An important challenge, in the medicinal chemistry field, is the research of novel forceful drugs to overcome tumor-acquired resistance. The c-Kit tyrosine kinase receptor (TKR) represents a suitable target for the carcinogenesis control of gastro-intestinal stromal (GIST), leukemia, and mastocytosis tumors; nevertheless, several hotspot mutations of the protein limit the efficacy of a few clinical administered TKRs inhibitors. In this study, a new in silico protocol based on ligand and structure-based combined method is proposed, with the aim to identify a set of new c-Kit inhibitors able to complex c-Kit mutated proteins. A recent and freely available web-server DRUDIT is used for the ligand-based method. The protocol application allows for identifying a new generation of potential TKR inhibitors, which, in silico, complex the V654A and T670I mutated proteins and potentially overcome resistant mutations (D816H). The structure-based analysis is performed by Induced Fit Docking (IFD) studies. The comparison between the explored ligands and well-known drugs highlights the possibility to overcome tumor-acquired resistance. The best-selected structures (630705 and SML1348) provide valuable binding affinities with the mutated c-Kit forms (respectively T670I and V654A).

在药物化学领域中，一项重要的挑战是研究新型有效药物以克服肿瘤获得性耐药。c-Kit酪氨酸激酶受体（TKR）代表了控制胃肠道间质（GIST），白血病和肥大细胞增多性肿瘤的致癌目标。然而，该蛋白质的几个热点突变限制了一些临床施用的TKRs抑制剂的功效。在这项研究中，提出了一种新的基于配体和基于结构的组合方法的计算机模拟方案，目的是确定一组能够使c-Kit突变蛋白复杂的新型c-Kit抑制剂。最新的和免费提供的Web服务器DRUDIT用于基于配体的方法。该协议应用程序可用于识别新一代潜在的TKR抑制剂，在计算机中，复杂化V654A和T670I突变蛋白并可能克服耐药性突变（D816H）。基于结构的分析是通过诱导拟合对接（IFD）研究进行的。探索的配体与知名药物之间的比较突出了克服肿瘤获得性耐药的可能性。最佳选择的结构（630705和SML1348）与突变的c-Kit形式（分别为T670I和V654A）提供了有价值的结合亲和力。