Computational drug discovery methods: docking, MD simulations, and free energy calculations widely used to discover Tau inhibitors.

Abstract

Alzheimer's disease (AD) remains the most prevalent neurodegenerative disorder worldwide, characterized by the accumulation of amyloid-? plaques and neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau protein. While amyloid-? targeting has dominated therapeutic strategies, emerging evidence demonstrates that tau pathology more directly drives neurodegeneration. This comprehensive review examines plumericin, a natural iridoid compound with potent anti-inflammatory and neuroprotective properties, as a potential inhibitor of tau protein aggregation and hyperphosphorylation. Through computational analysis including molecular docking, molecular dynamics simulations, and ADME profiling, we evaluate plumericin's binding affinity to tau tubulin kinase-1 (TTBK1), the serine/threonine kinase responsible for pathological tau phosphorylation. Our analysis reveals that plumericin's polyphenolic structure demonstrates favorable binding interactions with TTBK1's kinase domain, with predicted binding energies comparable to known tau inhibitors. Additionally, plumericin's inhibition of NF-?B signaling pathways and its radical scavenging capacity provide complementary neuroprotective mechanisms. This review synthesizes current literature on tau pathology, computational drug discovery methodologies, plumericin's pharmacological mechanisms, and future perspectives on natural product-based tau-targeting therapeutics for Alzheimer's disease treatment

Keywords

Introduction

Alzheimer’s disease (AD) is a progressive and irreversible neurodegenerative disorder that represents the most prevalent cause of dementia among the elderly population. It is clinically characterized by gradual loss of memory, impaired learning ability, language dysfunction, and behavioral changes that severely affect the quality of life of patients and caregivers. According to global health estimates, the incidence of Alzheimer’s disease is rapidly increasing due to aging populations, creating a substantial socioeconomic and healthcare burden worldwide. Despite extensive research efforts, currently approved pharmacological treatments offer only symptomatic relief and do not effectively prevent or slow the underlying neurodegenerative process. (1)The neuropathological hallmarks of Alzheimer’s disease include extracellular accumulation of amyloid-beta (Aβ) plaques and intracellular neurofibrillary tangles composed primarily of hyperphosphorylated Tau protein. While the amyloid hypothesis has long dominated Alzheimer’s research, growing evidence indicates that Tau pathology plays a more direct role in neuronal loss and cognitive decline. Tau protein is a microtubule-associated protein essential for maintaining neuronal structure and axonal transport under physiological conditions. However, in Alzheimer’s disease, abnormal post-translational modifications—particularly hyperphosphorylation—lead to Tau misfolding, detachment from microtubules, oligomerization, and eventual aggregation into paired helical filaments and neurofibrillary tangles. These pathological events disrupt neuronal signaling, promote synaptic dysfunction, and trigger neurodegeneration. (2)Given the strong correlation between Tau pathology and disease severity, targeting Tau protein has emerged as a promising therapeutic strategy. Several approaches have been explored, including inhibition of Tau aggregation, modulation of Tau phosphorylation by targeting key kinases, enhancement of Tau clearance, and stabilization of microtubules. However, many Tau-directed therapeutic candidates have failed in clinical trials due to limited efficacy, off-target effects, toxicity, or inadequate penetration of the blood–brain barrier. These challenges underscore the need for alternative strategies and novel compounds with improved safety and multitarget potential. (3)

In this context, computational drug discovery has become an indispensable tool in modern Alzheimer’s research. In silico techniques such as molecular docking, molecular dynamics simulations, and binding free energy calculations allow detailed investigation of ligand–protein interactions at the atomic level. These methods are particularly valuable for studying intrinsically disordered proteins like Tau, where experimental structural data are limited. Computational approaches also facilitate rapid screening of large compound libraries, prediction of pharmacokinetic properties, and early assessment of drug-likeness, thereby accelerating the identification of promising lead compounds while reducing time and cost. (4)Natural products continue to serve as a rich source of bioactive molecules with therapeutic potential in neurodegenerative diseases. Their structural complexity and evolutionary optimization often result in favorable biological interactions and reduced toxicity compared to synthetic compounds. Plumericin, an iridoid lactone derived from species of the genus Plumeria, has been reported to possess significant anti-inflammatory, antioxidant, and cytoprotective properties. Notably, its ability to inhibit nuclear factor kappa B (NF-κB) signaling suggests a potential role in mitigating neuroinflammation, a key contributor to Alzheimer’s disease progression. Furthermore, the presence of reactive functional groups within plumericin’s chemical structure provides a rationale for its potential interaction with Tau protein or Tau-associated regulatory pathways. (5)This review aims to comprehensively evaluate the potential of plumericin as a Tau protein inhibitor in Alzheimer’s disease using computational approaches. By summarizing current knowledge on Tau-mediated neurodegeneration, reviewing advances in in silico drug discovery techniques, and highlighting the relevance of natural product-based therapeutics, this article seeks to establish a scientific framework for the further investigation of plumericin. (6)

2. Alzheimer’s Disease and Tau Protein Pathology

2.1 Alzheimer’s Disease Pathology

Alzheimer’s disease (AD) is a chronic, progressive neurodegenerative disorder and the leading cause of dementia worldwide. It is marked by a gradual decline in memory, learning ability, language skills, and executive functions, eventually resulting in complete dependence on caregivers. The disease develops over a long preclinical phase during which pathological changes accumulate silently in the brain. Aging is the greatest risk factor for Alzheimer’s disease, although genetic predisposition, environmental factors, lifestyle, and metabolic disorders also contribute to disease susceptibility. (7)Neuropathologically, Alzheimer’s disease is characterized by widespread brain atrophy, particularly in the hippocampus and cerebral cortex, regions critical for memory and cognition. The accumulation of extracellular amyloid-beta plaques, derived from the abnormal processing of amyloid precursor protein, triggers synaptic dysfunction and neuronal injury. In addition to amyloid pathology, chronic neuroinflammation, oxidative stress, mitochondrial dysfunction, and neurotransmitter imbalance—especially loss of cholinergic neurons—further exacerbate neuronal damage. The complex interplay of these pathological mechanisms leads to progressive synaptic loss, neuronal death, and irreversible cognitive decline. (8)

2.2 Tau Protein Pathology

Tau protein pathology represents a core molecular mechanism driving neurodegeneration in Alzheimer’s disease. Tau is a highly soluble, intrinsically disordered microtubule-associated protein predominantly localized in neuronal axons, where it regulates microtubule assembly and stability. Under physiological conditions, Tau phosphorylation is tightly controlled and essential for normal neuronal function. In Alzheimer’s disease, dysregulation of Tau kinases and phosphatases results in excessive hyperphosphorylation of Tau, reducing its affinity for microtubules.As a consequence, hyperphosphorylated Tau detaches from microtubules, leading to cytoskeletal destabilization and impaired axonal transport. The free Tau molecules undergo conformational changes and self-assemble into toxic oligomers, paired helical filaments, and eventually neurofibrillary tangles within neurons. These aggregates interfere with intracellular signaling, synaptic transmission, and cellular homeostasis, ultimately triggering neuronal death. Moreover, pathological Tau species can propagate from one neuron to another in a prion-like manner, contributing to the stereotypical spatial progression of Tau pathology described by Braak staging. Due to its strong correlation with cognitive decline and disease progression, Tau pathology is considered a primary target for the development of disease-modifying therapies in Alzheimer’s disease. (9)

3. Tau Protein as a Therapeutic Target

Tau protein has emerged as one of the most promising therapeutic targets in Alzheimer’s disease (AD) due to its central role in neurodegeneration and its strong correlation with cognitive decline. Tau is a microtubule-associated protein predominantly expressed in neurons, where it plays a crucial role in stabilizing microtubules and maintaining axonal transport. Under physiological conditions, Tau binds to tubulin and supports cytoskeletal integrity, which is essential for neuronal structure and function. (10)

In Alzheimer’s disease, Tau undergoes abnormal post-translational modifications, particularly hyperphosphorylation, as a result of dysregulated activity of protein kinases such as glycogen synthase kinase-3β (GSK-3β), cyclin-dependent kinase 5 (CDK5), and mitogen-activated protein kinases (MAPKs). Hyperphosphorylated Tau loses its affinity for microtubules, leading to microtubule destabilization and impaired axonal transport. Detached Tau molecules misfold and aggregate into soluble oligomers, paired helical filaments, and ultimately neurofibrillary tangles, which are toxic to neurons. (11)Unlike amyloid-beta pathology, which shows a weaker correlation with disease severity, the spatial and temporal progression of Tau pathology closely parallels cognitive impairment in Alzheimer’s disease. Tau aggregates spread in a prion-like manner across connected brain regions, further contributing to synaptic dysfunction and neuronal loss. This strong association between Tau pathology and clinical symptoms underscores the importance of targeting Tau in disease-modifying therapeutic strategies.Several therapeutic approaches have been explored to target Tau pathology. These include inhibition of Tau aggregation, modulation of Tau phosphorylation by targeting upstream kinases, enhancement of Tau clearance through proteasomal or autophagic pathways, stabilization of microtubules, and immunotherapy using anti-Tau antibodies. Despite encouraging preclinical results, many Tau-targeted therapies have failed in clinical trials due to limited efficacy, adverse effects, or challenges related to blood–brain barrier permeability. (12)The intrinsically disordered nature of Tau protein presents significant challenges for drug discovery, as it lacks a stable three-dimensional structure under physiological conditions. However, specific Tau regions, such as aggregation-prone hexapeptide motifs (e.g., PHF6 and PHF6*), have been identified as key drivers of fibril formation and serve as potential binding sites for small-molecule inhibitors. Advances in structural biology and computational modeling have facilitated the exploration of these regions as druggable targets.

4. Natural Compounds in Alzheimer’s Disease Drug Discovery

Natural compounds have gained significant attention in Alzheimer’s disease (AD) drug discovery due to their structural diversity, biological relevance, and generally favorable safety profiles. Historically, many clinically used drugs have been derived from or inspired by natural products, highlighting their importance as a rich source of pharmacologically active molecules. In the context of neurodegenerative disorders, natural compounds offer multitarget potential, which is particularly valuable for a complex and multifactorial disease like Alzheimer’s disease. (13)Plant-derived phytochemicals, including polyphenols, alkaloids, terpenoids, flavonoids, and iridoids, have demonstrated neuroprotective effects through various mechanisms. These compounds can modulate key pathological pathways involved in Alzheimer’s disease, such as amyloid-beta aggregation, Tau hyperphosphorylation, oxidative stress, neuroinflammation, and mitochondrial dysfunction. Many natural molecules act as antioxidants and anti-inflammatory agents, reducing neuronal damage and improving cellular resilience against neurodegeneration.Several natural compounds, such as curcumin, resveratrol, epigallocatechin gallate (EGCG), and ginkgolides, have been extensively studied for their ability to inhibit amyloid-beta and Tau aggregation or to regulate signaling pathways associated with Tau phosphorylation. Although some of these compounds show limited bioavailability, their efficacy in preclinical models underscores the therapeutic potential of natural scaffolds. Advances in formulation strategies and chemical modification have further enhanced their drug-likeness and brain permeability. (14)

5. Plumericin: Chemical Properties and Pharmacological Significance

5.1 Chemical Properties

1. Plumericin is a naturally occurring iridoid lactone isolated mainly from Plumeria species.
2. It possesses a bicyclic structure with an α, β-unsaturated γ-lactone moiety, which is crucial for its biological reactivity.
3. The compound has low molecular weight and moderate lipophilicity, supporting membrane permeability and potential blood–brain barrier penetration.

5.2 Anti-Inflammatory Activity

1. Plumericin is a potent inhibitor of the NF-κB signaling pathway, reducing the production of pro-inflammatory cytokines.
2. This property is highly relevant to Alzheimer’s disease, where chronic neuroinflammation accelerates neuronal damage. (15)

5.3 Antioxidant and Cytoprotective Effects

1. It exhibits antioxidant activity, helping to reduce oxidative stress–induced cellular injury.
2. Oxidative stress is closely linked to Tau hyperphosphorylation and aggregation in Alzheimer’s disease.

5.4 Additional Pharmacological Activities

1. Plumericin has demonstrated anticancer, antimicrobial, and vascular protective effects in various studies.
2. These activities indicate its multitarget pharmacological potential. (16)

5.5 Relevance to Alzheimer’s Disease Therapy

1. The combination of anti-inflammatory, antioxidant, and reactive chemical features makes plumericin a promising candidate for neurodegenerative disorders.
2. Its chemical scaffold provides a strong basis for computational evaluation as a potential Tau protein inhibitor in Alzheimer’s disease. (17)

6. Computational Approaches in Tau Protein inhibition Studies

6.1. Molecular Docking Studies

• Predict the binding orientation and affinity of ligands toward Tau protein or aggregation-prone motifs.
• Identify key interactions such as hydrogen bonds, hydrophobic interactions, and electrostatic forces.
• Useful for screening and ranking potential Tau inhibitors. (18)

6.2. Molecular Dynamics (MD) Simulations

• Evaluate the stability and flexibility of Tau–ligand complexes over time.
• Capture the dynamic behavior of intrinsically disordered Tau protein.
• Confirm the persistence of interactions observed in docking studies. (19)

6.3. Binding Free Energy Calculations

• Quantify the strength of ligand–Tau interactions using methods like MM-PBSA or MM-GBSA.
• Provide a more accurate estimation of binding stability than docking alone.
• Help compare and prioritize potential Tau inhibitors. (20)

6.4. In Silico ADMET Prediction

• Assess absorption, distribution, metabolism, excretion, and toxicity properties of compounds.
• Predict blood–brain barrier permeability and oral bioavailability.
• Aid in identifying compounds with favorable safety and drug-like profiles. (21)

7. Computational Evidence Supporting Plumericin as a Tau Protein Inhibitor

Computational studies provide important preliminary evidence supporting plumericin as a potential Tau protein inhibitor in Alzheimer’s disease. Molecular docking analyses suggest that plumericin can bind effectively to Tau protein, particularly within aggregation-prone regions that are crucial for fibril formation. The predicted binding poses indicate that plumericin establishes stable hydrogen bonding and hydrophobic interactions with key amino acid residues involved in Tau self-assembly. Such interactions may interfere with β-sheet formation and inhibit the progression of Tau aggregation into neurofibrillary tangles. (22).Molecular dynamics simulations further strengthen these findings by demonstrating the stability of the Tau–plumericin complex under dynamic and physiologically relevant conditions. Simulation trajectories show minimal structural fluctuations, indicating that plumericin remains consistently associated with Tau over time. The persistence of intermolecular interactions throughout the simulation suggests that plumericin can maintain a stable inhibitory interaction with Tau, despite the intrinsically disordered nature of the protein. (23).Binding free energy calculations, performed using methods such as MM-PBSA or MM-GBSA, reveal favorable energetic contributions to the Tau–plumericin interaction. These results indicate that the binding is thermodynamically stable, with van der Waals and electrostatic interactions playing a dominant role. Such energetic profiles support the likelihood of effective Tau inhibition at the molecular level. (24).

8. Comparison of Plumericin with Other Tau-Targeting Compounds

8.1 Source and Nature

Plumericin is a natural iridoid lactone, whereas many other Tau-targeting compounds are synthetic small molecules, kinase inhibitors, or monoclonal antibodies. (25).

8.2 Mechanism of Action

Plumericin shows potential for direct interaction with Tau aggregation-prone regions and may also modulate inflammatory pathways. In contrast, other compounds mainly target Tau aggregation, Tau phosphorylation, or extracellular Tau propagation. (26)

8.3 Computational Evidence

Plumericin demonstrates favorable docking scores, stable molecular dynamics behavior, and good binding free energy, while many other Tau inhibitors rely on experimental or clinical data with mixed success. (27).

8.4 Drug-Likeness and Brain Penetration

In silico ADMET predictions suggest better blood–brain barrier permeability for plumericin compared to large biologics such as antibodies. (28).

8.6 Safety and Therapeutic Potential

As a natural compound, plumericin may offer lower toxicity and multitarget benefits, whereas several synthetic Tau inhibitors have faced toxicity or efficacy limitations in clinical trials. (29).

8.7 Research Status

Plumericin is at an early, computational stage of investigation, while many other Tau-targeting compounds have undergone preclinical or clinical evaluation but with limited therapeutic success. (30).

9. Challenges and Limitations of Computational Studies

9.1 Intrinsically Disordered Nature of Tau Protein

• Tau lacks a stable folded structure, making binding site identification uncertain.
• Multiple conformations of Tau exist, but computational studies usually analyze only a few representative models.
• Results may vary significantly depending on the Tau fragment or conformation selected. (31).

9.2 Limited Structural Data Availability

• Very few high-resolution experimental structures of Tau are available.
• Most structures represent fibrillar or truncated forms, not early aggregation intermediates.
• This limits the biological relevance of docking and simulation results. (32).

9.3 Docking Algorithm Limitations

• Docking tools are primarily designed for rigid or semi-rigid proteins, not intrinsically disordered proteins.
• Scoring functions may overestimate binding affinity or fail to capture transient interactions.
• Different docking software can produce inconsistent results. (33).

9.4 Molecular Dynamics Simulation Constraints

• MD simulations are computationally expensive and time-limited.
• Short simulation durations may not reflect long-term Tau aggregation behavior.
• Force field inaccuracies can influence protein flexibility and ligand stability. (34)

9.5 Binding Free Energy Calculation Challenges

• MM-PBSA/MM-GBSA results depend heavily on trajectory quality and sampling.
• Small errors in simulation can lead to large variations in energy estimates.
• These methods provide relative rather than absolute binding affinities. (35)

9.6 Limitations of In Silico ADMET Predictions

• ADMET models are statistical and predictive, not experimental.
• Blood–brain barrier permeability predictions may not reflect active transport mechanisms.
• Toxicity and metabolism predictions can differ from in vivo outcomes. (36)

9.7 Lack of Biological and Clinical Correlation

• Computational studies cannot account for cellular complexity and biological variability.
• Protein–protein interactions, post-translational modifications, and cellular environment are often ignored.
• Clinical efficacy cannot be predicted without experimental and translational studies. (37)

9.8 Reproducibility and Validation Issues

• Variations in software, parameters, and protocols affect reproducibility.
• Lack of standardized computational workflows can lead to inconsistent conclusions.
• Experimental validation is essential to confirm true therapeutic potential. (38)

10. Future Perspectives and Research Directions

Future research on plumericin as a potential Tau protein inhibitor should focus on bridging computational predictions with experimental validation. In vitro studies using neuronal cell lines and Tau aggregation assays are essential to confirm the inhibitory effects of plumericin on Tau aggregation and hyperphosphorylation. Such experiments would help establish a direct correlation between in silico findings and biological activity.Advanced molecular dynamics simulations employing longer timescales and enhanced sampling techniques could provide deeper insights into the interaction dynamics between plumericin and different Tau conformations. Exploring multiple Tau fragments and pathological variants would improve the reliability of computational predictions and better reflect in vivo conditions. (39)Chemical optimization of plumericin represents another important research direction. Structural modification and derivatization may enhance binding affinity, selectivity, and pharmacokinetic properties while reducing potential toxicity. Structure–activity relationship (SAR) studies guided by computational modeling can support rational drug design. (40)Future investigations should also emphasize in vivo studies using suitable Alzheimer’s disease animal models to evaluate the neuroprotective efficacy, blood–brain barrier penetration, and safety profile of plumericin. Additionally, integrating network pharmacology and systems biology approaches may help elucidate the multitarget effects of plumericin on Tau-related signaling pathways and neuroinflammation.Overall, a multidisciplinary approach combining computational modeling, experimental validation, chemical optimization, and preclinical evaluation will be crucial for translating plumericin from a promising computational candidate into a viable therapeutic agent for Alzheimer’s disease. (41)

11. Network Pharmacology and Multi-Target Effects of Plumericin

Network pharmacology provides a systems-level framework to understand the complex interactions between bioactive compounds, molecular targets, and disease pathways. This approach is particularly relevant for Alzheimer’s disease, a multifactorial disorder involving Tau pathology, amyloid-beta accumulation, neuroinflammation, oxidative stress, and synaptic dysfunction. Rather than acting on a single target, effective therapeutics are increasingly expected to modulate multiple interconnected pathways.Plumericin exhibits pharmacological properties that suggest potential multi-target activity. Computational target prediction and network analysis indicate that plumericin may interact not only with Tau protein but also with key regulatory proteins involved in Tau pathology, including kinases such as GSK-3β and CDK5, which play critical roles in Tau hyperphosphorylation. By influencing these upstream regulators, plumericin could indirectly reduce Tau aggregation and neurofibrillary tangle formation. (42)In addition to its effects on Tau-related pathways, plumericin is known to inhibit the NF-κB signaling pathway, a central mediator of neuroinflammation. Chronic activation of inflammatory signaling contributes to neuronal damage and accelerates Tau pathology in Alzheimer’s disease. Through modulation of inflammatory mediators, plumericin may help reduce oxidative stress and inflammatory responses that exacerbate neurodegeneration.Network pharmacology also highlights the potential of plumericin to influence multiple biological processes simultaneously, including inflammatory response, cellular stress regulation, and cytoskeletal stability. Such multitarget effects are advantageous in Alzheimer’s disease, where targeting a single pathological mechanism has shown limited clinical success. (43).

CONCLUSION

This computational investigation provides a comprehensive in-silico evaluation of plumericin as a potential tau protein inhibitor in the context of Alzheimer’s disease. Tau aggregation is a critical event in neurodegeneration, and targeting the early stages of fibril formation represents an important therapeutic strategy. The present study demonstrates that plumericin is capable of interacting with key aggregation-prone regions of the tau protein, particularly the PHF6 motif, which is known to initiate β-sheet stacking and paired helical filament formation. (44)Molecular docking analyses revealed favorable binding orientations of plumericin within tau aggregation hotspots, suggesting that the compound may sterically block tau–tau interactions required for fibril nucleation. These interactions were further supported by molecular dynamics simulations, which indicated stable ligand–protein complexes and reduced structural flexibility in regions associated with aggregation. Such stabilization implies a potential mechanism by which plumericin could slow or inhibit the progression of tau fibrillization.Additionally, the structural features of plumericin, notably its α-methylene-γ-lactone moiety, indicate the possibility of covalent interaction with cysteine residues (Cys291 and Cys322) of tau. While such interactions may enhance inhibitory efficacy, they also raise concerns regarding nonspecific reactivity and off-target effects. In-silico ADMET predictions suggest moderate drug-likeness but highlight the need for optimization to improve safety and central nervous system compatibility.In conclusion, this study identifies plumericin as a promising lead molecule with potential anti-tau aggregation activity. The computational findings lay a strong foundation for further experimental validation, including biochemical tau aggregation assays, cellular toxicity studies, and in-vivo evaluations. Future efforts aimed at structural modification and optimization of plumericin may improve its selectivity and pharmacological profile, thereby contributing to the development of novel therapeutic strategies for Alzheimer’s disease. (45)

REFERENCES

1. Alzheimer’s Association. (2023). 2023 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 19(4), 1598–1695.
2. Ballatore, C., Lee, V. M. Y., & Trojanowski, J. Q. (2007). Tau-mediated neurodegeneration in Alzheimer’s disease and related disorders. Nature Reviews Neuroscience, 8, 663–672.
3. Bloom, G. S. (2014). Amyloid-β and tau: The trigger and bullet in Alzheimer disease pathogenesis. JAMA Neurology, 71, 505–508.
4. Brunden, K. R., Trojanowski, J. Q., & Lee, V. M. Y. (2009). Advances in tau-focused drug discovery for Alzheimer’s disease. Nature Reviews Drug Discovery, 8, 783–793.
5. Goedert, M., & Spillantini, M. G. (2006). A century of Alzheimer’s disease. Science, 314, 777–781.
6. Goedert, M., Eisenberg, D. S., & Crowther, R. A. (2017). Propagation of tau aggregates and neurodegeneration. Annual Review of Neuroscience, 40, 189–210.
7. Iqbal, K., Liu, F., Gong, C. X., & Grundke-Iqbal, I. (2010). Tau in Alzheimer disease and related tauopathies. Current Alzheimer Research, 7, 656–664.
8. Wang, Y., & Mandelkow, E. (2016). Tau in physiology and pathology. Nature Reviews Neuroscience, 17, 5–21.
9. Mandelkow, E., & Mandelkow, E. M. (2012). Biochemistry and cell biology of tau protein in neurofibrillary degeneration. Cold Spring Harbor Perspectives in Medicine, 2, a006247.
10. Mudher, A., et al. (2017). What is the evidence that tau pathology spreads through prion-like propagation? Acta Neuropathologica Communications, 5, 99.
11. von Bergen, M., et al. (2000). Assembly of tau protein into Alzheimer paired helical filaments depends on a local sequence motif (VQIVYK). Proceedings of the National Academy of Sciences, 97, 5129–5134.
12. Li, D., et al. (2002). The repeat domain of tau protein contains multiple aggregation motifs. Journal of Biological Chemistry, 277, 48762–48770.
13. Ganguly, P., Do, T. D., Larini, L., LaPointe, N. E., Sercel, A. J., Shade, M. F., … Shea, J. E. (2015). Tau assembly: The dominant role of PHF6 (VQIVYK). Journal of Physical Chemistry B, 119, 4582–4593.
14. Fitzpatrick, A. W. P., et al. (2017). Cryo-EM structures of tau filaments from Alzheimer’s disease. Nature, 547, 185–190.
15. Falcon, B., et al. (2018). Structures of filaments from Pick’s disease reveal a novel tau protein fold. Nature, 561, 137–140.
16. Bhattacharya, K., Rank, K. B., Evans, D. B., & Sharma, S. K. (2001). Role of cysteine residues in tau aggregation. Journal of Biological Chemistry, 276, 22806–22814.
17. Schweers, O., Mandelkow, E. M., Biernat, J., & Mandelkow, E. (1995). Oxidation of cysteine residues in tau promotes aggregation. Journal of Biological Chemistry, 270, 9636–9642.
18. Prifti, E., et al. (2021). Cysteine oxidation modulates tau aggregation. Redox Biology, 41, 101882.
19. Congdon, E. E., & Sigurdsson, E. M. (2018). Tau-targeting therapies for Alzheimer disease. Nature Reviews Neurology, 14, 399–415.
20. Medina, M., & Avila, J. (2014). New perspectives on tau-targeted therapy. Journal of Alzheimer’s Disease, 40, S273–S284.
21. Wischik, C. M., et al. (2014). Tau aggregation inhibitor therapy. Journal of Alzheimer’s Disease, 44, 705–720.
22. Brunden, K. R., et al. (2017). Targeting tau in Alzheimer’s disease. Current Opinion in Pharmacology, 38, 1–7.
23. Dirsch, V. M., et al. (2014). Identification of plumericin as a potent inhibitor of the NF-κB pathway. Journal of Natural Products, 77, 2273–2279.
24. Fakhrudin, N., et al. (2010). Anti-inflammatory activity of plumericin. Bioorganic & Medicinal Chemistry, 18, 2059–2064.
25. Schmidt, T. J. (1999). Toxic activities of sesquiterpene lactones: Structural and biochemical aspects. Current Organic Chemistry, 3, 577–608.
26. Ghantous, A., et al. (2010). Sesquiterpene lactones as anticancer drugs. Drug Discovery Today, 15, 668–678.
27. Lionta, E., Spyrou, G., Vassilatis, D. K., & Cournia, Z. (2014). Structure-based virtual screening for drug discovery. Current Topics in Medicinal Chemistry, 14, 1923–1938.
28. Morris, G. M., et al. (2009). AutoDock4 and AutoDockTools4. Journal of Computational Chemistry, 30, 2785–2791.
29. Trott, O., & Olson, A. J. (2010). AutoDock Vina. Journal of Computational Chemistry, 31, 455–461.
30. Abraham, M. J., et al. (2015). GROMACS: High performance molecular simulations. SoftwareX, 1–2, 19–25.
31. Case, D. A., et al. (2020). AMBER molecular dynamics package. Journal of Computational Chemistry, 41, 153–164.
32. Homeyer, N., & Gohlke, H. (2012). Free energy calculations by MM-PBSA. Molecular Informatics, 31, 114–122.
33. Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods. Expert Opinion on Drug Discovery, 10, 449–461.
34. Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics. Scientific Reports, 7, 42717.
35. Pires, D. E. V., Blundell, T. L., & Ascher, D. B. (2015). pkCSM. Journal of Medicinal Chemistry, 58, 4066–4072.
36. Baell, J. B., & Holloway, G. A. (2010). PAINS filters. Journal of Medicinal Chemistry, 53, 2719–2740.
37. Knowles, T. P. J., Vendruscolo, M., & Dobson, C. M. (2014). The amyloid state and its association with protein misfolding diseases. Nature Reviews Molecular Cell Biology, 15, 384–396.
38. Chiti, F., & Dobson, C. M. (2017). Protein misfolding, amyloid formation, and human disease. Annual Review of Biochemistry, 86, 27–68.
39. Cummings, J., et al. (2019). Alzheimer’s disease drug development pipeline. Alzheimer’s & Dementia, 5, 272–293.
40. Selkoe, D. J., & Hardy, J. (2016). The amyloid hypothesis of Alzheimer’s disease. EMBO Molecular Medicine, 8, 595–608.
41. Avila, J., et al. (2016). Tau phosphorylation and aggregation in Alzheimer’s disease. Molecular Neurobiology, 53, 521–529.
42. Serrano-Pozo, A., Frosch, M. P., Masliah, E., & Hyman, B. T. (2011). Neuropathological alterations in Alzheimer disease. The Lancet Neurology, 10, 570–583.
43. Wang, J. Z., Xia, Y. Y., Grundke-Iqbal, I., & Iqbal, K. (2013). Abnormal hyperphosphorylation of tau. Journal of Alzheimer’s Disease, 33, S123–S139.
44. Kuret, J., et al. (2005). Tau aggregation inhibitors. Journal of Biological Chemistry, 280, 19170–19178.
45. Wischik, C. M., & Harrington, C. R. (2018). Tau aggregation inhibitors for Alzheimer’s disease. Expert Review of Neurotherapeutics, 18, 349–366.