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旧药新用:利用高通量半自动筛选平台鉴定具有抗肥胖作用的化合物。

A new use for old drugs: identifying compounds with an anti-obesity effect using a high through-put semi-automated screening platform.

作者信息

Haerkens Freek, Kikken Charlotte, Kirkels Laurens, van Amstel Monique, Wouters Willemijn, van Doornmalen Els, Francke Christof, Hughes Samantha

机构信息

BioCentre, HAN University of Applied Sciences, 6525EM, Nijmegen, the Netherlands.

Now at the Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 AJ, Nijmegen, the Netherlands.

出版信息

Heliyon. 2022 Aug 11;8(8):e10108. doi: 10.1016/j.heliyon.2022.e10108. eCollection 2022 Aug.

Abstract

Obesity is one of the most common global health problems for all age groups with obese people at risk of a variety of associated health complications. Consequently, there is a need to develop new therapies that lower body fat without the side effects. However, obesity is a complex and systemic disease, so that results are not easily translatable to clinical situations. A promising way to circumnavigate these issues is to reposition already approved drugs for new treatments, enabling a more streamlined drug discovery process due to the availability of pre-existing pharmacological and toxicological datasets. Chemical libraries, such as the Prestwick Chemical Library of 1200 FDA approved drugs, are available for this purpose. We have developed a simple semi-automated whole-organism approach to screening the Prestwick Chemical Library for those compounds which reduce fat content using the model organism . Our whole-organism approach to high-throughput screening identified 9 "lead" compounds that reduced fat within 2 weeks in the model. Further screening and analysis provided 4 "hit" compounds (Midodrine, Vinpocetine, Fenoprofen and Lamivudine) that showed significant promise as drugs to reduce fat levels. The effects of these candidates were found to further reduce fat content in nematodes where an /PPAR mutation resulted in "overweight" worms. Upon unblinding the "hit" compounds, they were found to have recently been shown to have anti-obesity effects in mammalian models too. In developing a whole-animal chemical screen to identify pharmacological agents as potential anti-obesity compounds, we demonstrate how chemical libraries can be rapidly and relatively cheaply profiled for active hits. Using the nematode thus enables drugs to be assessed for applicability in humans and provides a new incentive to explore drug repurposing as a feasible and efficient way to identify new anti-obesity compounds.

摘要

肥胖是所有年龄组中最常见的全球健康问题之一,肥胖者有患各种相关健康并发症的风险。因此,需要开发新的疗法来降低体脂且无副作用。然而,肥胖是一种复杂的全身性疾病,因此研究结果不易转化为临床应用。规避这些问题的一个有前景的方法是重新定位已获批药物用于新的治疗,由于已有药理学和毒理学数据集,这使得药物发现过程更加简化。化学文库,如包含1200种FDA批准药物的普雷斯蒂克化学文库,可用于此目的。我们开发了一种简单的半自动化全生物体方法,使用模式生物在普雷斯蒂克化学文库中筛选那些能降低脂肪含量的化合物。我们的全生物体高通量筛选方法确定了9种“先导”化合物,它们在模型中能在2周内降低脂肪。进一步的筛选和分析提供了4种“命中”化合物(米多君、长春西汀、非诺洛芬和拉米夫定),它们作为降低脂肪水平的药物显示出巨大潜力。发现这些候选化合物的作用能进一步降低线虫中的脂肪含量,在这些线虫中,/PPAR突变导致线虫“超重”。在揭晓“命中”化合物后,发现它们最近在哺乳动物模型中也显示出抗肥胖作用。在开发一种全动物化学筛选以鉴定作为潜在抗肥胖化合物的药理剂时,我们展示了如何快速且相对廉价地对化学文库进行活性命中分析。使用线虫从而能够评估药物在人类中的适用性,并为探索药物重新利用作为鉴定新的抗肥胖化合物的可行且有效方法提供了新的动力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac36/9399480/cab70dfc3819/gr1.jpg

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