Abstract：
Cyclin-dependent kinases 1 (CDK1) has been identified as a potential target for the search for new antitumor drugs. However, no clinically effective CDK1 inhibitors are now available for cancer treatment. Therefore, this study aimed to offer potential CDK1 inhibitors using de novo drug generation, molecular docking, and molecular dynamics (MD) simulation studies. We first utilized the BREED algorithm (a de novo drug generation approach) to produce a novel library of small molecules targeting CDK1. To initially obtain novel potential CDK1 inhibitors with favorable physicochemical properties and excellent druggability, we performed a virtual rule-based rational drug screening on our generated library and found ten initial hits. Then, the molecular interactions and dynamic stability of these ten initial hits and CDK1 complexes during their all-atom MD simulations (total 18 μs) and binding pose metadynamics simulations were investigated, resulting in five final hits. Furthermore, another MD simulation (total 2.1 μs) with different force fields demonstrated the binding ability of the five hits to CDK1. It was found that these five hits, CBMA001 (ΔG = -29.88 kcal/mol), CBMA002 (ΔG = -34.89 kcal/mol), CBMA004 (ΔG = -32.47 kcal/mol), CBMA007 (ΔG = -31.16 kcal/mol), and CBMA008 (ΔG = -34.78 kcal/mol) possessed much greater binding affinity to CDK1 than positive compound Flavopiridol (FLP, ΔG = -25.38 kcal/mol). Finally, CBMA002 and CBMA004 were identified as excellent selective CDK1 inhibitors in silico. Together, this study provides a workflow for rational drug design and two promising selective CDK1 inhibitors that deserve further investigation.
摘要：
细胞周期蛋白依赖性激酶1（CDK1）已被确定为寻找新的抗肿瘤药物的潜在靶标。然而,目前尚无临床有效的CDK1抑制剂可用于癌症治疗.因此,这项研究旨在提供潜在的CDK1抑制剂，使用从头产生药物，分子对接,和分子动力学(MD)模拟研究。我们首先利用BREED算法(从头药物生成方法)来产生靶向CDK1的新的小分子文库。初步获得具有良好理化性质和优良成药性的新型潜在CDK1抑制剂,我们对我们生成的文库进行了基于虚拟规则的合理药物筛选,发现了10个初始命中.然后，研究了这十个初始命中和CDK1复合物在其全原子MD模拟（共18μs）和结合姿态元动力学模拟过程中的分子相互作用和动态稳定性，最终命中了五次。此外，另一个具有不同力场的MD模拟（总共2.1μs）证明了五次命中对CDK1的结合能力。发现这五次点击，CBMA001（ΔG=-29.88kcal/mol），CBMA002（ΔG=-34.89kcal/mol），CBMA004(ΔG=-32.47kcal/mol),CBMA007（ΔG=-31.16kcal/mol），和CBMA008（ΔG=-34.78kcal/mol）比阳性化合物Flavopiridol（FLP，ΔG=-25.38kcal/mol)。最后,CBMA002和CBMA004在计算机上被鉴定为优异的选择性CDK1抑制剂。一起,本研究为合理的药物设计和两种有前景的选择性CDK1抑制剂提供了工作流程,值得进一步研究.
