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虚拟筛选与分子对接:发现新型 c-KIT 抑制剂。

Virtual Screening and Molecular Docking: Discovering Novel c-KIT Inhibitors.

机构信息

Post graduate Program in Health Sciences, University of Western São Paulo (UNOESTE), Presidente Prudente, SP,Brazil.

Post graduate Program in Environmental and Regional Development Studies, University of Western São Paulo (UNOESTE) Presidente Prudente, SP,Brazil.

出版信息

Curr Med Chem. 2022;29(2):166-188. doi: 10.2174/0929867328666210915102920.

Abstract

Gastrointestinal stromal tumors (GISTs) are unusual cancers, which are developed in specialized cells in the gastrointestinal tract wall. Various strategies involving single-agents, combinations, and rapid complementary inhibitor cycling are now being used to control such tumors. Based on promising early clinical trial experience, certain novel KIT and PDGFRA tyrosine kinase inhibitors have shown advanced clinical development. Resistance to tyrosine kinase inhibitors has brought immense difficulties, with patients now requiring additional therapeutic options. This review describes and discusses the last five years (2016-2020) in developing novel c-KIT kinase inhibitors using virtual screening and docking approaches. Computational techniques can be used to complement experimental studies to identify new candidate molecules for therapeutic use. Molecular modeling strategies allow the analysis of the required characteristics that compounds must have to effectively bind c-KIT. Through such analyses, it is possible to both discover and design novel inhibitors against cancer-related proteins that play a critical role in tumor development (including mutant strains). Docking showed potential in the detection of the key residues responsible for ligand recognition and is very helpful to understand the interactions in the active site that can be used to develop new compounds/classes of anticancer drugs and help millions of cancer patients.

摘要

胃肠道间质瘤(GISTs)是一种不常见的癌症,它起源于胃肠道壁的特殊细胞。目前,人们正在采用各种策略来控制这些肿瘤,包括单一药物、联合用药和快速互补抑制剂循环。基于有前途的早期临床试验经验,某些新型 KIT 和 PDGFRA 酪氨酸激酶抑制剂已显示出先进的临床开发水平。对酪氨酸激酶抑制剂的耐药性带来了巨大的困难,患者现在需要更多的治疗选择。本综述描述并讨论了过去五年(2016-2020 年)使用虚拟筛选和对接方法开发新型 c-KIT 激酶抑制剂的情况。计算技术可用于补充实验研究,以鉴定用于治疗的新候选分子。分子建模策略允许分析化合物必须具有的有效结合 c-KIT 的所需特性。通过这些分析,可以发现和设计针对在肿瘤发展中起关键作用的癌症相关蛋白的新型抑制剂(包括突变株)。对接在检测负责配体识别的关键残基方面显示出了潜力,它非常有助于理解活性位点中的相互作用,这些相互作用可用于开发新的化合物/类抗癌药物,并帮助数百万癌症患者。

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