Screening of potential drug for Alzheimer's disease: a computational study with GSK-3 β inhibition through virtual screening, docking, and molecular dynamics simulation

Discovery of effective GSK-3β inhibitors as therapeutic potential against Alzheimer's disease: A computational drug design insight

Alzheimer's disease (AD) is mostly thought to be caused by overactivity of glycogen synthase kinase 3-beta (GSK3-β). Therefore, a GSK-3β inhibitor may be a suggested medicine for Alzheimer's therapy. Nowadays, computational techniques are thought to be among the quickest and most affordable options for therapeutic design and drug discovery. Following a preliminary screening of flavonoids for possible protection against cognitive illnesses such as Alzheimer's, Amentoflavone, Curcumin, and Notopterol were shown to be promising candidates. Using molecular docking, the ligand orientation and binding energy in the ATP-binding pocket of GSK-3β were ascertained. Amentoflavone formed a hydrogen bond with the GSK-3β protein's ATP binding site during the molecular docking phase, obtaining the highest negative binding energy. However, when the results moved closer to a molecular dynamics simulation, the findings changed, and Curcumin was shown to be the most potent inhibitor. All structures remained stable during the MD simulation of the GSK-3β protein and its ligands. Moreover, compared to other natural compounds, Curcumin showed higher binding free energy. Therefore, Curcumin may be useful as a polyphenolic flavonoid in the prevention and treatment of AD. Hence, additional research in vitro and in vivo can focus on these flavonoid compounds as an alternative treatment.

Identification of novel brain penetrant GSK-3β inhibitors toward Alzheimer's disease therapy by virtual screening, molecular docking, dynamic simulation, and MMPBSA analysis

One of the significant therapeutic targets for Alzheimer's disease (AD) is Glycogen Synthase Kinase-3β (GSK-3β). Inhibition of GSK-3β can prevent hyperphosphorylation of tau, and thus prevent formation and accumulation of neurofibrillary tangles and neuropil threads that block intracellular transport, trigger unfolded protein response, and increase oxidative stress, cumulatively leading to neurodegeneration. In this study, we have performed structure-based virtual screening of two small-molecule libraries from ChemDiv CNS databases using AutoDock Vina to identify hit molecules based on their binding affinities compared to that of an established GSK-3β inhibitor, indirubin-3'-monoxime (IMO). Pharmacoinformatic screening on SwissADME and pkCSM servers enabled identification of lead molecules with favorable pharmacoinformatic properties for drug likeliness, including blood brain barrier (BBB) permeability. Further, molecular dynamic simulations identified six candidate lead molecules that show stable complex formation with GSK-3β in dynamic state under physiological conditions. Principal component analysis of the dynamic state was used to plot Free Energy Landscapes (FELs) of GSK-3β-ligand complexes. STRIDE secondary structure analysis of the lowest energy conformations identified from FEL plots, and binding free energy calculations by Molecular Mechanics Poisson-Boltzmann Surface Area ((ΔGbind)MM-PBSA) of the simulation trajectories led to the identification of two ligands as potential lead molecules having favorable free energy landscape profiles as well as significantly lower (ΔGbind)MM-PBSA in dynamic state compared to that of reference inhibitor IMO. Hence, this study identifies two novel brain penetrant GSK-3β inhibitors that are likely to have therapeutic potential against Alzheimer's disease.

Targeting glycogen synthase kinase-3β for Alzheimer's disease: Recent advances and future Prospects

Senile plaques induced by β-amyloid (Aβ) abnormal aggregation and neurofibrillary tangles (NFT) caused by tau hyperphosphorylation are important pathological manifestations of Alzheimer's disease (AD). Glycogen synthase kinase-3 (GSK-3) is a conserved kinase; one member GSK-3β is highly expressed in the AD brain and involved in the formation of NFT. Hence, pharmacologically inhibiting GSK-3β activity and expression is a good approach to treat AD. As summarized in this article, multiple GSK-3β inhibitors has been comprehensively summarized over recent five years. However, only lithium carbonate and Tideglusib have been studied in clinical trials of AD. Besides ATP-competitive and non-ATP-competitive inhibitors, peptide inhibitors, allosteric inhibitors and other types of inhibitors have gradually attracted more interest. Moreover, considering the close relationship between GSK-3β and other targets involved in cholinergic hypothesis, Aβ aggregation hypothesis, tau hyperphosphorylation hypothesis, oxidative stress hypothesis, neuro-inflammation hypothesis, etc., diverse multifunctional molecules and multi-target directed ligands (MTDLs) have also been disclosed. We hope that these recent advances and critical perspectives will facilitate the discovery of safe and effective GSK-3β inhibitors for AD treatment.

Monophasic coamorphous sulpiride: a leap in physicochemical attributes and dual inhibition of GlyT1 and P-glycoprotein, supported by experimental and computational insights

Study aimed to design and development of a supramolecular formulation of sulpiride (SUL) to enhance its solubility, dissolution and permeability by targeting a novel GlyT1 inhibition mechanism. SUL is commonly used to treat gastric and duodenal ulcers, migraine, anti-emetic, anti-depressive and anti-dyspeptic conditions. Additionally, Naringin (NARI) was incorporated as a co-former to enhance the drug's intestinal permeability by targeting P-glycoprotein (P-gp) efflux inhibition. NARI, a flavonoid has diverse biological activities, including anti-apoptotic, anti-oxidant, and anti-inflammatory properties. This study aims to design and develop a supramolecular formulation of SUL with NARI to enhance its solubility, dissolution, and permeability by targeting a novel GlyT1 inhibition mechanism, extensive experimental characterization was performed using solid-state experimental techniques in conjunction with a computational approach. This approach included quantum mechanics-based molecular dynamics (MD) simulation and density functional theory (DFT) studies to investigate intermolecular interactions, phase transformation and various electronic structure-based properties. The findings of the miscibility study, radial distribution function (RDF) analysis, quantitative simulations of hydrogen/π-π bond interactions and geometry optimization aided in comprehending the coamorphization aspects of SUL-NARI Supramolecular systems. Molecular docking and MD simulation were performed for detailed binding affinity assessment and target validation. The solubility, dissolution and ex-vivo permeability studies demonstrated significant improvements with 31.88-fold, 9.13-fold and 1.83-fold increments, respectively. Furthermore, biological assessments revealed superior neuroprotective effects in the SUL-NARI coamorphous system compared to pure SUL. In conclusion, this study highlights the advantages of a drug-nutraceutical supramolecular formulation for improving the solubility and permeability of SUL, targeting novel schizophrenia treatment approaches through combined computational and experimental analyses.Communicated by Ramaswamy H. Sarma.

Rational Design of Dual Inhibitors for Alzheimer's Disease: Insights from Computational Screening of BACE1 and GSK-3β

BACKGROUND

Alzheimer's disease (AD) is one of the most concerned neurodegenerative disorders across the world characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs), leading to cognitive decline and memory loss. Targeting key pathways involved in AD like Aβ and NFT pathways, are crucial for the development of effective therapeutic strategies. In this study, we aimed to identify and establish promising dual inhibitors targeting BACE1 and GSK-3β, two proteins implicated in Aβ and NFT formation respectively.

METHODS

We have used molecular docking, ADME property analysis, and MMGBSA calculations for the identification of hit molecules and further evaluation of binding affinity, drug-like properties, and stability against BACE1 and GSK-3β.

RESULTS

Our results demonstrated strong binding affinities of ZINC000034853956 towards the active sites of both proteins, with favorable interactions involving key residues crucial for inhibitory activity. Additionally, ZINC000034853956 exhibited favorable drug-like properties. MD simulations revealed the stable binding of ZINC000034853956 to both BACE1 and GSK-3β over a 50 ns period, with consistent ligand-protein interactions, such as hydrogen bonding and hydrophobic contacts. These findings highlight the potential of ZINC000034853956 as a promising candidate for AD treatment, acting as a dual inhibitor targeting both BACE1 and GSK-3β. Overall, our study provides valuable insights into the potential of ZINC000034853956 as a dual inhibitor for AD. The strong binding affinity, favorable drug-like properties, and stability observed in MD simulations support its suitability for further optimization and preclinical studies.

CONCLUSION

Further investigations are warranted to elucidate the precise molecular mechanisms and therapeutic benefits of ZINC000034853956. Our findings offer hope for the development of novel therapeutic interventions targeting crucial pathways involved in AD neurodegeneration.

Pharmacophore-Based Screening, Molecular Docking, and Dynamic Simulation of Fungal Metabolites as Inhibitors of Multi-Targets in Neurodegenerative Disorders

Neurodegenerative disorders, such as Alzheimer's disease (AD), negatively affect the economic and psychological system. For AD, there is still a lack of disease-altering treatments and promising cures due to its complex pathophysiology. In this study, we computationally screened the natural database of fungal metabolites against three known therapeutic target proteins of AD. Initially, a pharmacophore-based, drug-likeness category was employed for screening, and it filtered the 14 (A-N) best hits out of 17,544 fungal metabolites. The 14 best hits were docked individually against GSK-3β, the NMDA receptor, and BACE-1 to investigate the potential of finding a multitarget inhibitor. We found that compounds B, F, and L were immuno-toxic, whereas E, H, I, and J had a higher LD50 dose (5000 mg/kg). Among the examined metabolites, the Bisacremine-C (compound I) was found to be the most active molecule against GSK-3β (ΔG: -8.7 ± 0.2 Kcal/mol, Ki: 2.4 × 106 M-1), NMDA (ΔG: -9.5 ± 0.1 Kcal/mol, Ki: 9.2 × 106 M-1), and BACE-1 (ΔG: -9.1 ± 0.2 Kcal/mol, Ki: 4.7 × 106 M-1). It showed a 25-fold higher affinity with GSK-3β, 6.3-fold higher affinity with NMDA, and 9.04-fold higher affinity with BACE-1 than their native ligands, respectively. Molecular dynamic simulation parameters, such as RMSD, RMSF, Rg, and SASA, all confirmed that the overall structures of the targeted enzymes did not change significantly after binding with Bisacremine-C, and the ligand remained inside the binding cavity in a stable conformation for most of the simulation time. The most significant hydrophobic contacts for the GSK-3β-Bisacremine-C complex are with ILE62, VAL70, ALA83, and LEU188, whereas GLN185 is significant for H-bonds. In terms of hydrophobic contacts, TYR184 and PHE246 are the most important, while SER180 is vital for H-bonds in NMDA-Bisacremine-C. THR232 is the most crucial for H-bonds in BACE-1-Bisacremine-C and ILE110-produced hydrophobic contacts. This study laid a foundation for further experimental validation and clinical trials regarding the biopotency of Bisacremine-C.

Multitargeted Virtual Screening and Molecular Simulation of Natural Product-like Compounds against GSK3β, NMDA-Receptor, and BACE-1 for the Management of Alzheimer's Disease

The complexity of Alzheimer's disease (AD) and several side effects of currently available medication inclined us to search for a novel natural cure by targeting multiple key regulatory proteins. We initially virtually screened the natural product-like compounds against GSK3β, NMDA receptor, and BACE-1 and thereafter validated the best hit through molecular dynamics simulation (MDS). The results demonstrated that out of 2029 compounds, only 51 compounds exhibited better binding interactions than native ligands, with all three protein targets (NMDA, GSK3β, and BACE) considered multitarget inhibitors. Among them, F1094-0201 is the most potent inhibitor against multiple targets with binding energy -11.7, -10.6, and -12 kcal/mol, respectively. ADME-T analysis results showed that F1094-0201 was found to be suitable for CNS drug-likeness in addition to their other drug-likeness properties. The MDS results of RMSD, RMSF, Rg, SASA, SSE and residue interactions indicated the formation of a strong and stable association in the complex of ligands (F1094-0201) and proteins. These findings confirm the F1094-0201's ability to remain inside target proteins' binding pockets while forming a stable complex of protein-ligand. The free energies (MM/GBSA) of BACE-F1094-0201, GSK3β-F1094-0201, and NMDA-F1094-0201 complex formation were -73.78 ± 4.31 kcal mol^-1, -72.77 ± 3.43 kcal mol^-1, and -52.51 ± 2.85 kcal mol^-1, respectively. Amongst the target proteins, F1094-0201 have a more stable association with BACE, followed by NMDA and GSK3β. These attributes of F1094-0201 indicate it as a possible option for the management of pathophysiological pathways associated with AD.

Microorganism-Derived Molecules as Enzyme Inhibitors to Target Alzheimer's Diseases Pathways

Alzheimer's disease (AD) is the most common form of dementia. It increases the risk of other serious diseases and causes a huge impact on individuals, families, and socioeconomics. AD is a complex multifactorial disease, and current pharmacological therapies are largely based on the inhibition of enzymes involved in the pathogenesis of AD. Natural enzyme inhibitors are the potential sources for targeting AD treatment and are mainly collected from plants, marine organisms, or microorganisms. In particular, microbial sources have many advantages compared to other sources. While several reviews on AD have been reported, most of these previous reviews focused on presenting and discussing the general theory of AD or overviewing enzyme inhibitors from various sources, such as chemical synthesis, plants, and marine organisms, while only a few reviews regarding microbial sources of enzyme inhibitors against AD are available. Currently, multi-targeted drug investigation is a new trend for the potential treatment of AD. However, there is no review that has comprehensively discussed the various kinds of enzyme inhibitors from the microbial source. This review extensively addresses the above-mentioned aspect and simultaneously updates and provides a more comprehensive view of the enzyme targets involved in the pathogenesis of AD. The emerging trend of using in silico studies to discover drugs concerning AD inhibitors from microorganisms and perspectives for further experimental studies are also covered here.

Screening of Azadirachta indica phytoconstituents as GSK-3β inhibitor and its implication in neuroblastoma: molecular docking, molecular dynamics, MM-PBSA binding energy, and in-vitro study

Glycogen synthase kinase-3 (GSK-3), a constitutively active serine/threonine kinase, primary regulator of various cellular activities varying from glycogen metabolism to cell proliferation and regulation. GSK-3β is associated with the pathogenesis of numerous human diseases, including cancer, metabolic disorder, and Alzheimer's disease. In this study, Azadirachta indica compounds were selected and further screened on the BOILED-Egg model. The compounds showing good GIT absorption were docked with the crystal structure of GSK-3β. The compounds with high docking score were submitted for the molecular dynamic simulation (MDS) and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA). Based upon the MDS and MM-PBSA study, gedunin showed the highest binding energy throughout the MDS process. Gedunin was isolated from the Azadirachta indica, and its efficacy on GSK-3β inhibition was studied in the human neuroblastoma (SH-SY5Y) cells. Gedunin induced apoptosis and anti-proliferative activity by arresting G2/M phase, as evident by cell-cycle analysis. From immunoblot study, gedunin significantly enhanced the expression of an inhibitory form of GSK-3β (p-GSK-3β Ser9) in concentration-dependent manner. Our findings demonstrate that gedunin may act as an effective GSK-3β inhibitor suggesting that this compound may be used for the management of neuroblastoma. Further preclinical and clinical investigation is desirable.Communicated by Ramaswamy H. Sarma.

Inhibition of GSK_3β by Iridoid Glycosides of Snowberry (Symphoricarpos albus) Effective in the Treatment of Alzheimer's Disease Using Computational Drug Design Methods

The inhibition of glycogen synthase kinase-3β (GSK-3β) activity prevents tau hyperphosphorylation and binds it to the microtubule network. Therefore, a GSK-3β inhibitor may be a recommended drug for Alzheimer's treatment. In silico methods are currently considered as one of the fastest and most cost-effective available alternatives for drug/design discovery in the field of treatment. In this study, computational drug design was conducted to introduce compounds that play an effective role in inhibiting the GSK-3β enzyme by molecular docking and molecular dynamics simulation. The iridoid glycosides of the common snowberry (Symphoricarpos albus), including loganin, secologanin, and loganetin, are compounds that have an effect on improving memory and cognitive impairment and the results of which on Alzheimer's have been studied as well. In this study, in the molecular docking phase, loganin was considered a more potent inhibitor of this protein by establishing a hydrogen bond with the ATP-binding site of GSK-3β protein and the most negative binding energy to secologanin and loganetin. Moreover, by molecular dynamics simulation of these ligands and GSK-3β protein, all structures were found to be stable during the simulation. In addition, the protein structure represented no change and remained stable by binding ligands to GSK-3β protein. Furthermore, loganin and loganetin have higher binding free energy than secologanin; thus, these compounds could effectively bind to the active site of GSK-3β protein. Hence, loganin and loganetin as iridoid glycosides can be effective in Alzheimer's prevention and treatment, and thus, further in vitro and in vivo studies can focus on these iridoid glycosides as an alternative treatment.

Treasuring the computational approach in medicinal plant research

Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was time consuming and expensive. Computational methods such as Molecular Docking, Molecular Dynamic Simulation and Artificial intelligence are significant Insilico tools in medicinal plant research. Molecular docking approach exploits the mechanism of potential phytochemicals into the target active site to elucidate its interactions and biological therapeutic properties. MD simulation illuminates the dynamic behavior of biomolecules at atomic level with fine quality representation of biomolecules. Dramatical advancement in computer science is illustrating the biological mechanism via these tools in different diseases treatment. The advancement comprises speed, the system configuration, and other software upgradation to insights into the structural explanation and optimization of biomolecules. A probable shift from simulation to artificial intelligence has in fact accelerated the art of scientific study to a sky high. The most upgraded algorithm in artificial intelligence such as Artificial Neural Networks, Deep Neural Networks, Neuro-fuzzy Logic has provided a wide opportunity in easing the time required in classical experimental strategy. The notable progress in computer science technology has paved a pathway for understanding the pharmacological functions and creating a roadmap for drug design and development and other achievement in the field of medicinal plants research. This review focus on the development and overview in computational research moving from static molecular docking method to a range of dynamic simulation and an advanced artificial intelligence such as machine learning.