Discovery of Cyclic Peptide Inhibitors Targeted on TNFα-TNFR1 from Computational Design and Bioactivity Verification

Abstract

Activating tumor necrosis factor receptor 1 (TNFR1) with tumor necrosis factor alpha (TNFα) is one of the key pathological mechanisms resulting in the exacerbation of rheumatoid arthritis (RA) immune response. Despite various types of drugs being available for the treatment of RA, a series of shortcomings still limits their application. Therefore, developing novel peptide drugs that target TNFα-TNFR1 interaction is expected to expand therapeutic drug options. In this study, the detailed interaction mechanism between TNFα and TNFR1 was elucidated, based on which, a series of linear peptides were initially designed. To overcome its large conformational flexibility, two different head-to-tail cyclization strategies were adopted by adding a proline-glycine (GP) or cysteine-cysteine (CC) to form an amide or disulfide bond between the N-C terminal. The results indicate that two cyclic peptides, R1_CC4 and α_CC8, exhibit the strongest binding free energies. α_CC8 was selected for further optimization using virtual mutations through in vitro activity and toxicity experiments due to its optimal biological activity. The L16R mutant was screened, and its binding affinity to TNFR1 was validated using ELISA assays. This study designed a novel cyclic peptide structure with potential anti-inflammatory properties, possibly bringing an additional choice for the treatment of RA in the future.

Keywords

• molecular dynamics simulation
• computational drug design
• cyclic peptide
• TNFα
• TNFR1