Ullah Hanif, Zhang Baoyun, Sharma Narendra Kumar, McCrea Pierre D, Srivastava Yogesh
Guangxi Key Laboratory for Genomics and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomics and Personalized Medicine, Guangxi Medical University, Nanning, China.
Key Laboratory of Regenerative Biology, South China Institute for Stem Cell Biology and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.
Front Mol Biosci. 2022 Aug 25;9:981020. doi: 10.3389/fmolb.2022.981020. eCollection 2022.
The molecular consequences of cancer associated mutations in Acute myeloid leukemia (AML) linked factors are not very well understood. Here, we interrogated the COSMIC database for missense mutations associated with the RUNX1 protein, that is frequently mis-regulated in AML, where we sought to identify recurrently mutated positions at the DNA-interacting interface. Indeed, six of the mutated residues, out of a total 417 residues examined within the DNA binding domain, evidenced reduced DNA association in predictions. Further, given the prominence of RUNX1's compromised function in AML, we asked the question if the mutations themselves might alter RUNX1's interaction (off-target) with known FDA-approved drug molecules, including three currently used in treating AML. We identified several AML-associated mutations in RUNX1 that were calculated to enhance RUNX1's interaction with specific drugs. Specifically, we retrieved data from the COSMIC database for cancer-associated mutations of RUNX1 by using R package "data.table" and "ggplot2" modules. In the presence of DNA and/or drug, we used docking scores and energetics of the complexes as tools to evaluate predicted interaction strengths with RUNX1. For example, we performed predictions of drug binding pockets involving Enasidenib, Giltertinib, and Midostaurin (AML associated), as well as ten different published cancer associated drug compounds. Docking of wild type RUNX1 with these 13 different cancer-associated drugs indicates that wild-type RUNX1 has a lower efficiency of binding while RUNX1 mutants R142K, D171N, R174Q, P176H, and R177Q suggested higher affinity of drug association. Literature evidence support our prediction and suggests the mutation R174Q affects RUNX1 DNA binding and could lead to compromised function. We conclude that specific RUNX1 mutations that lessen DNA binding facilitate the binding of a number of tested drug molecules. Further, we propose that molecular modeling and docking studies for RUNX1 in the presence of DNA and/or drugs enables evaluation of the potential impact of RUNX1 cancer associated mutations in AML.
急性髓系白血病（AML）相关因子中与癌症相关的突变所产生的分子后果尚未得到很好的理解。在此，我们在COSMIC数据库中查询了与RUNX1蛋白相关的错义突变，RUNX1蛋白在AML中经常发生调控异常，我们试图在DNA相互作用界面识别出反复发生突变的位点。确实，在DNA结合域内总共检测的417个残基中，有6个突变残基在预测中显示出与DNA的结合减少。此外，鉴于RUNX1功能受损在AML中的突出性，我们提出一个问题，即这些突变本身是否可能改变RUNX1与已知FDA批准的药物分子的相互作用（脱靶），包括目前用于治疗AML的三种药物。我们在RUNX1中鉴定出几个与AML相关的突变，经计算这些突变会增强RUNX1与特定药物的相互作用。具体而言，我们使用R包“data.table”和“ggplot2”模块从COSMIC数据库中检索RUNX1的癌症相关突变数据。在存在DNA和/或药物的情况下，我们使用复合物的对接分数和能量学作为工具来评估与RUNX1预测的相互作用强度。例如，我们对涉及恩杂鲁胺、吉瑞替尼和米哚妥林（与AML相关）以及十种不同的已发表的癌症相关药物化合物的药物结合口袋进行了预测。野生型RUNX1与这13种不同的癌症相关药物的对接表明，野生型RUNX1的结合效率较低，而RUNX1突变体R142K、D171N、R174Q、P176H和R177Q显示出更高的药物结合亲和力。文献证据支持我们的预测，并表明R174Q突变会影响RUNX1与DNA的结合，并可能导致功能受损。我们得出结论，减少DNA结合的特定RUNX1突变会促进许多测试药物分子的结合。此外，我们提出在存在DNA和/或药物的情况下对RUNX1进行分子建模和对接研究，能够评估RUNX1癌症相关突变在AML中的潜在影响。
