4.7 Article

Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations

Journal

BIOMEDICINES
Volume 9, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/biomedicines9091197

Keywords

CDK7; cancer; pharmacophore; molecular docking; MD simulation; MM-PBSA; pharmacokinetic properties

Funding

  1. Neurological Disorder Research Program of the National Research Foundation (NRF) - Korean Government (MSIT) [2020M3E5D9080660]
  2. National Research Foundation of Korea [2020M3E5D9080660] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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CDK7 plays a critical role in regulating cell cycle and RNA polymerase-based transcription, and its overexpression is associated with cancer. Through a pharmacophore-based approach, potential hit compounds against CDK7 were identified, with molecular docking and dynamics simulations showing promising binding affinity. The hits exhibit better binding affinity and pharmacokinetic properties compared to established CDK7 inhibitors, suggesting their potential importance in combating CDK7-related malignancies.
The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits-ZINC20392430, SN00112175, SN00004718, and SN00262261-having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.

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