PepCARES: A Comprehensive Advanced Refinement and Evaluation System for Peptide Design and Affinity Screening

Peptides are crucial in vaccine research, and their remarkable specificity and efficacy make them a promising potential drug class. However, designing and screening these peptides computationally is challenging. Here, we present the comprehensive advanced refinement and evaluation system (PepCARES), a program utilizing our novel model called PeptideMPNN and score evaluation for peptide design and affinity screening. PeptideMPNN, built on ProteinMPNN with transfer learning, significantly enhances sequence recovery (by 26.26%) and reduces perplexity (by 0.536) in a sequence generation task. We designed peptides targeting two HLA alleles and, using MHCfovea and PDBePISA, identified candidates with high potential. From 20 designed peptides, 14 and 7 peptides were selected, respectively. Our research provides a method for designing and screening peptides, making an important step toward the development of peptide-based vaccines.