Computational benchmarking of putative KIFC1 inhibitors.
Med Res Rev
; 43(2): 293-318, 2023 03.
Article
en En
| MEDLINE
| ID: mdl-36104980
The centrosome in animal cells is instrumental in spindle pole formation, nucleation, proper alignment of microtubules during cell division, and distribution of chromosomes in each daughter cell. Centrosome amplification involving structural and numerical abnormalities in the centrosome can cause chromosomal instability and dysregulation of the cell cycle, leading to cancer development and metastasis. However, disturbances caused by centrosome amplification can also limit cancer cell survival by activating mitotic checkpoints and promoting mitotic catastrophe. As a smart escape, cancer cells cluster their surplus of centrosomes into pseudo-bipolar spindles and progress through the cell cycle. This phenomenon, known as centrosome clustering (CC), involves many proteins and has garnered considerable attention as a specific cancer cell-targeting weapon. The kinesin-14 motor protein KIFC1 is a minus end-directed motor protein that is involved in CC. Because KIFC1 is upregulated in various cancers and modulates oncogenic signaling cascades, it has emerged as a potential chemotherapeutic target. Many molecules have been identified as KIFC1 inhibitors because of their centrosome declustering activity in cancer cells. Despite the ever-increasing literature in this field, there have been few efforts to review the progress. The current review aims to collate and present an in-depth analysis of known KIFC1 inhibitors and their biological activities. Additionally, we present computational docking data of putative KIFC1 inhibitors with their binding sites and binding affinities. This first-of-kind comparative analysis involving experimental biology, chemistry, and computational docking of different KIFC1 inhibitors may help guide decision-making in the selection and design of potent inhibitors.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Benchmarking
/
Neoplasias
Límite:
Animals
Idioma:
En
Revista:
Med Res Rev
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos