Gabrielsen Mari, Kurczab Rafał, Siwek Agata, Wolak Małgorzata, Ravna Aina W, Kristiansen Kurt, Kufareva Irina, Abagyan Ruben, Nowak Gabriel, Chilmonczyk Zdzisław, Sylte Ingebrigt, Bojarski Andrzej J
Medical Pharmacology and Toxicology, Department of Medical Biology, Faculty of Health Sciences, UiT, The Arctic University of Norway , 9037 Tromsø, Norway.
J Chem Inf Model. 2014 Mar 24;54(3):933-43. doi: 10.1021/ci400742s. Epub 2014 Feb 26.
The serotonin (5-hydroxytryptamine, 5-HT) transporter (SERT) plays an essential role in the termination of serotonergic neurotransmission by removing 5-HT from the synaptic cleft into the presynaptic neuron. It is also of pharmacological importance being targeted by antidepressants and psychostimulant drugs. Here, five commercial databases containing approximately 3.24 million drug-like compounds have been screened using a combination of two-dimensional (2D) fingerprint-based and three-dimensional (3D) pharmacophore-based screening and flexible docking into multiple conformations of the binding pocket detected in an outward-open SERT homology model. Following virtual screening (VS), selected compounds were evaluated using in vitro screening and full binding assays and an in silico hit-to-lead (H2L) screening was performed to obtain analogues of the identified compounds. Using this multistep VS/H2L approach, 74 active compounds, 46 of which had K(i) values of ≤1000 nM, belonging to 16 structural classes, have been identified, and multiple compounds share no structural resemblance with known SERT binders.
血清素(5-羟色胺,5-HT)转运体(SERT)通过将5-HT从突触间隙转运到突触前神经元,在血清素能神经传递的终止过程中发挥着至关重要的作用。它在药理学上也具有重要意义,是抗抑郁药和精神兴奋药物的作用靶点。在此,我们使用基于二维(2D)指纹和基于三维(3D)药效团的筛选相结合的方法,并对向外开放的SERT同源模型中检测到的结合口袋的多种构象进行灵活对接,对五个包含约324万种类药物化合物的商业数据库进行了筛选。经过虚拟筛选(VS)后,使用体外筛选和完全结合试验对选定的化合物进行评估,并进行了计算机辅助的从命中到先导(H2L)筛选,以获得已鉴定化合物的类似物。使用这种多步骤的VS/H2L方法,已鉴定出74种活性化合物,其中46种的K(i)值≤1000 nM,属于16个结构类别,并且多种化合物与已知的SERT结合剂没有结构相似性。