Computational benchmarking of putative KIFC1 inhibitors
Nivya Sharma1, Dani Setiawan2, Donald Hamelberg2
1Department of Biology, Georgia State University, Atlanta, Georgia, USA.
Medicinal Research Reviews
|September 15, 2022
Summary
Centrosome clustering (CC) in cancer cells involves KIFC1, a protein targeted by inhibitors. This review analyzes KIFC1 inhibitors, aiding in developing new cancer therapies.
Area of Science:
- Cell Biology
- Molecular Oncology
- Biochemistry
Background:
- The centrosome is crucial for cell division; its amplification in cancer leads to chromosomal instability.
- Cancer cells employ centrosome clustering (CC) to survive, often involving the KIFC1 protein.
- KIFC1 upregulation in cancer makes it a promising therapeutic target.
Purpose of the Study:
- To review known KIFC1 inhibitors and their biological activities.
- To present computational docking data for KIFC1 inhibitors.
- To provide a comparative analysis to guide the design of potent KIFC1 inhibitors.
Main Methods:
- Literature review of KIFC1 inhibitors and their experimental validation.
- Computational docking studies to predict binding sites and affinities.
- Comparative analysis of experimental and computational data.
Main Results:
- Identification and analysis of various KIFC1 inhibitors with centrosome declustering activity.
- Presentation of docking data for selected inhibitors, revealing binding interactions.
- A comparative framework integrating biological and computational findings.
Conclusions:
- KIFC1 inhibitors represent a promising strategy for cancer therapy by targeting CC.
- Integrated analysis of experimental and computational data is valuable for inhibitor design.
- This review provides a foundation for developing more effective KIFC1-targeted cancer treatments.
