Rational design of peptide-based programmed cell death 1 immune checkpoint inhibitors using advanced integrated...

Area of Science:

• Immunology
• Computational Biology
• Drug Discovery

Background:

• The programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) pathway is a key immune checkpoint exploited by cancers.
• Current monoclonal antibody therapies have limitations, necessitating the development of alternative inhibitors like peptides.

Purpose of the Study:

• To design and evaluate novel peptide inhibitors of the PD-1/PD-L1 immune checkpoint using an integrated in silico approach.
• To identify potent peptide inhibitors with enhanced binding affinity and therapeutic potential for cancer immunotherapy.

Main Methods:

• Creation of a diverse peptide library by combining PD-L1 fragments with validated anticancer peptides.
• Utilized structural modeling, virtual screening, point mutations, and molecular docking to identify lead candidates.
• Assessed therapeutic potential through toxicity/allergenicity predictions, molecular dynamics, steered molecular dynamics, and umbrella sampling.

Main Results:

• Identified Pep872_mod392 as a potent PD-1 inhibitor with high binding affinity and a low dissociation constant.
• Structural analysis revealed extensive interactions between Pep872_mod392 and PD-1, effectively blocking PD-L1 binding.
• Molecular dynamics simulations confirmed the stability and thermodynamic favorability of the Pep872_mod392-PD-1 complex.

Conclusions:

• Pep872_mod392 is a promising candidate for further experimental validation and optimization as a cancer immunotherapy agent.
• The in silico strategy is effective for identifying potent inhibitors of immune checkpoints and protein-protein interactions.
• This research lays the groundwork for developing novel peptide-based cancer therapeutics.