Biology subjects

Kaysser, L.

Publications and source records attributed to Kaysser, L..

3 recordsLinked to original sources

bioRxiv2026

A generalizable interface-seeded framework for de novo design of functional oligomers

Protein oligomers are ubiquitous in biological systems and essential for function. However, the de novo design of oligomers that controllably assemble in response to exogenous stimuli remains challenging. Here, we present an AI-based generative approach that leverages an interface-seeded strategy for designing responsive homo-oligomers from isolated interaction modules. Experimentally validated designs are highly accurate and explore new-to-nature topologies. We show that designs effectively respond to their chemical triggers with conditional oligomerization or to phosphorylation-driven conformational changes with reversible oligomerization. We further functionalized our responsive assemblies to build ligand-dependent membrane binding systems and phosphorylation-controlled gene regulatory switches. Our framework enables the generalizable design of responsive protein complexes, opening novel possibilities for the engineering of biosynthetic systems with sophisticated regulatory mechanisms.

biochemistry↗

bioRxiv2025

Intrinsic structure of lipoplexes embedded in polyelectrolyte multilayers

The functionalization of surfaces with therapeutically applicable nucleic acid carriers provides promising strategies in biomedical research to develop therapies which focus on local nucleic acid delivery. One such approach is the embedding of lipoplexes (LPXs) in polysaccharide-based polyelectrolyte multilayers (PEMs). PEMs based on hyaluronic acid and chitosan lead to efficient embedding of customized LPX connected with good biological activity. However, although quantitative evaluation demonstrates LPX embedding, information on the embedded LPXs has been missing. In this study we used synchrotron-based grazing-incidence small angle x-ray scattering to investigate the effects of the change in the chemical environment caused by the embedding into PEMs on the LPXs internal mesoscopic structure. While the lamellar character of the LPXs was preserved, the repeat distance was affected by the embedding into polysaccharide-based coatings.

biophysics↗

bioRxiv2024

HyperMPNN - A general strategy to design thermostable proteins learned from hyperthermophiles

Stability is a key factor to enable the use of recombinant proteins in therapeutic or biotechnological applications. Deep learning protein design approaches like ProteinMPNN have shown strong performance both in creating novel proteins or stabilizing existing ones. However, it is unlikely that the stability of the designs will significantly exceed that of the natural proteins in the training set, which are biophysically only marginally stable. Therefore, we collected predicted protein structures from hyperthermophiles, which differ substantially in their amino acid composition from mesophiles. Notably, ProteinMPNN fails to recover their unique amino acid composition. Here we show that a retrained network on predicted proteins from hyperthermophiles, termed HyperMPNN, not only recovers this unique amino acid composition but can also be applied to proteins from non-hyperthermophiles. Using this novel approach on a protein nanoparticle with a melting temperature of 65{degrees}C resulted in designs remaining stable at 95{degrees}C. In conclusion, we created a new way to design highly thermostable proteins through self-supervised learning on data from hyperthermophiles.

bioinformatics↗