Silicon exaptation discovers antimicrobial peptides
- 1VTT Technical Research Centre of Finland
Abstract
Advances in machine learning (ML) have enabled the de novo design of synthetic proteins and peptides tailored for specific structural or functional properties. As ML becomes a central tool in forward design, we suggest that its value extends beyond optimizing known objectives. It can also lead to what we term here in this work as silicon exaptation, revealing unexpected functional properties that were never part of the original design goals. This reflects a principle common in biology, that repurposes traits where features evolved for one role can later enable unforeseen functions. In this context, these accidental findings are not constrained by preconceptions but arise from latent function emergence and the algorithm's gradual drift, a new process that can co-evolves with human curiosity, intuition, and interpretive reasoning, which can be used to recognize unexpected patterns and transform them into new discoveries. In this study, we discovered a set of peptides through silicon exaptation, in which the ML pipeline was originally optimized for structural characteristics unrelated to any antimicrobial functionalities. The peptides were originally designed to adopt defined secondary structures in response to environmental stimuli, with no antimicrobial properties intended or included in the training objectives. We systematically evaluated the antimicrobial potential of these peptides using broth microdilution assays and membrane integrity tests, identifying several candidates with potent and selective antibacterial activity without detectable cytotoxicity toward mammalian cells.
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BibTeX
@misc{wojtan2026silicon,
title = {{Silicon exaptation discovers antimicrobial peptides}},
author = {G. Wojtan and N. Ahonen and B. F. Yildirir and S. Julin and M. Babin and T. Laakko and C. Ganser and F.- Y. Chan and A. Suvi and N. Nonappa and C. Jonkergouw and A. Miserez and T. Uchihashi and P. Batys and P. Mohammadi},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.21.753171},
url = {https://www.biorxiv.org/content/10.64898/2026.09.21.753171v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Silicon exaptation discovers antimicrobial peptides
AU - G. Wojtan
AU - N. Ahonen
AU - B. F. Yildirir
AU - S. Julin
AU - M. Babin
AU - T. Laakko
AU - C. Ganser
AU - F.- Y. Chan
AU - A. Suvi
AU - N. Nonappa
AU - C. Jonkergouw
AU - A. Miserez
AU - T. Uchihashi
AU - P. Batys
AU - P. Mohammadi
PY - 2026
DA - 2026/09/21
PB - bioRxiv
DO - 10.64898/2026.09.21.753171
UR - https://www.biorxiv.org/content/10.64898/2026.09.21.753171v1
AB - Advances in machine learning (ML) have enabled the de novo design of synthetic proteins and peptides tailored for specific structural or functional properties. As ML becomes a central tool in forward design, we suggest that its value extends beyond optimizing known objectives. It can also lead to what we term here in this work as silicon exaptation, revealing unexpected functional properties that were never part of the original design goals. This reflects a principle common in biology, that repurposes traits where features evolved for one role can later enable unforeseen functions. In this context, these accidental findings are not constrained by preconceptions but arise from latent function emergence and the algorithm's gradual drift, a new process that can co-evolves with human curiosity, intuition, and interpretive reasoning, which can be used to recognize unexpected patterns and transform them into new discoveries. In this study, we discovered a set of peptides through silicon exaptation, in which the ML pipeline was originally optimized for structural characteristics unrelated to any antimicrobial functionalities. The peptides were originally designed to adopt defined secondary structures in response to environmental stimuli, with no antimicrobial properties intended or included in the training objectives. We systematically evaluated the antimicrobial potential of these peptides using broth microdilution assays and membrane integrity tests, identifying several candidates with potent and selective antibacterial activity without detectable cytotoxicity toward mammalian cells.
ER -