A novel decoding strategy for ProteinMPNN to design with less MHC Class I immune-visibility

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Abstract

Due to their versatility and diverse production methods, proteins have attracted a lot of interest for industrial as well as therapeutic applications. Designing new therapeutics requires careful consideration of immune responses, particularly the cytotoxic T-lymphocyte (CTL) reaction to intra-cellular proteins. In this study, we introduce<monospace>CAPE-Beam</monospace>, a novel decoding strategy for the established<monospace>ProteinMPNN</monospace>protein design model. Our approach minimizes CTL immunogenicity risk by limiting designs to only consist of kmers that are either predicted not to be presented to CTLs or are subject to central tolerance. We compare<monospace>CAPE-Beam</monospace>to greedily sampling from<monospace>ProteinMPNN</monospace>and<monospace>CAPE-MPNN</monospace>. We find that our novel decoding strategy can produce structurally similar proteins while incorporating more human like kmers. This significantly lowers CTL immunogenicity risk in precision medicine, and represents a key step towards reducing this risk in protein therapeutics targeting a wider patient population.

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