Steindl Theodora, Laggner Christian, Langer Thierry
Institute of Pharmacy, Computer Aided Molecular Design Group, University of Innsbruck, Innrain 52, A-6020 Innsbruck, Austria.
J Chem Inf Model. 2005 May-Jun;45(3):716-24. doi: 10.1021/ci049638a.
Three-dimensional pharmacophore models for peptidic and small organic nonpeptidic inhibitors of the human rhinovirus 3C protease were generated in a structure-based as well as in a ligand-based approach, using the software package Catalyst. The inhibitors possess an electrophilic moiety, often a Michael acceptor function, which covalently binds to a cysteine in the active site of the enzyme. Since this process presents the key step for virus inactivation, the creation of a new function in Catalyst was required in order to include this decisive functionality into the pharmacophore models. In the present study we focus on this feature definition process because it presents an innovative strategy to expand the pharmacophore description ability of the Catalyst software to also include covalent bonds between ligand and binding site. The resulting hypotheses were then used for virtual screening of 3D databases in order to verify their quality and to search for structurally diverse, possible new lead substances.
使用Catalyst软件包,通过基于结构和基于配体的方法,生成了针对人鼻病毒3C蛋白酶的肽类和小型有机非肽类抑制剂的三维药效团模型。这些抑制剂具有亲电部分,通常是迈克尔受体功能,它与酶活性位点中的半胱氨酸共价结合。由于这一过程是病毒失活的关键步骤,因此需要在Catalyst中创建新功能,以便将这一决定性功能纳入药效团模型。在本研究中,我们专注于这一特征定义过程,因为它提出了一种创新策略,可扩展Catalyst软件的药效团描述能力,使其也能包括配体与结合位点之间的共价键。然后将所得的假设用于三维数据库的虚拟筛选,以验证其质量并寻找结构多样的可能新先导物质。