Discovery of new multifunctional selective acetylcholinesterase inhibitors: structure-based virtual screening and biological evaluation

Methoxy-naphthyl-Linked N-Benzyl Pyridinium Styryls as Dual Cholinesterase Inhibitors: Design, Synthesis, Biological Evaluation, and Structure-Activity Relationship

The multifaceted nature of Alzheimer's disease (AD) indicates the need for multitargeted agents as potential therapeutics. Both cholinesterases (ChEs), acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), play a vital role in disease progression. Thus, inhibiting both ChEs is more beneficial than only one for effectively managing AD. The present study provides a detailed lead optimization of the e-pharmacophore-generated pyridinium styryl scaffold to discover a dual ChE inhibitor. A structure-activity relationship analysis indicated the importance of three structural fragments, methoxy-naphthyl, vinyl-pyridinium, and substituted-benzyl, in a dual ChE inhibitor pharmacophore. The optimized 6-methoxy-naphthyl derivative, 7av (SB-1436), inhibits EeAChE and eqBChE with IC₅₀ values of 176 and 370 nM, respectively. The kinetic study has shown that 7av inhibits AChE and BChE in a non-competitive manner with k_i values of 46 and 115 nM, respectively. The docking and molecular dynamics simulation demonstrated that 7av binds with the catalytic and peripheral anionic sites of AChE and BChE. Compound 7av also significantly stops the self-aggregation of Aβ. The data presented herein indicate the potential of 7av for further investigation in preclinical models of AD.

Validation of Acetylcholinesterase Inhibition Machine Learning Models for Multiple Species

Acetylcholinesterase (AChE) is an important enzyme and target for human therapeutics, environmental safety, and global food supply. Inhibitors of this enzyme are also used for pest elimination and can be misused for suicide or chemical warfare. Adverse effects of AChE pesticides on nontarget organisms, such as fish, amphibians, and humans, have also occurred as a result of biomagnifications of these toxic compounds. We have exhaustively curated the public data for AChE inhibition data and developed machine learning classification models for seven different species. Each set of models were built using up to nine different algorithms for each species and Morgan fingerprints (ECFP6) with an activity cutoff of 1 μM. The human (4075 compounds) and eel (5459 compounds) consensus models predicted AChE inhibition activity using external test sets from literature data with 81% and 82% accuracy, respectively, while the reciprocal cross (76% and 82% percent accuracy) was not species-specific. In addition, we also created machine learning regression models for human and eel AChE inhibition to return a predicted IC₅₀ value for a queried molecule. We did observe an improved species specificity in the regression models, where a human support vector regression model of human AChE inhibition (3652 compounds) predicted the IC₅₀s of the human test set to a better extent than the eel regression model (4930 compounds) on the same test set, based on mean absolute percentage error (MAPE = 9.73% vs 13.4%). The predictive power of these models certainly benefits from increasing the chemical diversity of the training set, as evidenced by expanding our human classification model by incorporating data from the Tox21 library of compounds. Of the 10 compounds we tested that were predicted active by this expanded model, two showed >80% inhibition at 100 μM. This machine learning approach therefore offers the ability to rapidly score massive libraries of molecules against the models for AChE inhibition that can then be selected for future in vitro testing to identify potential toxins. It also enabled us to create a public website, MegaAChE, for single-molecule predictions of AChE inhibition using these models at megaache.collaborationspharma.com.

Natural Inhibitors of Cholinesterases: Chemistry, Structure-Activity and Methods of Their Analysis

This article aims to provide an updated description and comparison of the data currently available in the literature (from the last 15 years) on the studied natural inhibitors of cholinesterases (IChEs), namely, acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). These data also apply to the likely impact of the structures of the compounds on the therapeutic effects of available and potential cholinesterase inhibitors. IChEs are hitherto known compounds with various structures, activities and origins. Additionally, multiple different methods of analysis are used to determine the cholinesterase inhibitor potency. This summary indicates that natural sources are still suitable for the discovery of new compounds with prominent pharmacological activity. It also emphasizes that further studies are needed regarding the mechanisms of action or the structure-activity correlation to discuss the issue of cholinesterase inhibitors and their medical application.

Multi-Level High-Throughput Screening for Discovery of Ligands That Inhibit Insulin Aggregation

We have developed a multi-level virtual screening protocol to identify lead molecules from the FDA inactives database that can inhibit insulin aggregation. The method is based on the presence of structural and interaction specificity in non-native aggregation pathway protein-protein interactions. Some key challenges specific to the present problem, when compared with native protein association, include structural heterogeneity of the protein species involved, multiple association pathways, and relatively higher probability of conformational rearrangement of the association complex. In this multi-step method, the inactives database was first screened using the dominant pharmacophore features of previously identified molecules shown to significantly inhibit insulin aggregation nucleation by binding to its aggregation-prone conformers. We then performed ensemble docking of several low-energy ligand conformations on these aggregation-prone conformers followed by molecular dynamics simulations and binding affinity calculations on a subset of docked complexes to identify a final set of five potential lead molecules to inhibit insulin aggregation nucleation. Their effect on aggregation inhibition was extensively investigated by incubating insulin under aggregation-prone aqueous buffer conditions (low pH, high temperature). Aggregation kinetics were characterized using size exclusion chromatography and Thioflavin T fluorescence assay, and the secondary structure was determined using circular dichroism spectroscopy. Riboflavin provided the best aggregation inhibition, with 85% native monomer retention after 48 h incubation under aggregation-prone conditions, whereas the no-ligand formulation showed complete monomer loss after 36 h. Further, insulin incubated with two of the screened inactives (aspartame, riboflavin) had the characteristic α-helical dip in CD spectra, while the no-ligand formulation showed a change to β-sheet rich conformations.

Identifying Possible AChE Inhibitors from Drug-like Molecules via Machine Learning and Experimental Studies

Acetylcholinesterase (AChE) is one of the most important drug targets for Alzheimer's disease (AD) treatment. In this work, a machine learning model was trained to rapidly and accurately screen large chemical databases for the potential inhibitors of AChE. The obtained results were then validated via in vitro enzyme assay. Moreover, atomistic simulations including molecular docking and molecular dynamics simulations were then used to understand molecular insights into the binding process of ligands to AChE. In particular, two compounds including benzyl trifluoromethyl ketone and trifluoromethylstyryl ketone were indicated as highly potent inhibitors of AChE because they established IC₅₀ values of 0.51 and 0.33 μM, respectively. The obtained IC₅₀ of two compounds is significantly lower than that of galantamine (2.10 μM). The predicted log(BB) suggests that the compounds may be able to traverse the blood-brain barrier. A good agreement between computational and experimental studies was observed, indicating that the hybrid approach can enhance AD therapy.

Iboga-type alkaloids with Indolizidino[8,7-b]Indole scaffold and bisindole alkaloids from Tabernaemontana bufalina Lour

Phytochemical investigation on the aerial parts of Tabernaemontana bufalina Lour. (Apocynaceae) led to the identification of four undescribed monoterpenoid indole alkaloids named taberbufamines A-D, an undescribed natural product, and fourteen known indole alkaloids. The structures of the undescribed alkaloids were established by spectroscopic and computational methods, and their absolute configurations were further determined by quantum chemical TDDFT calculations and the experimental ECD spectra. Taberbufamines A and B possessed an uncommon skeleton incorporating an indolizidino [8,7-b]indole motif with a 2-hydroxymethyl-butyl group attached at the pyrrolidine ring. Biosynthetically, Taberbufamines A and B might be derived from iboga-type alkaloid through rearrangement. Vobatensine C showed significant bioactivity against A-549, Bel-7402, and HCT-116 cells with IC₅₀ values of 2.61, 1.19, and 1.74 μM, respectively. Ervahanine A showed antimicrobial activity against Bacillus subtilis, Mycobacterium smegmatis, and Helicobacter pylori with MIC values of 4, 8, and 16 μg/mL, respectively. 19(S)-hydroxyibogamine was shown as butyrylcholinesterase inhibitor (IC₅₀ of 20.06 μM) and α-glycosidase inhibitor (IC₅₀ of 17.18 μM), while tabernamine, ervahanine B, and ervadivaricatine B only showed α-glycosidase inhibitory activities with IC₅₀ values in the range of 0.95-4.61 μM.

Japonisine A, a fawcettimine-type Lycopodium alkaloid with an unusual skeleton from Lycopodium japonicum Thunb

Japonisine A, a novel fawcettimine-type Lycopodium alkaloid with an unusual skeleton and two new fawcettimine-type ones, along with 20 known Lycopodium alkaloids, were isolated from the whole plants of Lycopodium japonicum Thunb. Their structures were determined by extensive spectroscopic analysis, including 1D and 2D NMR, and HR-ESIMS, as well as by comparison with the literature data. Notably, japonisine A (1) was the first example of fawcettimine-related Lycopodium alkaloid with a 2-oxopropyl attached at C-6. All the isolates were evaluated for their inhibitory effects on acetylcholinesterase (AChE) and α-glucosidase. Unfortunately, the results indicated that all the compounds were inactive against the acetylcholinesterase (AChE) and α-glucosidase.

In vivo Evaluation of a Newly Synthesized Acetylcholinesterase Inhibitor in a Transgenic Drosophila Model of Alzheimer's Disease

Alzheimer's disease is a neurodegenerative disease characterized by disrupted memory, learning functions, reduced life expectancy, and locomotor dysfunction, as a result of the accumulation and aggregation of amyloid peptides that cause neuronal damage in neuronal circuits. In the current study, we exploited a transgenic Drosophila melanogaster line, expressing amyloid-β peptides to investigate the efficacy of a newly synthesized acetylcholinesterase inhibitor, named XJP-1, as a potential AD therapy. Behavioral assays and confocal microscopy were used to characterize the drug effect on AD symptomatology and amyloid peptide deposition. The symptomatology induced in this particular transgenic model recapitulates the scenario observed in human AD patients, showing a shortened lifespan and reduced locomotor functions, along with a significant accumulation of amyloid plaques in the brain. XJP-1 treatment resulted in a significant improvement of AD symptoms and a reduction of amyloid plaques by diminishing the amyloid aggregation rate. In comparison with clinically effective AD drugs, our results demonstrated that XJP-1 has similar effects on AD symptomatology, but at 10 times lower drug concentration than donepezil. It also showed an earlier beneficial effect on the reduction of amyloid plaques at 10 days after drug treatment, as observed for donepezil at 20 days, while the other drugs tested have no such effect. As a novel and potent AChE inhibitor, our study demonstrates that inhibition of the enzyme AChE by XJP-1 treatment improves the amyloid-induced symptomatology in Drosophila, by reducing the number of amyloid plaques within the fruit fly CNS. Thus, compound XJP-1 has the therapeutic potential to be further investigated for the treatment of AD.

Recent Advances in Virtual Screening for Cholinesterase Inhibitors

Alzheimer's disease (AD) is a significant health crisis, and current treatments provide only limited benefits to cognition at the cost of serious side effects. Recently, virtual screening techniques such as ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) have emerged as powerful drug discovery tools for identifying potential ligands of a biological target from a large database of chemical structures. The cholinesterases are an AD target particularly well suited for drug discovery using virtual screening due to their well-characterized active sites and comprehensive understanding of the structure-activity relationships of existing inhibitors. Over the last 5 years (2015-2020), at least 15 studies have used virtual screening techniques to discover potent new cholinesterase inhibitors. Herein we review how LBVS and SBVS have been applied individually or in tandem to discover novel acetylcholinesterase and butyrylcholinesterase inhibitors for AD, and highlight the need to confirm in vitro activity of screening compounds.

The Antiviral Drug Tilorone Is a Potent and Selective Inhibitor of Acetylcholinesterase

Acetylcholinesterase (AChE) is an important drug target in neurological disorders like Alzheimer's disease, Lewy body dementia, and Parkinson's disease dementia as well as for other conditions like myasthenia gravis and anticholinergic poisoning. In this study, we have used a combination of high-throughput screening, machine learning, and docking to identify new inhibitors of this enzyme. Bayesian machine learning models were generated with literature data from ChEMBL for eel and human AChE inhibitors as well as butyrylcholinesterase inhibitors (BuChE) and compared with other machine learning methods. High-throughput screens for the eel AChE inhibitor model identified several molecules including tilorone, an antiviral drug that is well-established outside of the United States, as a newly identified nanomolar AChE inhibitor. We have described how tilorone inhibits both eel and human AChE with IC₅₀'s of 14.4 nM and 64.4 nM, respectively, but does not inhibit the closely related BuChE IC₅₀ > 50 μM. We have docked tilorone into the human AChE crystal structure and shown that this selectivity is likely due to the reliance on a specific interaction with a hydrophobic residue in the peripheral anionic site of AChE that is absent in BuChE. We also conducted a pharmacological safety profile (SafetyScreen44) and kinase selectivity screen (SelectScreen) that showed tilorone (1 μM) only inhibited AChE out of 44 toxicology target proteins evaluated and did not appreciably inhibit any of the 485 kinases tested. This study suggests there may be a potential role for repurposing tilorone or its derivatives in conditions that benefit from AChE inhibition.

Discovery of novel NF-кB inhibitor based on scaffold hopping: 1,4,5,6,7,8-hexahydropyrido[4,3-d]pyrimidine

NF-κB is a key signaling pathway molecule linking hepatoma and chronic inflammation. Inhibition of NF-κB activation can alleviate inflammation, and promote hepatoma cell apoptosis. In this study, a series of fluoro-substituted 1,4,5,6,7,8-hexahydropyrido[4,3-d]pyrimidines (PPMs, 31-57) were synthesized from 3,5-bis(arylidene)-4-piperidones (BAPs, 4-30) based on scaffold hopping. We successfully discovered the most potent 43 substituted by electron-withdrawing substitutes (3-F and 4-CF₃) exhibited less toxicity and higher anti-inflammatory activity. Preliminary mechanistic studies revealed that 43 induced dose-dependent cell apoptosis at cell and protein level, while inhibited NF-κB activation by suppressing LPS-induced phosphorylation levels of p65, IκBα and Akt, and by indirectly suppressing MAPK signaling, and by inhibiting the nuclear translocation of NF-κB induced by TNF-α or LPS. Docking analysis verified simulated 43 could reasonably bind to the active site of Bcl-2, p65 and p38 proteins. This compound, as a novel NF-κB inhibitor, also demonstrated both anti-inflammatory and anti-hepatoma activities, warranting its further development as a potential multifunctional agent for the clinical treatment of liver cancers and inflammatory diseases.

Discovery and Biological Evaluation of New Selective Acetylcholinesterase Inhibitors with Anti-Aβ Aggregation Activity through Molecular Docking-Based Virtual Screening

Discovery of novel multifunctional inhibitors targeting acetylcholinesterase (AChE) has becoming a hot spot in anti-Alzheimer's disease (AD) drug development. In the present study, four potent small molecule inhibitors (A01, A02, A03 and A04) of AChE with new chemical scaffold were identified. Inhibitor A03 displayed the most potent inhibition activity on AChE at enzymatic level with IC₅₀ value of 180 nM, and high selectivity towards AChE over butyrylcholinesterase (BChE) by more than 100-fold. The binding modes of compounds A01-A04 were carefully analyzed by molecular docking and molecular dynamics (MD) simulation to provide informative clues for further structure modification. Finally, the anti-amyloid beta (Aβ) aggregation and neuroprotective activity were also well investigated. Our findings highlighted the therapeutic promise of AChE inhibitors A01-A04 for AD treatment.

Discovery of New Selective Butyrylcholinesterase (BChE) Inhibitors with Anti-Aβ Aggregation Activity: Structure-Based Virtual Screening, Hit Optimization and Biological Evaluation

In this study, a series of selective butyrylcholinesterase (BChE) inhibitors was designed and synthesized from the structural optimization of hit 1, a 4-((3,4-dihydroisoquinolin-2(1H)-yl)methyl)benzoic acid derivative identified by virtual screening our compound library. The in vitro enzyme assay results showed that compounds 9 ((4-((3,4-dihydroisoquinolin-2(1H)-yl)methyl)phenyl)(pyrrolidin-1-yl)methanone) and 23 (N-(2-bromophenyl)-4-((3,4-dihydroisoquinolin-2(1H)-yl)methyl)benzamide) displayed improved BChE inhibitory activity and good selectivity towards BChE versus AChE. Their binding modes were probed by molecular docking and further validated by molecular dynamics simulation. Kinetic analysis together with molecular modeling studies suggested that these derivatives could target both the catalytic active site (CAS) and peripheral anionic site (PAS) of BChE. In addition, the selected compounds 9 and 23 displayed anti-Aβ_1–42 aggregation activity in a dose-dependent manner, and they did not show obvious cytotoxicity towards SH-SY5Y neuroblastoma cells. Also, both compounds showed significantly protective activity against Aβ_1-42-induced toxicity in a SH-SY5Y cell model. The present results provided a new valuable chemical template for the development of selective BChE inhibitors.