RSC Chemical BiologyBioengineeringPeer-reviewed journal article
De novo acyl carrier proteins display structure-independent modification and sequence novelty
Michael A. HerreraiD, Grace King, Zoe Ozols, Gioele Antonio TiburtiniiD, Nicoletta Schiavo, Francesca SpyrakisiD, Louise K. CharkoudianiD, Dominic J. CampopianoiD
Abstract
Acyl carrier proteins (ACPs) are dynamic, structurally conserved -helical proteins central to many primary and secondary metabolic processes. Whilst prior engineering efforts have focused on strategic mutagenesis and "helix swaps", much of the ACP sequence design space remains underexplored. Here, we create diverse variants of the archetypal ACP subclass - AcpP - using a bespoke sequence-generating algorithm (ALGO-CP), which utilises a combined evolutionary and physicochemical design approach. Using ALGO-CP, we generated two soluble candidates - ALGO-055 and ALGO-059 - that can undergo full post-translational modification from apo[->]holo[->]acyl forms in vitro, using recombinant modifying enzymes. Building on these successful designs, we further adapted ALGO-CP to produce several chimeras, two of which - chALGO-012 and chALGO-024 - also exhibit full modifiability. We explore the structural plasticity of our ALGO variants via robust molecular dynamic simulations, and we further reveal by circular dichroism spectroscopy that ALGO-055 and ALGO-059 lack the canonical -helical fold of an ACP, whilst remaining soluble and readily modifiable. Upon acylation of ALGO-055 and ALGO-059, we observe a marked increase in helicity indicative of partial restructuring. Of note, both ALGO-055 and ALGO-059 harbour several rare amino acid variations across their sequences, whilst preserving many important acidic "hotspots" involved in key protein-protein interactions. By testing the limits of the AcpP design space, our findings suggest that some key aspects of ACP behaviour (specifically post-translational modification) can be retained independently of the canonical structure. This work establishes a foundation for probing ACP sequence diversity through a hybrid computational-experimental approach. ALGO-CP is available under AGPL3.0 license: https://github.com/MAHerrera-94/ALGO_CP.
- assay: protein structure
- assay: protein sequence
- research focus: protein design
- approach: deep learning
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 21th percentile
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