Discovery of novel dual acetylcholinesterase inhibitors with antifibrillogenic activity related to Alzheimer's disease

Unveiling new thiazole-clubbed piperazine derivatives as multitarget anti-AD: Design, synthesis, and in silico studies

New thiazole-clubbed piperazine derivatives were designed, synthesized, evaluated for their inhibitory capabilities against human acetylcholinesterase and butyrylcholinesterase (hAChE and/or hBuChE) and β-amyloid (Aβ) aggregation, and investigated for their metal chelating potential as multitarget agents for the treatment of Alzheimer's disease. Compounds 10, 19-21, and 24 showed the highest hAChE inhibitory activity at submicromolar concentrations, of which compound 10 was the most potent with a half-maximal inhibitory concentration (IC50) value of 0.151 μM. Compounds 10 and 20 showed the best hBuChE inhibitory activities (IC50 values of 0.135 and 0.103 μM, respectively), in addition to remarkable Aβ1-42 aggregation inhibitory activities and metal chelating capabilities. Both compounds were further evaluated against human neuroblastoma SH-SY5Y and PC12 neuronal cells, where they proved noncytotoxic at their active concentrations against hAChE or hBuChE. They also offered a significant neuroprotective effect against Aβ25-35-induced cytotoxicity in human neuroblastoma SH-SY5Y cells. Compound 10 displayed acceptable physicochemical properties and could pass the blood-brain barrier. The molecular docking study revealed the good binding interactions of compound 10 with the key amino acids of both the catalytic active site and the peripheral anionic site of hAChE, explaining its significant potency.

New Multitarget Molecules Derived from Caffeine as Potentiators of the Cholinergic System

Cholinergic deficit is a characteristic factor of several pathologies, such as myasthenia gravis, some types of congenital myasthenic syndromes, and Alzheimer's Disease. Two molecular targets for its treatment are acetylcholinesterase (AChE) and nicotinic acetylcholine receptor (nAChR). In previous studies, we found that caffeine behaves as a partial nAChR agonist and confirmed that it inhibits AChE. Here, we present new bifunctional caffeine derivatives consisting of a theophylline ring connected to amino groups by different linkers. All of them were more potent AChE inhibitors than caffeine. Furthermore, although some of them also activated muscle nAChR as partial agonists, not all of them stabilized nAChR in its desensitized conformation. To understand the molecular mechanism underlying these results, we performed docking studies on AChE and nAChR. The nAChR agonist behavior of the compounds depends on their accessory group, whereas their ability to stabilize the receptor in a desensitized state depends on the interactions of the linker at the binding site. Our results show that the new compounds can inhibit AChE and activate nAChR with greater potency than caffeine and provide further information on the modulation mechanisms of pharmacological targets for the design of novel therapeutic interventions in cholinergic deficit.

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.

Discovery of Guanidine Derivatives from Buthus martensii Karsch with Metal-Binding and Cholinesterase Inhibition Properties

Two rare guanidine-type alkaloids, Buthutin A (1) and Buthutin B (2), along with two other compounds (3, 4), were isolated from Buthus martensii Karsch, and determined using extensive spectroscopic data analysis and high resolution-mass spectrometry. Compound 1 showed the most potent inhibition on AChE and BChE with IC₅₀ values of 7.83 ± 0.06 and 47.44 ± 0.95 μM, respectively. Kinetic characterization of compound 1 confirmed a mixed-type of AChE inhibition mechanism in accordance with the docking results, which shows its interaction with both catalytic active (CAS) and peripheral anionic (PAS) sites. The specific binding of compound 1 to PAS domain of AChE was also confirmed experimentally. Moreover, compounds 1 and 3 exhibited satisfactory biometal binding abilities toward Cu²⁺, Fe²⁺, Zn²⁺ and Al³⁺ ions. These results provide a new evidence for further development and utilization of B. martensii in health and pharmaceutical products.

Identification of known drugs as potential SARS-CoV-2 Mpro inhibitors using ligand- and structure-based virtual screening

Background: The new coronavirus pandemic has had a significant impact worldwide, and therapeutic treatment for this viral infection is being strongly pursued. Efforts have been undertaken by medicinal chemists to discover molecules or known drugs that may be effective in COVID-19 treatment – in particular, targeting the main protease (Mpro) of the virus. Materials & methods: We have employed an innovative strategy – application of ligand- and structure-based virtual screening – using a special compilation of an approved and diverse set of SARS-CoV-2 crystallographic complexes that was recently published. Results and conclusion: We identified seven drugs with different original indications that might act as potential Mpro inhibitors and may be preferable to other drugs that have been repurposed. These drugs will be experimentally tested to confirm their potential Mpro inhibition and thus their effectiveness against COVID-19.

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.

Allosteric Modulators of Potential Targets Related to Alzheimer's Disease: a Review

Among neurodegenerative disorders, Alzheimer's disease (AD) is the most common type of dementia, and there is an urgent need to discover new and efficacious forms of treatment for it. Pathological patterns of AD include cholinergic dysfunction, increased β-amyloid (Aβ) peptide concentration, the appearance of neurofibrillary tangles, among others, all of which are strongly associated with specific biological targets. Interactions observed between these targets and potential drug candidates in AD most often occur by competitive mechanisms driven by orthosteric ligands that sometimes result in the production of side effects. In this context, the allosteric mechanism represents a key strategy; this can be regarded as the selective modulation of such targets by allosteric modulators in an advantageous manner, as this may decrease the likelihood of side effects. The purpose of this review is to present an overview of compounds that act as allosteric modulators of the main biological targets related to AD.