Virtual Screening for Identification of Dual Inhibitors against CDK4/6 and Aromatase Enzyme.
Tenzin AdonDhivya ShanmugarajanHissana AtherShaik Mohammad Asif AnsariUmme HaniSubbaRao V MadhunapantulaHonnavalli Yogish KumarPublished in: Molecules (Basel, Switzerland) (2023)
CDK4/6 and aromatase are prominent targets for breast cancer drug discovery and are involved in abnormal cell proliferation and growth. Although aromatase inhibitors have proven to be effective (for example exemestane, anastrozole, letrozole), resistance to treatment eventually occurs through the activation of alternative signaling pathways, thus evading the antiproliferative effects of aromatase inhibitors. One of the evasion pathways is Cylin D-CDK4/6-Rb signaling that promotes tumor proliferation and resistance to aromatase inhibitors. There is significant evidence that the sequential inhibition of both proteins provides therapeutic benefits over the inhibition of one target. The basis of this study objective is the identification of molecules that are likely to inhibit both CDK4/6 and aromatase by computational chemistry techniques, which need further biochemical studies to confirm. Initially, a structure-based pharmacophore model was constructed for each target to screen the sc-PDB database. Consequently, pharmacophore screening and molecular docking were performed to evaluate the potential lead candidates that effectively mapped both of the target pharmacophore models. Considering abemaciclib (CDK4/6 inhibitor) and exemestane (aromatase inhibitor) as reference drugs, four potential virtual hit candidates (1, 2, 3, and 4) were selected based on their fit values and binding interaction after screening a sc-PDB database. Further, molecular dynamics simulation studies solidify the stability of the lead candidate complexes. In addition, ADMET and DFT calculations bolster the lead candidates. Hence, these combined computational approaches will provide a better therapeutic potential for developing CDK4/6-aromatase dual inhibitors for HR+ breast cancer therapy.
Keyphrases
- molecular docking
- molecular dynamics simulations
- cell cycle
- drug discovery
- cell proliferation
- molecular dynamics
- signaling pathway
- cancer therapy
- metabolic syndrome
- density functional theory
- epithelial mesenchymal transition
- emergency department
- wastewater treatment
- type diabetes
- drug delivery
- adipose tissue
- case control
- bioinformatics analysis
- drug induced