Setmelanotide optimization through fragment-growing, molecular docking in-silico method targeting MC4 receptor

Area of Science:

• Biochemistry
• Computational Chemistry
• Pharmacology

Background:

• Obesity is a global health concern requiring novel therapeutic strategies.
• Ligand-protein interactions are crucial for developing targeted anti-obesity medications.
• Understanding receptor binding mechanisms is key to drug design.

Purpose of the Study:

• To design novel setmelanotide derivatives for improved anti-obesity effects.
• To investigate the binding affinity and selectivity of new compounds with melanocortin receptors.
• To explore the potential of in silico drug design for obesity treatment.

Main Methods:

• Utilized cryo-EM protein structure (7AUE) for molecular modeling.
• Employed fragment-growing and de novo evolution strategies.
• Performed in silico simulations to assess binding abilities and selectivity.
• Analyzed molecular surface differences in receptor binding pockets.

Main Results:

• Designed setmelanotide derivatives with D-Met substitution at the linker site.
• Simulations indicated enhanced binding to melanocortin 4 receptor.
• Achieved improved selectivity for melanocortin 4 receptor over melanocortin 1 receptor.
• Identified shape differences in binding pockets as key to selectivity.

Conclusions:

• Novel setmelanotide derivatives demonstrate potential for enhanced anti-obesity activity.
• Improved selectivity is attributed to specific molecular surface interactions.
• In silico design offers a promising avenue for future anti-obesity drug discovery.
• Further research and synthesis are needed to validate these findings.