Rivastigmine–Sinapinic Acid Hybrid Carbamates as Multi-Target Cholinesterase/MAO-B Inhibitors: An in silico Design and ADMET Evaluation
9th International Eurasian Conference on Biological and Chemical Sciences (EurasianBioChem 2026) , Ankara, Türkiye, 19 - 21 Ekim 2026, ss.37-38, (Özet Bildiri)
- Yayın Türü: Bildiri / Özet Bildiri
- Basıldığı Şehir: Ankara
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.37-38
- Kocaeli Üniversitesi Adresli: Evet
Özet
Cholinesterase inhibition remains a cornerstone strategy for the symptomatic treatment of Alzheimer's disease (AD), a progressive neurodegenerative disorder marked by cognitive decline and memory loss linked to reduced synaptic acetylcholine levels [1,2]. As AD progresses, butyrylcholinesterase (BChE) activity increasingly compensates for diminished acetylcholinesterase (AChE) function, making selective BChE inhibition an attractive strategy that may reduce the peripheral side effects associated with non-selective inhibitors [3]. Rivastigmine, an FDA-approved carbamate-based inhibitor of both AChE and BChE, remains widely used but only manages symptoms without altering disease progression [4]. Multi-target-directed ligand (MTDL) design, combining cholinesterase inhibition with a second AD-relevant target such as monoamine oxidase-B (MAO-B), implicated in the oxidative stress accompanying AD pathology, has emerged as a promising strategy for addressing the multifactorial nature of the disease [5]. Sinapinic acid, a hydroxycinnamic acid found in cereals, fruits, and other plant sources, exhibits antioxidant, antimicrobial, anti-inflammatory, anticancer, and neuroprotective activity, and previous docking studies have shown that it interacts with AChE, supporting its use as a scaffold in this context [6,7]. Building on this, we designed a series of rivastigmine–sinapinic acid hybrid carbamates with the rationale of favoring BChE selectivity, and evaluated their inhibitory potential against AChE, BChE, and MAO-B through molecular docking, together with in silico ADMET analysis. This computational multi-target approach identified promising candidates among these hybrid carbamates and characterized their predicted pharmacokinetic and toxicity profiles.