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基于机器学习和转录组的药物重定位方法鉴定黑色素浓缩激素受体1(MCHR1)拮抗剂及其新适应症

Identification and New Indication of Melanin-Concentrating Hormone Receptor 1 (MCHR1) Antagonist Derived from Machine Learning and Transcriptome-Based Drug Repositioning Approaches.

作者信息

Lim Gyutae, You Ka Young, Lee Jeong Hyun, Jeon Moon Kook, Lee Byung Ho, Ryu Jae Yong, Oh Kwang-Seok

机构信息

Data Convergence Drug Research Center, Korea Research Institute of Chemical Technology, 141 Gajeong-ro, Yuseong-gu, Daejeon 34114, Korea.

Graduate School of New Drug Discovery and Development, Chungnam National University, Daejeon 34134, Korea.

出版信息

Int J Mol Sci. 2022 Mar 30;23(7):3807. doi: 10.3390/ijms23073807.

Abstract

Melanin-concentrating hormone receptor 1 (MCHR1) has been a target for appetite suppressants, which are helpful in treating obesity. However, it is challenging to develop an MCHR1 antagonist because its binding site is similar to that of the human Ether-à-go-go-Related Gene (hERG) channel, whose inhibition may cause cardiotoxicity. Most drugs developed as MCHR1 antagonists have failed in clinical development due to cardiotoxicity caused by hERG inhibition. Machine learning-based prediction models can overcome these difficulties and provide new opportunities for drug discovery. In this study, we identified KRX-104130 with potent MCHR1 antagonistic activity and no cardiotoxicity through virtual screening using two MCHR1 binding affinity prediction models and an hERG-induced cardiotoxicity prediction model. In addition, we explored other possibilities for expanding the new indications for KRX-104130 using a transcriptome-based drug repositioning approach. KRX-104130 increased the expression of low-density lipoprotein receptor (LDLR), which induced cholesterol reduction in the gene expression analysis. This was confirmed by comparison with gene expression in a nonalcoholic steatohepatitis (NASH) patient group. In a NASH mouse model, the administration of KRX-104130 showed a protective effect by reducing hepatic lipid accumulation, liver injury, and histopathological changes, indicating a promising prospect for the therapeutic effect of NASH as a new indication for MCHR1 antagonists.

摘要

黑色素浓缩激素受体1(MCHR1)一直是食欲抑制剂的作用靶点,这类抑制剂有助于治疗肥胖症。然而,开发MCHR1拮抗剂具有挑战性,因为其结合位点与人类醚 - 去极化相关基因(hERG)通道的结合位点相似,抑制该通道可能会导致心脏毒性。大多数作为MCHR1拮抗剂开发的药物由于hERG抑制引起的心脏毒性而在临床开发中失败。基于机器学习的预测模型可以克服这些困难,并为药物发现提供新的机会。在本研究中,我们通过使用两个MCHR1结合亲和力预测模型和一个hERG诱导的心脏毒性预测模型进行虚拟筛选,鉴定出具有强大MCHR1拮抗活性且无心脏毒性的KRX - 104130。此外,我们使用基于转录组的药物重新定位方法探索了扩展KRX - 104130新适应症的其他可能性。在基因表达分析中,KRX - 104130增加了低密度脂蛋白受体(LDLR)的表达,从而导致胆固醇降低。通过与非酒精性脂肪性肝炎(NASH)患者组的基因表达进行比较,这一点得到了证实。在NASH小鼠模型中,给予KRX - 104130通过减少肝脏脂质积累、肝损伤和组织病理学变化显示出保护作用,这表明作为MCHR1拮抗剂的新适应症,KRX - 104130对NASH的治疗效果具有广阔前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f5b/8998904/aebaef083d43/ijms-23-03807-g001.jpg

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