Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognition

Area of Science:

• Oncology
• Pharmacology
• Computational Biology

Background:

• The p53 protein, a crucial tumor suppressor, is frequently inactivated in human cancers.
• In many cancers, wild-type p53 function is inhibited by the murine double minute 2 (MDM2) protein.
• Inhibiting the p53-MDM2 interaction offers a novel therapeutic strategy for cancer treatment.

Purpose of the Study:

• To identify novel small-molecule inhibitors of the p53-MDM2 interaction using virtual screening.
• To evaluate the potential of identified compounds as anti-cancer therapeutics.

Main Methods:

• Ultrafast shape recognition (USR) virtual screening of the DrugBank database.
• Molecular modeling, including flexible receptor docking and binding energy analysis.
• Experimental validation using human colon tumor cells.

Main Results:

• Six potential p53-MDM2 inhibitors were identified via USR screening.
• Molecular modeling supported the inhibitory potential of the screened compounds.
• Telmisartan, a top hit, demonstrated dose-dependent, p53-dependent inhibition of colon tumor cell growth.

Conclusions:

• The USR-based virtual screening protocol is effective for identifying p53-MDM2 inhibitors.
• Telmisartan shows immediate clinical potential as a cancer therapeutic and a lead for developing novel inhibitors.
• Targeting the p53-MDM2 interaction is a promising strategy for developing new cancer treatments.