Rani Neetu, Kumar Pravir
Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University (Formerly DCE), Shahbad Daulatpur, Bawana Road, Delhi, 110042, India.
Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, Delhi, 110042, India.
Mol Biotechnol. 2024 Aug 29. doi: 10.1007/s12033-024-01258-8.
CDK4 is a member of the serine-threonine kinase family, which has been found to be overexpressed in a plethora of studies related to neurodegenerative diseases. CDK4 is one of the most validated therapeutic targets for neurodegenerative diseases. Hence, the discovery of potent inhibitors of CDK4 is a promising candidate in the drug discovery field. Firstly, the reference drug Palbociclib was identified from the available literature as a potential candidate against target CDK4. In the present study, the Collection of Open Natural Products (COCONUT) database was accessed for determining potential CDK4 inhibitors using computational approaches based on the Tanimoto algorithm for similarity with the target drug, i.e., Palbociclib. The potential candidates were analyzed using SWISSADME, and the best candidates were filtered based on Lipinski's Rule of 5, Brenk, blood-brain barrier permeability, and Pains parameter. Further, the molecular docking protocol was accessed for the filtered compounds to anticipate the CDK4-ligand binding score, which was validated by the fastDRH web-based server. Based on the best docking score so obtained, the best four natural compounds were chosen for further molecular dynamic simulation to assess their stability with CDK4. In this study, two natural products, with COCONUT Database compound ID-CNP0396493 and CNP0070947, have been identified as the most suitable candidates for neuroprotection.
细胞周期蛋白依赖性激酶4（CDK4）是丝氨酸 - 苏氨酸激酶家族的成员，在大量与神经退行性疾病相关的研究中已发现其表达上调。CDK4是神经退行性疾病中最经证实的治疗靶点之一。因此，发现有效的CDK4抑制剂是药物研发领域一个有前景的候选方向。首先，从现有文献中确定参考药物帕博西尼作为针对靶点CDK4的潜在候选药物。在本研究中，访问了开放天然产物集（COCONUT）数据库，使用基于与目标药物（即帕博西尼）相似性的Tanimoto算法的计算方法来确定潜在的CDK4抑制剂。使用SWISSADME对潜在候选物进行分析，并根据Lipinski的五规则、Brenk、血脑屏障通透性和PAINS参数筛选出最佳候选物。此外，对筛选出的化合物进行分子对接实验，以预测CDK4 - 配体结合分数，并通过基于网络的fastDRH服务器进行验证。基于由此获得的最佳对接分数，选择最佳的四种天然化合物进行进一步的分子动力学模拟，以评估它们与CDK4的稳定性。在本研究中，两种天然产物，其COCONUT数据库化合物ID分别为CNP0396493和CNP0070947，已被确定为神经保护的最合适候选物。
