Biology subjects

Scrutton, N. S.

Publications and source records attributed to Scrutton, N. S..

6 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

Triplet Quenching by Active Site Cysteine Residues Improves Photostability in Fatty Acid Photodecarboxylase

Enzyme photobiocatalysis uses light to drive high-energy transformations but is limited by the rarity of photoenzymes. Fatty acid photodecarboxylase (FAP), a recently discovered photoenzyme, enables fatty acid conversion to alkanes/alkenes via excitation of an FAD cofactor, though its poor photostability and photoinactivation has hindered industrial applications. Here, we combine protein engineering approaches with biocatalytic and biophysical techniques, as well as computational chemistry, to demonstrate that additional active site cysteine residues can suppress oxygen-mediated inactivation processes that are driven by the FAD triplet-excited state. We identify a number of positions close to the FAD for cysteine residues that lead to a significant enhancement in activity as a result of an increase in the number of catalytic turnovers and improved photostability. The additional cysteine residues quench the triplet excited state of the FAD cofactor via a proposed proton-coupled electron transfer mechanism, resulting in lower levels of harmful reactive oxygen species. Our study highlights promising routes to mitigate non-productive, photoinactivation pathways in FAP and informs the rational design of new flavin-based photoenzymes.

biochemistry↗

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↗

bioRxiv2025

De novo production of prenylnaringenin compounds by a metabolically engineered Escherichia coli

Prenylnaringenin (PN) compounds, namely 8-prenylnaringenin (8-PN), 3-prenylnaringenin (3-PN), and 6-prenylnaringenin (6-PN), are reported to have several interesting bioactivities. This study aimed to validate a biosynthetic pathway for de novo production of PN in Escherichia coli. A previously optimized E. coli chassis capable of efficiently de novo producing naringenin was used to evaluate eleven prenyltransferases (PTs) for the production of PN compounds. As PT reaction requires dimethylallyl pyrophosphate (DMAPP) as extended substrate that has limited availability inside the cells, clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 12a (Cas12a) (CRISPR-Cas12a) was used to construct ten boosted DMAPP-E. coli strains. All the PTs, in combination with the naringenin biosynthetic pathway, were tested in these strains. Experiments in 96-well deep well plates identified twelve strains capable of producing PN. E. coli M-PAR-121 with the integration of the 1-deoxy-D-xylulose-5-phosphate synthase (DXS) gene from E. coli (EcDXS) into the lacZ locus of the genome (E. coli M-PAR-121:EcDXS) expressing the soluble aromatic PT from Streptomyces roseochromogenes (CloQ) and the naringenin biosynthetic pathway was selected as the best producer strain. After optimizing the production media in shake flasks, 160.57 {micro}M of 3-PN, 4.4 {micro}M of 6-PN, and 2.66 {micro}M of 8-PN were obtained. The production was then evaluated at the bioreactor scale and 397.57 {micro}M of 3-PN (135.33 mg/L) and 25.61 {micro}M of 6-PN (8.72 mg/L) were obtained. To the best of our knowledge, this work represents the first report of de novo production of PN compounds using E. coli as a chassis.

synthetic biology↗

bioRxiv2017

Selenzyme: Enzyme selection tool for pathway design

Synthetic biology applies the principles of engineering to biology in order to create biological functionalities not seen before in nature. One of the most exciting applications of synthetic biology is the design of new organisms with the ability to produce valuable chemicals including pharmaceuticals and biomaterials in a greener; sustainable fashion. Selecting the right enzymes to catalyze each reaction step in order to produce a desired target compound is, however, not trivial. Here, we present Selenzyme, a free online enzyme selection tool for metabolic pathway design. The user is guided through several decision steps in order to shortlist the best candidates for a given pathway step. The tool graphically presents key information about enzymes based on existing databases and tools such as: similarity of sequences and of catalyzed reactions; phylogenetic distance between source organism and intended host species; multiple alignment highlighting conserved regions, predicted catalytic site, and active regions; and relevant properties such as predicted solubility and transmembrane regions. Selenzyme provides bespoke sequence selection for automated workflows in biofoundries. The tool is integrated as part of the pathway design stage into the design-build-test-learn SYNBIOCHEM pipeline. The Selenzyme web server is available at http://selenzyme.synbiochem.co.uk.

bioinformatics↗

bioRxiv2017

PartsGenie: an integrated tool for optimising and sharing synthetic biology parts

Synthetic biology is typified by developing novel genetic constructs from the assembly of reusable synthetic DNA parts, which contain one or more features such as promoters, ribosome binding sites, coding sequences and terminators. While repositories of such parts exist to promote their reuse, there is still a need to design novel parts from scratch.\n\nPartsGenie, freely available at http://parts.synbiochem.co.uk, is introduced to facilitate the computational design of such synthetic biology parts. PartsGenie has been designed to bridge the gap between optimisation tools for the design of novel parts, the representation of such parts in community-developed data standards such as Synthetic Biology Open Language (SBOL), and their sharing in journal-recommended data repositories.\n\nConsisting of a drag-and-drop web interface, a number of DNA optimisation algorithms, and an interface to the well-used data repository JBEI ICE, PartsGenie facilitates the design, optimisation and dissemination of reusable synthetic biology parts through a single, integrated application. PartsGenie can therefore be used as a single, stand-alone tool, or integrated into larger synthetic biology pipelines that are being developed in the SYNBIOCHEM centre and elsewhere.

synthetic biology↗