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Janus 激酶 1 和 3(JAK1/3)双重抑制剂的推测:基于药效团的层次虚拟筛选。

Putative dual inhibitors of Janus kinase 1 and 3 (JAK1/3): Pharmacophore based hierarchical virtual screening.

机构信息

Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab, 147002, India.

Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab, 147002, India.

出版信息

Comput Biol Chem. 2018 Oct;76:109-117. doi: 10.1016/j.compbiolchem.2018.07.009. Epub 2018 Jul 5.

Abstract

Janus kinase 1 and 3 are non-receptor protein tyrosine kinases, involved in the regulation of various cytokines implicated in the pathogenesis of autoimmune and inflammatory disease conditions. Thus, they serve as therapeutic targets for the designing of multi-targeted agents for the treatment of inflammatory-mediated pathological conditions. In the present study, diverse inhibitors of JAK1 and JAK3 were considered for the development of ligand-based pharmacophore models, followed by docking analysis to design putative dual inhibitors. The pharmacophore models were generated in PHASE 3.4, and top five models for each target were selected on the basis of survival minus inactive score. The best model for JAK1 (AAADH.25) and JAK3 (ADDRR.142) were selected corresponding to the highest value of Q. Both models were employed for the screening of a PHASE database, and subsequently, the retrieved hits were filtered employing molecular docking in JAK1 and JAK3 proteins. The stable interactions between retrieved hits and proteins were confirmed using molecular dynamics simulations. Finally, ADME properties of screened dual inhibitors displaying essential interactions with both proteins were calculated. Thus, the new leads obtained in this way may be prioritized for experimental validation as potential novel therapeutic agents in the treatment of various autoimmune and inflammatory disorders related to JAK1 and JAK3.

摘要

Janus 激酶 1 和 3 是非受体蛋白酪氨酸激酶,参与调节多种细胞因子,这些细胞因子与自身免疫和炎症性疾病的发病机制有关。因此,它们可作为设计用于治疗炎症介导的病理状况的多靶向药物的治疗靶点。在本研究中,考虑了多种 JAK1 和 JAK3 的抑制剂,用于开发基于配体的药效团模型,然后进行对接分析以设计可能的双重抑制剂。药效团模型在 PHASE 3.4 中生成,每个靶标选择生存减去非活性评分最高的五个模型。针对 JAK1(AAADH.25)和 JAK3(ADDRR.142)的最佳模型分别对应于 Q 值的最高值。这两个模型都用于 PHASE 数据库的筛选,随后,使用 JAK1 和 JAK3 蛋白中的分子对接筛选检索到的命中。通过分子动力学模拟确认检索到的命中与蛋白质之间的稳定相互作用。最后,计算了与两种蛋白质均显示出必需相互作用的筛选出的双重抑制剂的 ADME 特性。因此,以这种方式获得的新先导物可能会被优先进行实验验证,作为治疗与 JAK1 和 JAK3 相关的各种自身免疫和炎症性疾病的潜在新型治疗剂。

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