Identifying the Novel Pyrimidine-Based CDK2 Inhibitors as Anticancer Agents Using Text-Mining and Combined Molecular Modeling Approaches

Authors : Kader SAHİN, Serdar DURDAGI

Pages : 383-404

Doi:10.18596/jotcsa.701243

View : 12 | Download : 4

Publication Date : 2020-06-23

Article Type : Research Paper

Abstract :The cycline-dependent kinase insert ignore into journalissuearticles values(CDK); protein is an important target used in anti-cancer drug designing studies. Pyrimidine is a crucial fragment which is used in many FDA-approved drugs including anti-cancer drugs. In the current study, a small molecule database insert ignore into journalissuearticles values(Specs SC); that includes more than 210.000 compounds were used in text mining studies and 6668 molecules that carry “pyrimidine” fragments were filtered. These compounds were then screened at the binding pocket of CDK-2 target using molecular docking and molecular dynamics insert ignore into journalissuearticles values(MD); simulations approaches. Binding free energies of screened compounds were also compared with pyrimidine-based FDA approved anti-cancer drug Abemaciclib which targets CDK. Based on comparison of docking scores of screened compounds, top-7 hits were used in 100 ns MD simulations. Same MD simulations protocol insert ignore into journalissuearticles values(100 ns); were also applied to Abemaciclib-bound CDK-2 complex structure. Average Molecular Mechanics/Generalized Born Surface Area insert ignore into journalissuearticles values(MM/GBSA); energies were then calculated. Our MM/GBSA results showed that 6 out of 7 compounds have better MM/GBSA scores than FDA approved compound Abemaciclib. Thus, together with combination of text mining and integrated molecular modeling approaches, we identified novel pyrimidine-based hits against CDK.
Keywords : CDK inhibitors, , virtual screening, , text mining, molecular docking, molecular dynamics simulations