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结合代谢稳定性和肽功能的愿望函数。

Desirability function combining metabolic stability and functionality of peptides.

机构信息

Drug Quality and Registration (DruQuaR) Group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.

出版信息

J Pept Sci. 2011 May;17(5):398-404. doi: 10.1002/psc.1323. Epub 2011 Feb 4.

Abstract

The evaluation of peptides as potential therapeutic or diagnostic agents requires the consideration of several criteria that are targeted around two axes: functionality and metabolic stability. Most often, a compromise has to be made between these mutually opposing characteristics. In this study, Derringer's desirability function, a multi-criteria decision-making method, was applied to determine the best peptide for opioid studies in a single figure-of-merit. The penetration of the blood-brain barrier (BBB) determines the biological functionality of neuropeptides in the brain target tissue, and consists of an influx and an efflux component. The metabolic stability in the two concerned tissues, i.e. plasma and brain, are taken into consideration as well. The overall selection of the peptide drug candidate having the highest BBB-drugability is difficult due to these conflicting responses as well as the different scalings of the four biological parameters under consideration. The highest desirability, representing the best BBB-drugability, was observed for dermorphin. This peptide is thus the most promising drug candidate from the set of eight opioid peptides that were investigated. The least desirable candidate, with the worst BBB influx and/or metabolic stability, was found to be CTAP. Validation of the desirability function by in vivo medical imaging showed that dermorphin and DAMGO penetrate the BBB, whereas EM-1 and TAPP did not. These results are thus consistent with those obtained with the desirability evaluation. To conclude, the multi-criteria decision method was proven to be useful in biomedical research, where a selection of the best candidate based on opposing characteristics is often required.

摘要

评估肽类作为潜在治疗或诊断剂需要考虑几个标准,这些标准围绕两个轴:功能和代谢稳定性。通常,这两个相互对立的特征之间必须做出妥协。在这项研究中,Derringer 的理想性函数,一种多标准决策方法,被应用于在单一综合指标中确定用于阿片类研究的最佳肽。血脑屏障 (BBB) 的穿透性决定了神经肽在大脑靶组织中的生物学功能,它由内流和外流两部分组成。还考虑了在两个相关组织(即血浆和大脑)中的代谢稳定性。由于这些相互矛盾的反应以及所考虑的四个生物学参数的不同标度,很难选择具有最高 BBB 可穿透性的肽类候选药物。具有最高理想性的药物(代表最佳的 BBB 可穿透性)是 Dermorphin。因此,与研究的八种阿片肽相比,这种肽是最有前途的候选药物。具有最差 BBB 内流和/或代谢稳定性的最不理想的候选药物是 CTAP。通过体内医学成像验证理想函数,发现 Dermorphin 和 DAMGO 穿透了 BBB,而 EM-1 和 TAPP 没有。因此,这些结果与通过理想性评估获得的结果一致。总之,多标准决策方法已被证明在生物医学研究中非常有用,在这种研究中,通常需要根据对立特征选择最佳候选物。

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