A novel decoding strategy for ProteinMPNN to design with less visibility to cytotoxic T-lymphocytes

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 CAPE-Beam, a novel decoding strategy for the established ProteinMPNN 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 that prevents CTLs from attacking self-peptides. We compare CAPE-Beam to the standard way of sampling from ProteinMPNN and the state of the art (SOTA) technique CAPE-MPNN. 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. Source: https://github.com/hcgasser/CAPE_Beam.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.07.055
Citations
1
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.81

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article

A novel decoding strategy for ProteinMPNN to design with less visibility to cytotoxic T-lymphocytes

Javier A. Alfaro, Hans-Christof Gasser, Ajitha Rajan
1 citations
Computational and Structural Biotechnology Journal
RNA and protein synthesis mechanisms
0.81
article

A novel decoding strategy for ProteinMPNN to design with less visibility to cytotoxic T-lymphocytes

Javier A. Alfaro, Hans-Christof Gasser, Ajitha Rajan
article en
1 citations

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 CAPE-Beam, a novel decoding strategy for the established ProteinMPNN 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 that prevents CTLs from attacking self-peptides. We compare CAPE-Beam to the standard way of sampling from ProteinMPNN and the state of the art (SOTA) technique CAPE-MPNN. 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. Source: https://github.com/hcgasser/CAPE_Beam.

Computational and Structural Biotechnology JournalVol. 27
University of Calgary (CA), Occupational Cancer Research Centre (CA), University of Edinburgh (GB)
UK Research and Innovation, Royal Academy of Engineering, Royal Society, HORIZON EUROPE Framework Programme
Zero hunger
Openalex Percentile: Top 25%
RNA and protein synthesis mechanisms
0.81
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A novel decoding strategy for ProteinMPNN to design with less visibility to cytotoxic T-lymphocytes — Javier A. Alfaro, Hans-Christof Gasser, et al. · Computational and Structural Biotechnology Journal (2025) | TGRS Research Map | TGRS