Acetylcholinesterase Inhibition (Potential Anti‐Alzheimer Effects) by Aminobenzoic Acid Derivatives: Synthesis, in Vitro and in Silico Evaluation
Alzheimer's disease is a neurodegenerative condition that decreases cognitive function. Thus, intense research efforts have focused on developing acetylcholinesterase (AChE) inhibitors with less side effects. The aim of this study was to synthesize aminobenzoic acid derivatives and test their A...
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Veröffentlicht in: | ChemistrySelect (Weinheim) 2020-11, Vol.5 (44), p.14177-14182 |
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Sprache: | eng |
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Zusammenfassung: | Alzheimer's disease is a neurodegenerative condition that decreases cognitive function. Thus, intense research efforts have focused on developing acetylcholinesterase (AChE) inhibitors with less side effects. The aim of this study was to synthesize aminobenzoic acid derivatives and test their AChE inhibitory capacity in silico and in vitro. Ten electron‐poor aminobenzoic acid derivatives were synthesized in good‐high yields. Their interaction with EeAChE, according to docking simulations, is mainly mediated by the aromatic ring of the ligands and the catalytic triad of the receptor (π‐π interactions). The in vitro evaluation revealed mixed inhibition (mostly competitive) in all cases. The structural analysis showed better Ki values for heterocyclic than linear compounds and with the presence of two carboxylic groups attached. 5‐Aminoisophthalic acid (AIPA_3, KI=73 μM) showed the lowest KI of all compounds. The electron‐poor aromatic ring of the test compounds is recognized by the electron‐rich peripheric and catalytic binding sites of AChE. AIPA_3, with the best properties, is a promising lead compound for developing new AChE inhibitors.
This study comprises the design and synthesis of m‐aminobenzoic acid amide and imide derivatives, their acetylcholinesterase enzyme inhibition assays and a close explanation aided by molecular docking experiments with the aim of propose drug candidates to treat Alzheimer's Disease; resulting aminoisophthalic acid succinimide (AIPA_3) promised to be the best candidate (KI=73 μM). |
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ISSN: | 2365-6549 2365-6549 |
DOI: | 10.1002/slct.202003471 |