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PepGen provides scalable, motif-constrained MHC II peptide redesign and de novo generation, validated through thorough benchmarks and functional assays.
PepChem, a deep learning model utilizing novel, molecular-level peptide representations that enable predictions for sidechain modifications, bridges the critical gap in PTM-aware immune recognition prediction, with immediate applications in autoimmunity, cancer, and infectious disease.
The results suggest that anti-TIM3 combined with decitabine engages a distinct mechanism of immune activation compared to anti-PD1 and anti-CTLA4, preferentially expanding NK-cell and CD4+ T-cell populations.
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