Protein ScienceBiochemistryPeer-reviewed journal article
Computational design of blue melanin with peptide motif scaffolding
Di Sheng LeeiD, Bomi ParkiD, Sergio Salgado, James DolginiD, David Lee KaplaniD
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 heterogenous molecular weights. Control of melanin size (length) is challenging; thus, only specific colors (yellow to brown) exist in nature. In this work, we 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, we 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 {lambda}max absorbing in 615-620 nm, contributed by homogeneous melanin length achieved around 60 Y units. Other designs also formed new colors (purple, green), along with more known colors (red, yellow, brown). We found that blue melanin exhibited thermal stability at an autoclave temperature of 121{degrees}C and photostability of weeks under 600 lux illumination. We also demonstrated the application of blue melanin as an electrophoretic ink. De novo color design from simple peptides could potentially transform how colorants are sourced and produced. Our approach with computational design should also inspire the development of new deep-learning tools to directly predict colors from amino acid sequences.
- assay: protein sequence
- research focus: protein design
- research focus: sequence-to-function modeling
- approach: deep learning
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 46th percentile
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