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量化用于治疗阿尔茨海默病的跨峡谷型乙酰胆碱酯酶抑制剂的配体-受体相互作用。

Quantifying ligand-receptor interactions for gorge-spanning acetylcholinesterase inhibitors for the treatment of Alzheimer's disease.

作者信息

Martis Elvis A F, Chandarana Rakesh C, Shaikh Mushtaque S, Ambre Premlata K, D'Souza Jacinta S, Iyer Krishna R, Coutinho Evans C, Nandan Santosh R, Pissurlenkar Raghuvir R S

机构信息

a Department of Pharmaceutical Chemistry , Molecular Simulations Group, Bombay College of Pharmacy , Kalina, Santacruz [E], Mumbai 400098 , India.

出版信息

J Biomol Struct Dyn. 2015;33(5):1107-25. doi: 10.1080/07391102.2014.931824. Epub 2014 Jul 11.

Abstract

There is a need for continued development of acetylcholinesterase (AChE) inhibitors that could prolong the life of acetylcholine in the synaptic cleft and also prevent the aggregation of amyloid peptides associated with Alzheimer's disease. The lack of a 3D-QSAR model which specifically deconvulates the type of interactions and quantifies them in terms of energies has motivated us to report a CoRIA model vis-à-vis the standard 3D-QSAR methods, CoMFA and CoMSIA. The CoRIA model was found to be statistically superior to the CoMFA and CoMSIA models and it could efficiently extract key residues involved in ligand recognition and binding to AChE. These interactions were quantified to gauge the magnitude of their contribution to the biological activity. In order to validate the CoRIA model, a pharmacophore map was first constructed and then used to virtually screen public databases, from which novel scaffolds were cherry picked that were not present in the training set. The biological activities of these novel molecules were then predicted by the CoRIA, CoMFA, and CoMSIA models. The hits identified were purchased and their biological activities were measured by the Ellman's method for AChE inhibition. The predicted activities are in unison with the experimentally measured biological activities.

摘要

需要持续开发乙酰胆碱酯酶(AChE)抑制剂,这类抑制剂能够延长乙酰胆碱在突触间隙中的存在时间,还能防止与阿尔茨海默病相关的淀粉样肽聚集。缺乏一种能够具体解析相互作用类型并根据能量对其进行量化的3D-QSAR模型,促使我们报告一种相对于标准3D-QSAR方法(CoMFA和CoMSIA)的CoRIA模型。结果发现,CoRIA模型在统计学上优于CoMFA和CoMSIA模型,并且它能够有效提取参与配体识别和与AChE结合的关键残基。对这些相互作用进行了量化,以衡量它们对生物活性贡献的大小。为了验证CoRIA模型,首先构建了药效团图谱,然后用于虚拟筛选公共数据库,从中挑选出训练集中不存在的新型骨架。然后通过CoRIA、CoMFA和CoMSIA模型预测这些新型分子的生物活性。购买了所鉴定的命中化合物,并通过Ellman法测量它们对AChE抑制的生物活性。预测活性与实验测量的生物活性一致。

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