Biology subjects

Albanese, K. I.

Publications and source records attributed to Albanese, K. I..

5 recordsLinked to original sources

bioRxiv2026

Expanding all-α-helical protein space through rational computational design

De novo protein design is advancing rapidly1,2. This is being driven by AI to generate protein backbones, sequences, and structural models3-7. As a result, de novo designed proteins are becoming larger and more complex8-10, and increasingly explore new protein structures11,12. By contrast, natural proteins have evolved structural and functional complexity by modular combination of recurring protein domains13. Approximately 25% of these natural domains are mostly -helical structures14. Here we show how these can be expanded using rational computational design. Following the domain classification scheme CATH15, we build complex all- de novo proteins hierarchically using sequence-to-structure relationships for helix-helix interactions, systematic rules to connect helices, computational tools to design loops, and in silico evaluation. The pipeline starts with a target architecture of free-standing helices. These are connected into a topology by considering local arrangements of helical bundles using understood sequence-to-structure relationships for helix packing. Single-chain sequences are completed using template- and AI-based methods. Finally, AlphaFold models are assessed to give small numbers of designs for experimental validation. We test 31 designs for 14 different architectures and 25 topologies. 75% of these express as stable, monomeric, water-soluble proteins; and >30% yield X-ray crystal structures matching the designs to atomic accuracy and with new-to-nature structures. Finally, several of the scaffolds are functionalised through one-shot designs to deliver ion, small-molecule and protein binders.

synthetic biology↗

bioRxiv2025

De novo designed 3-helix bundle peptides and proteins with controlled topology and stability

Computational protein design is advancing rapidly. However, approaches and methods are needed to increase success rates and to elaborate designs. Here we describe the combination of rational and computational design to deliver three-helix bundle (3HB) peptide assemblies and single-chain proteins with control over topology and thermal stability. First, we garner sequence-to-structure relationships from antiparallel 3HBs in the Protein Data Bank. This gives core-packing rules, including layers of hydrogen-bonded polar residues, which are combined with surface-charge patterning to design complementary sequences for acidic (A), basic (B), and neutral (N) helices. By altering the design of the N helix, two sets of synthetic peptides are generated for clockwise and anticlockwise arrangements of the three-helix assemblies. Solution-phase characterization shows that both ABN peptide mixtures form stable, heterotrimeric assemblies consistent with the targeted up-down-up topologies. Next, AlphaFold2 models for both designs are used to seed computational designs of single-chain proteins where the helices are connected by loop building. Synthetic genes for these express in E. coli to yield soluble, monomeric, and thermally stable proteins. By systematically introducing additional polar layers within the core, the thermal stability of these proteins is varied without compromising the specificity of the helix-helix interactions. Chemical and thermal denaturation reveals comparable thermodynamic parameters to those of highly stable natural proteins. Four X-ray crystal structures confirm that the design models and AlphaFold2 predictions match to sub-[A] accuracy.

biophysics↗

bioRxiv2024

De novo design of parallel and antiparallel A3B3 heterohexameric alpha-helical barrels

The de novo design of -helical coiled-coil peptides is advanced. Using established sequence-to-structure relationships, it is possible to generate various coiled-coil assemblies with predictable numbers and orientations of helices. Here we target new assemblies, namely A3B3 heterohexamer -helical barrels. These designs are based on pairs of sequences with 3-heptad repeats (abcdefg) programmed with a = Leu, d = Ile, e = Ala, and g = Ser, and b = c = Glu to make the acidic (A) chains and b = c = Lys in the basic (B) chains. These design rules ensure that the desired oligomeric state and stoichiometry are readily achieved. However, controlling the orientation of neighboring helices (parallel or anti-parallel) is less straightforward. Surprisingly, we find that assembly and helix orientation are sensitive to the starting position of the heptad repeats (the register) in the peptide sequences. Peptides starting at g (g-register) form a parallel 6-helix barrel in solution and in an X-ray crystal structure, whereas the b- and c-register peptides form an antiparallel complex. In lieu of experimental X-ray structures for b- and c-register peptides, AlphaFold-Multimer is used to predict atomistic models. However, considerably more sampling than the default value is required to match the models and the experimental data, as many confidently predicted and plausible models are generated with incorrect helix orientations. This work reveals the previously unknown influence of heptad register on the orientation of -helical coiled-coil peptides and provides insights for the modeling of oligopeptide coiled-coil complexes with AlphaFold.

synthetic biology↗

bioRxiv2023

Rationally seeded computational protein design

Computational protein design is advancing rapidly. Here we describe efficient routes to two families of -helical-barrel proteins with central channels that bind small molecules. The designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides. Adjacent helices are connected using computational loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix-turn-helix-turn-helix motifs that are packed onto the barrels computationally. Throughout these pipelines, residues that define open states of the barrels are maintained. This minimises sequence sampling and accelerates routes to successful designs. For each of 6 targets, just 2 - 6 synthetic genes are made for expression in E. coli. On average, 80% express to give soluble monomeric proteins that are characterized fully, including high-resolution structures for most targets that match the seed structures and design models with high accuracy.

synthetic biology↗

bioRxiv2022

From peptides to proteins: coiled-coil tetramers to single-chain 4-helix bundles

The design of completely synthetic proteins from first principles--de novo protein design--is challenging. This is because, despite recent advances in computational protein-structure prediction and design, we do not understand fully the sequence-to-structure relationships for protein folding, assembly, and stabilization. Antiparallel 4-helix bundles are amongst the most studied scaffolds for de novo protein design. We set out to re-examine this target, and to determine clear sequence-to-structure relationships, or design rules, for the structure. Our aim was to determine a common and robust sequence background for designing multiple de novo 4-helix bundles, which, in turn, could be used in chemical and synthetic biology to direct protein-protein interactions and as scaffolds for functional protein design. Our approach starts by analyzing known antiparallel 4-helix coiled-coil structures to deduce design rules. In terms of the heptad repeat, abcdefg--i.e., the sequence signature of many helical bundles--the key features that we identify are: a = Leu, d = Ile, e = Ala, g = Gln, and the use of complementary charged residues at b and c. Next, we implement these rules in the rational design of synthetic peptides to form antiparallel homo- and heterotetramers. Finally, we use the sequence of the homotetramer to derive a single-chain 4-helix-bundle protein for recombinant production in E. coli. All of the assembled designs are confirmed in aqueous solution using biophysical methods, and ultimately by determining high-resolution X-ray crystal structures. Our route from peptides to proteins provides an understanding of the role of each residue in each design.

synthetic biology↗