In silico study suggests potential drugs that target CD151 to treat breast cancer and glioblastoma

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of Computational Chemistry Pub Date : 2024-07-31 DOI:10.1002/jcc.27439
Gema Ramírez-Salinas, Martha Cecilia Rosales-Hernandéz, José Correa-Basurto, Issac Guerrero-González, Selene Saraí Hernández-Castro, Marlet Martinez-Archundia
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Abstract

Recently tetraspanin CD151 has been identified as an important biological target involved in metastatic processes which include cell adhesion, tumor progression processes, and so forth in different types of cancers, such as breast cancer and glioblastoma. This in Silico study considered 1603 compounds from the Food and Drug Administration database, after performing an ADMET analysis; we selected 853 ligands, which were used for docking analysis. The most promising ligands were selected from docking studies, based on two criteria: (a) showed lowest affinity to the CD151 protein and (b) they interact with the QRD motif, located in the second extracellular loop. Furthermore, we investigate the stability of the protein-ligand complexes through MD simulations as well as free energy MM-PBSA calculations. From these results, loperamide and glipizide were identified as the best evaluated drugs. We suggest an in vitro analysis is needed to confirm our in silico prediction studies.

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硅学研究提出了以 CD151 为靶点治疗乳腺癌和脂肪母细胞瘤的潜在药物。
最近,人们发现四泛素 CD151 是一个重要的生物靶点,它参与了不同类型癌症(如乳腺癌和胶质母细胞瘤)的转移过程,包括细胞粘附、肿瘤进展过程等。这项硅学研究考虑了食品与药物管理局数据库中的 1603 种化合物,在进行 ADMET 分析后,我们选择了 853 种配体,并对其进行了对接分析。根据两个标准,我们从对接研究中选出了最有前景的配体:(a) 与 CD151 蛋白的亲和力最低;(b) 与位于细胞外第二环的 QRD 基序相互作用。此外,我们还通过 MD 模拟以及自由能 MM-PBSA 计算研究了蛋白质配体复合物的稳定性。根据这些结果,洛哌丁胺和格列吡嗪被确定为评估结果最好的药物。我们建议需要进行体外分析来证实我们的硅学预测研究。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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