In this section
@article{Pretorius:2025,
author = {Pretorius, D and Nikov, G and Washio, K and Florent, S-W and Taunt, H and Ovchinnikov, S and Murray, J},
journal = {Communications Chemistry},
title = {Designing novel solenoid proteins with in silico evolution},
year = {2025}
}
TY - JOUR
AB - Solenoid proteins are elongated tandem repeat proteins with diverse biological functions, making them attractive targets for protein design. Advances in machine learning have transformed our understanding of sequence-structure relationships, enabling new approaches for de novo protein design. Here, we present an in silico evolution platform that couples a solenoid discriminator network with AlphaFold2 as an oracle within a genetic algorithm. Starting from random sequences, we design α-, β-, and αβ-solenoid backbones, generating structures that span natural and novel solenoid space. We experimentally characterise 41 solenoid designs, with α-solenoids consistently folding as intended, including one structurally validated design that closely matches the design model. All β-solenoids initially failed, reflecting the difficulty of designing β-strand majority proteins. By introducing terminal capping elements and refining designs based on earlier experimental screens, we generate two β-solenoids that have biophysical properties consistent with their designs. Our approach achieves fold-specific hallucination-based design without depending on explicit structural templates.
AU - Pretorius,D
AU - Nikov,G
AU - Washio,K
AU - Florent,S-W
AU - Taunt,H
AU - Ovchinnikov,S
AU - Murray,J
PY - 2025///
SN - 2399-3669
TI - Designing novel solenoid proteins with in silico evolution
T2 - Communications Chemistry
ER -
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