Bis-Amiridines as Acetylcholinesterase and Butyrylcholinesterase Inhibitors: N-Functionalization Determines the Multitarget Anti-Alzheimer’s Activity Profile

Morphing cholinesterase inhibitor amiridine into multipotent drugs for the treatment of Alzheimer's disease

The search for novel drugs to address the medical needs of Alzheimer's disease (AD) is an ongoing process relying on the discovery of disease-modifying agents. Given the complexity of the disease, such an aim can be pursued by developing so-called multi-target directed ligands (MTDLs) that will impact the disease pathophysiology more comprehensively. Herewith, we contemplated the therapeutic efficacy of an amiridine drug acting as a cholinesterase inhibitor by converting it into a novel class of novel MTDLs. Applying the linking approach, we have paired amiridine as a core building block with memantine/adamantylamine, trolox, and substituted benzothiazole moieties to generate novel MTDLs endowed with additional properties like N-methyl-d-aspartate (NMDA) receptor affinity, antioxidant capacity, and anti-amyloid properties, respectively. The top-ranked amiridine-based compound 5d was also inspected by in silico to reveal the butyrylcholinesterase binding differences with its close structural analogue 5b. Our study provides insight into the discovery of novel amiridine-based drugs by broadening their target-engaged profile from cholinesterase inhibitors towards MTDLs with potential implications in AD therapy.

A comprehensive review of multi-target directed ligands in the treatment of Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia affecting specifically older population. AD is an irreversible neurodegenerative CNS disorder associated with complex pathophysiology. Presently, the USFDA has approved only four drugs viz. Donepezil, Rivastigmine, Memantine, and Galantamine for the treatment of AD. These drugs exhibit their neuroprotective effects either by inhibiting cholinesterase enzyme (ChE) or N-methyl-d-aspartate (NMDA) receptor. However, the conventional therapy "one target, one molecule" has failed to provide promising therapeutic effects due to the multifactorial nature of AD. This triggered the development of a novel strategy called Multi-Target Directed Ligand (MTDL) which involved designing one molecule that acts on multiple targets simultaneously. The present review discusses the detailed pathology involved in AD and the various MTDL design strategies bearing different heterocycles, in vitro and in vivo activities of the compounds, and their corresponding structure-activity relationships. This knowledge will allow us to identify and design more effective MTDLs for the treatment of AD.

Conjugates of amiridine and thiouracil derivatives as effective inhibitors of butyrylcholinesterase with the potential to block β-amyloid aggregation

New amiridine-thiouracil conjugates with different substituents in the pyrimidine fragment (R = CH3 , CF2 Н, CF3 , (CF2 )2 H) and different spacer lengths (n = 1-3) were synthesized. The conjugates rather weakly inhibit acetylcholinesterase (AChE) and exhibit high inhibitory activity (IC50 up to 0.752 ± 0.021 µM) and selectivity to butyrylcholinesterase (BChE), which increases with spacer elongation; the lead compounds are 11c, 12c, and 13c. The conjugates are mixed-type reversible inhibitors of both cholinesterases and practically do not inhibit the structurally related off-target enzyme carboxylesterase. The results of molecular docking to AChE and BChE are consistent with the experiment on enzyme inhibition and explain the structure-activity relationships, including the rather low anti-AChE activity and the high anti-BChE activity of long-chain conjugates. The lead compounds displace propidium from the AChE peripheral anion site (PAS) at the level of the reference compound donepezil, which agrees with the mixed-type mechanism of AChE inhibition and the main mode of binding of conjugates in the active site of AChE due to the interaction of the pyrimidine moiety with the PAS. This indicates the ability of the studied conjugates to block AChE-induced aggregation of β-amyloid, thereby exerting a disease-modifying effect. According to computer calculations, all synthesized conjugates have an ADME profile acceptable for drugs.

Machine Learning Prediction of Mycobacterial Cell Wall Permeability of Drugs and Drug-like Compounds

The cell wall of Mycobacterium tuberculosis and related organisms has a very complex and unusual organization that makes it much less permeable to nutrients and antibiotics, leading to the low activity of many potential antimycobacterial drugs against whole-cell mycobacteria compared to their isolated molecular biotargets. The ability to predict and optimize the cell wall permeability could greatly enhance the development of novel antitubercular agents. Using an extensive structure-permeability dataset for organic compounds derived from published experimental big data (5371 compounds including 2671 penetrating and 2700 non-penetrating compounds), we have created a predictive classification model based on fragmental descriptors and an artificial neural network of a novel architecture that provides better accuracy (cross-validated balanced accuracy 0.768, sensitivity 0.768, specificity 0.769, area under ROC curve 0.911) and applicability domain compared with the previously published results.