]\u003c/b\u003e. Whereas, the larvae fed with hIAPP exhibited intense red fluorescence, indicative of necrotic cell death [Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e(d\u0026rsquo;)\u003c/b\u003e]. Here, the necrotic regions appeared as bright red puncta localised around fragmented or condensed nuclei, confirming extensive membrane damage and cell death. Conversely, larvae co-treated with hIAPP\u0026thinsp;+\u0026thinsp;Withaferin A, and hIAPP\u0026thinsp;+\u0026thinsp;Withanolide A displayed an absence of red fluorescence, suggesting preservation of membrane integrity and a lack of necrotic damage [Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e(e\u0026rsquo;, f\u0026rsquo;)\u003c/b\u003e]. Overall, the merged DAPI-PI images [Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e \u003cb\u003e(a\u0026rsquo;\u0026rsquo;-f\u0026rsquo;\u0026rsquo;)\u003c/b\u003e] corroborate the cytoprotective role of Withaferin A and Withanolide A against hIAPP-induced membrane disruption, highlighting their potential in mitigating necrotic cell death in Drosophila gut tissues.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e3.8. WFA \u0026amp; WLA have a glucose-lowering effect in diabetic flies\u003c/h2\u003e \u003cp\u003eThe hemolymph free glucose level of adult \u003cem\u003eDrosophila melanogaster\u003c/em\u003e was quantified using the Glucose Oxidase-Peroxidase (GOD-POD) colourimetric enzymatic assay. This method is based on the oxidation of D-glucose to gluconic acid and hydrogen peroxide (H₂O₂) catalysed by the enzyme glucose oxidase [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The generated H₂O₂ subsequently reacts with the chromogenic substrate \u003cem\u003eo\u003c/em\u003e-dianisidine in the presence of peroxidase to yield a pink-coloured product, the intensity of which is directly proportional to the glucose concentration. The absorbance of the reaction product was measured spectrophotometrically at 540 nm [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Previously, this method has been used to confirm type 2 diabetes in Drosophila fed with a high-sugar diet and a high-fat diet [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. According to previous reports, several phytocompounds exhibiting pronounced anti diabetic potential were tested in the Drosophila diabetic model induced by a high-sucrose diet [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHence, this experimental approach will also help us determine the anti-diabetic efficacy of Withaferin A and Withanolide A. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e displays a bar plot of the mean hemolymph-free glucose concentration. The mean hemolymph-free glucose concentration in 15-day-old adult control flies was 0.621\u0026thinsp;\u0026plusmn;\u0026thinsp;0.029 mg/mL. Flies treated with a high-sucrose diet (HSD) exhibited a significant elevation in free glucose levels, reaching 0.962\u0026thinsp;\u0026plusmn;\u0026thinsp;0.060 mg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming a diabetic-like metabolic phenotype. Next, to check the anti-diabetic potential of Withaferin A and Withanolide A, HSD-fed flies were treated with Withaferin A and Withanolide A for another 7 days on a standard diet. Treatment with Withaferin A significantly reduced glucose levels to 0.605\u0026thinsp;\u0026plusmn;\u0026thinsp;0.059 mg/mL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), while Withanolide A produced a more pronounced decrease to 0.564\u0026thinsp;\u0026plusmn;\u0026thinsp;0.123 mg/mL (p\u0026thinsp;=\u0026thinsp;0.0001). In contrast, flies transferred from the HSD group to non-treated standard food medium did not exhibit a statistically significant reduction in glucose concentration (0.916\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0341 mg/mL, p\u0026thinsp;=\u0026thinsp;ns). These results indicate that Withaferin A and Withanolide A effectively ameliorate HSD-induced hyperglycemia in Drosophila adults, with Withanolide A exhibiting superior glucose-lowering efficacy. This suggests that Withanolide A may be a better choice to improve metabolic homeostasis by enhancing insulin sensitivity or modulating oxidative stress and amyloid burden.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe development and progression of over 50 protein diseases, including Alzheimer's disease, Parkinson's disease, prion disease, and Type 2 diabetes, are intimately linked to the assembly of amyloidogenic proteins and peptides into toxic oligomeric and fibrillar aggregates. The prevention and inhibition of pathogenic protein aggregation by potential molecules is currently the focus of significant research efforts aimed at developing therapeutic options against these diseases. In this study, from \u003cem\u003ein-silico\u003c/em\u003e screening and MD Simulation, we found Withaferin A and Withanolide A derived from Ashwagandha have better binding affinity and stable interaction with hIAPP. Withanolide A induced structural change in the aggregation-prone region (20\u0026ndash;29 AA). The ThT Assay clearly indicates that both molecules (ideally, Withanolide A) significantly slowed the aggregation kinetics, suggesting that they suppress the development of hIAPP fibrils. The morphological images from confocal and TEM suggest that Withanolide A has reduced the formation of hIAPP fibrils. Additionally, the \u003cem\u003ein vivo\u003c/em\u003e study is noteworthy for its observation that both Withaferin A and Withanolide A mitigate hIAPP-induced toxicity in the Drosophila gut, reducing ROS generation, preserving nuclear integrity, and preventing necrotic cell death. Further, we also evaluated the antidiabetic activity of these molecules in diabetic flies. Although both molecules demonstrated glucose-lowering effects, it is worth noting that Withanolide A outperformed Withaferin A. To sum up, our integrated \u003cem\u003ein silico\u003c/em\u003e, \u003cem\u003ein vitro\u003c/em\u003e, and \u003cem\u003ein vivo\u003c/em\u003e studies demonstrate that Withanolide A is a potent natural inhibitor of hIAPP toxicity and aggregation. It also shows glucose-lowering effects in Drosophila models with diabetes. To the best of our knowledge, this is the first report showing that Withanolide A is an inhibitor of hIAPP. Building on our \u003cem\u003ein-silico\u003c/em\u003e, in-vitro, and in-vivo findings presented here, future research should extend to mammalian models to confirm the anti-diabetic potential of Withanolide A and explore its suitability for preclinical development.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eWe acknowledge the Science and Engineering Research Board (SERB), DST, New Delhi, India (EMR/2017/003759) for funding. KD is thankful to UGC, New Delhi, India, for the financial support (Application number 211610018329) she has received for her PhD work.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSMP: Conceptualization, methodology, data curation, data analysis, investigation, visualization, writing\u0026ndash; original draft, writing\u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eKD: Investigation, data curation, visualization, data curation, writing\u0026ndash; original draft, writing\u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eDPB: Investigation, visualization, data curation, formal analysis.\u003c/p\u003e\n\u003cp\u003eMM: Supervision, resources, validation, writing\u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eHS: Supervision, resources, validation, writing\u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eUT: Conceptualization, supervision, validation, resources, funding acquisition, project administration, writing\u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eSMP and UT thank the IIT (ISM), Dhanbad, for providing the required HPC facility and financial support. We also acknowledge the Science and Engineering Research Board (SERB), DST, New Delhi, India (EMR/2017/003759) for funding. KD is thankful to UGC for the financial support (Application number 211610018329) she has received for her PhD work. The authors gratefully acknowledge the National Institute of Technology (NIT) Rourkela for the instrumentation facilities, Prof. Usharani Subuddhi, NIT Rourkela, for PL measurements, and Prof. Suman Jha, NIT Rourkela, for the fruitful discussion.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData will be available upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJucker, M. \u0026amp; Walker, L. C. Propagation and spread of pathogenic protein assemblies in neurodegenerative diseases. \u003cem\u003eNat. Neurosci.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e, 1341\u0026ndash;1349 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnowles, T. P. 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Sci.\u003c/em\u003e \u003cb\u003e18\u003c/b\u003e, 663\u0026ndash;675 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Human islet amyloid polypeptide, Diabetes, Molecular docking, MD simulation, Withanolide A, Drosophila","lastPublishedDoi":"10.21203/rs.3.rs-9208858/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9208858/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe aberrant aggregation of human islet amyloid polypeptide (hIAPP) or Amylin into toxic oligomers and fibrils leads to pancreatic β-cell dysfunction and progressive cell death, which is a key pathological feature of Type II diabetes mellitus (T2DM). In this study, we adopted a hybrid approach combining virtual screening and molecular dynamics (MD) simulation, with experimental validation, to identify inhibitors of hIAPP aggregation. Herein, we screened 2000 phytoconstituents from natural products using molecular docking, followed by \u003cem\u003ein silico\u003c/em\u003e ADMET predictions. Withaferin A and Withanolide A (phytoconstituents of Ashwagandha) were found to be lead molecules with suitable drug-like properties. Next, we performed an 800 ns MD simulation to assess the stability and interaction dynamics of hIAPP-ligand complexes. Building on the computational screening, we further carried out a comprehensive experimental analysis to validate the inhibitory effects of lead molecules. The collective experimental results from the Thioflavin T (ThT) assays, combined with Confocal and Transmission Electron Microscopy (TEM), suggest that the ligands (preferably Withanolide A) have a potent inhibitory effect against hIAPP aggregation by increasing the lag phase and inhibiting fibril formation of hIAPP. For \u003cem\u003ein vivo\u003c/em\u003e validation using Drosophila models, Withanolide A was found to mitigate hIAPP oligomer-induced toxicity by reducing apoptosis, necrosis, and oxidative stress in the Drosophila gut, as confirmed by multiple cell death staining assays and reactive oxygen species (ROS) analysis. Besides, in diabetic flies, Withanolide A lowered glucose levels, demonstrating anti-diabetic activity. Thus, this work, for the first time, suggests that Withanolide A may be a potential candidate for inhibiting hIAPP aggregation and as a T2DM drug.\u003c/p\u003e","manuscriptTitle":"Withanolide A Inhibits hIAPP aggregation: An In silico, Biophysical, and Drosophila-Based In Vivo Validation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 15:09:51","doi":"10.21203/rs.3.rs-9208858/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-18T11:26:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52437352331083635678836379074208485922","date":"2026-04-23T18:41:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T11:08:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68923868685034929172483967096147821150","date":"2026-04-22T18:10:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"242731581371587745830407053886447425597","date":"2026-04-22T09:00:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268506663714466213892690765843134739419","date":"2026-04-18T14:34:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T17:12:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-07T14:14:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-27T06:29:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T06:29:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-24T08:08:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0fbf4074-7f54-4250-96c0-208d4b675c9d","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T11:26:47+00:00","index":73,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66498484,"name":"Biological sciences/Biochemistry"},{"id":66498485,"name":"Biological sciences/Biophysics"},{"id":66498486,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":66498487,"name":"Biological sciences/Drug discovery"}],"tags":[],"updatedAt":"2026-04-17T15:09:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 15:09:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9208858","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9208858","identity":"rs-9208858","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}