对Meinox小分子文库的筛选能够鉴定出病理特征不同的癌症中的抗癌化合物。

Screening of the small molecule library of Meinox enables the identification of anticancer compounds in pathologically distinct cancers.

作者信息

Mammadova Aynura, Mermer Arif, Kocabaş Fatih

机构信息

Department of Genetics and Bioengineering, Faculty of Engineering, Yeditepe University, İstanbul Turkey.

University of Strasbourg CNRS France.

出版信息

Turk J Biol. 2021 Oct 18;45(5):633-643. doi: 10.3906/biy-2104-14. eCollection 2021.

Abstract

Small molecules are widely used for the modulation of the molecular basis of diseases. This makes them the perfect tool for discovering and developing new therapeutics. In this work, we have established a library of small molecules in house and characterized its molecular and druglike properties. We have shown that most small molecules have molecular weights less than 450. They have pharmaceutically relevant cLogP, cLogS, and druglikeness value distributions. In addition, Meinox's small molecule library contained small molecules with polar surface areas that are less than 60 square angstroms, suggesting their potent ability to cross the blood-brain barrier. Meinox's small molecule library was also tested in vitro for pathologically distinct forms of cancer, including pancreatic adenocarcinoma PANC1, breast carcinoma MCF7, and lymphoblastic carcinoma RS4-11 cell lines. Analysis of this library at a dose of 1 μM allowed the discovery of potent, specific or broadly active anticancer compounds against pathologically distinct cancers. This study shows that in vitro analysis of different cancers or other phenotypic assays with Meinox small molecule library may generate novel and potent bioassay-specific compounds.

摘要

小分子被广泛用于调节疾病的分子基础。这使其成为发现和开发新疗法的理想工具。在这项工作中,我们在内部建立了一个小分子文库,并对其分子和类药性质进行了表征。我们已经表明,大多数小分子的分子量小于450。它们具有与药学相关的cLogP、cLogS和类药性值分布。此外,Meinox的小分子文库包含极性表面积小于60平方埃的小分子,这表明它们具有很强的穿越血脑屏障的能力。Meinox的小分子文库还在体外针对病理上不同形式的癌症进行了测试,包括胰腺腺癌PANC1、乳腺癌MCF7和淋巴细胞癌RS4-11细胞系。以1μM的剂量对该文库进行分析,发现了针对病理上不同癌症的强效、特异性或广泛活性的抗癌化合物。这项研究表明,用Meinox小分子文库对不同癌症进行体外分析或进行其他表型分析可能会产生新的、强效的生物测定特异性化合物。

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