Computational design of blue melanin with peptide motif scaffolding
The Preprint
Authors: D. S. Lee, B. Park, S. Salgado, J. Dolgin, D. L. Kaplan
Posted on: bioRxiv (2026). Not yet peer-reviewed.
De novo design of stable blue (and purple/green) melanin pigments using deep-learning protein design.
Abstract
Section titled “Abstract”De novo melanin design seeks to extend natural melanin colors to new, stable colors (blue, purple, green) with sequence-to-color tunability. Natural melanin, polymerized from tyrosine (Y), is a robust pigment with heterogeneous molecular weights. Control of melanin size (length) is challenging; thus, only specific colors (yellow to brown) exist in nature. In this work, the authors describe the design of blue melanin through the polymerization of Y-containing pentapeptides with two key properties: tight packing during peptide assembly and high solubility in aqueous environments. By motif scaffolding a pentapeptide-repeat protein (PRP) with RFdiffusion, they narrowed 160,000 possible combinations to a library of 905 Y-containing pentapeptides with tight-packing features. Two of the most soluble designs successfully formed stable blue melanin with λmax absorbing at 615–620 nm, contributed by homogeneous melanin length achieved around 60 Y units. Other designs also formed new colors (purple, green), along with more familiar colors (red, yellow, brown). Blue melanin exhibited thermal stability at an autoclave temperature of 121 °C and photostability of weeks under 600 lux illumination, and was demonstrated as an electrophoretic ink. De novo color design from simple peptides could potentially transform how colorants are sourced and produced, and should also inspire the development of new deep-learning tools to directly predict colors from amino acid sequences.
Reference
Section titled “Reference”Lee, D. S., Park, B., Salgado, S., Dolgin, J., & Kaplan, D. L. (2026). Computational design of blue melanin with peptide motif scaffolding. bioRxiv. https://doi.org/10.64898/2026.02.02.703104
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