Computational Approach for the Development of pH-Selective PD-1/PD-L1 Signaling Pathway Inhibition in Fight with...

Area of Science:

• Oncology
• Immunology
• Computational Chemistry

Background:

• Immunotherapy targeting the PD-1/PD-L1 pathway shows promise in cancer treatment.
• However, non-specific immune activation against healthy cells remains a significant challenge.
• Tumor microenvironments often exhibit acidic pH, differing from healthy tissues.

Purpose of the Study:

• To develop a strategy for selective PD-L1 pathway targeting in the acidic tumor microenvironment.
• To identify novel pH-selective inhibitors using in silico methods.
• To reduce off-target toxicity associated with current immunotherapies.

Main Methods:

• Virtual screening of approximately 10,000 natural compounds from the MolPort database.
• Molecular mechanics and molecular dynamics simulations under physiological (pH 7.4) and acidic (pH 5.5) conditions.
• Analysis of inhibitor binding affinity and complex stability.

Main Results:

• The compound MolPort-001-742-690 demonstrated promising pH-selective inhibition of PD-L1.
• This inhibitor exhibited higher affinity for PD-L1 in acidic conditions compared to neutral pH.
• Molecular dynamics simulations confirmed the stability of the inhibitor-PD-L1 complex at acidic pH, with lower predicted toxicity than existing inhibitors.

Conclusions:

• In silico techniques can effectively discover pH-selective inhibitors for targeted cancer immunotherapy.
• MolPort-001-742-690 represents a potential candidate for enhancing immunotherapy precision and safety.
• Further experimental validation is warranted to translate these findings into clinical applications.