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• W4387563746 abstract "Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease's onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our in-silico study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer's and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer's drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer's treatment. Further in vitro and in vivo studies are warranted to explore these findings.Communicated by Ramaswamy H. Sarma." @default.
• W4387563746 created "2023-10-13" @default.
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• W4387563746 date "2023-10-11" @default.
• W4387563746 modified "2023-10-13" @default.
• W4387563746 title "<i>In silico</i> identification of colchicine derivatives as novel and potential inhibitors based on molecular docking and dynamic simulations targeting multifactorial drug targets involved in Alzheimer’s disease" @default.
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• W4387563746 doi "https://doi.org/10.1080/07391102.2023.2263586" @default.
• W4387563746 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37822182" @default.
• W4387563746 hasPublicationYear "2023" @default.
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