Biology subjects

Leggett, G. J.

Publications and source records attributed to Leggett, G. J..

3 recordsLinked to original sources

bioRxiv2025

Rapid Assessment of Size, Shape, and Chemical Complementarity of Ligands for Computational Protein Design

Driven by deep-learning approaches, computational protein design is advancing rapidly, and it is now possible to generate many de novo protein structures quickly and robustly. This sets new frontiers for the field, including designing proteins that bind small molecules tightly and specifically, and understanding the non-covalent interactions that underpin such designs to make binding predictable and tunable. Here we address these challenges with a rapid physics-based computational method to generate isosteric and chemically complementary binding pockets for small-molecule targets in de novo designed proteins. We test this experimentally by constructing and characterizing binding proteins for several synthetic and natural chromophores. By evaluating only single-digit numbers of designs, the pipeline delivers stable proteins with pre-organized binding sites confirmed by X-ray crystallography, which bind the targets selectively with micromolar affinities or better. To illustrate the scope and applications of this approach, we incorporate distinct and coupled chromophore-binding sites in a two-domain de novo protein enabling controlled energy transfer between the two sites, and we develop a small de novo binding protein that can be used in live mammalian cells to visualize sub-cellular structures.

biophysics↗

bioRxiv2024

Confinement and Catalysis Within De Novo Designed Peptide Barrels

De novo protein design has advanced such that many peptide assemblies and protein structures can be generated predictably and quickly. The drive now is to bring functions to these structures, for example, small-molecule binding and catalysis. The formidable challenge of binding and orienting multiple small molecules to direct chemistry is particularly important for paving the way to new functionalities. To address this, here we describe the design, characterization, and application of small-molecule:peptide ternary complexes in aqueous solution. This uses -helical barrel (HB) peptide assemblies, which comprise 5 or more -helices arranged around central channels. These channels are solvent accessible, and their internal dimensions and chemistries can be altered predictably. Thus, HBs are analogous to molecular flasks made in supramolecular, polymer, and materials chemistry. Using Forster resonance energy transfer as a readout, we demonstrate that specific HBs can accept two different organic dyes, 1,6-diphenyl-1,3,5-hexatriene and Nile Red in close proximity. In addition, two anthracene molecules can be accommodated within an HB to promote photocatalytic anthracene-dimer formation. However, not all ternary complexes are productive, either in energy transfer or photocatalysis, illustrating the control that can be exerted by judicious choice and design of the HB.

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↗