Elena Lopez-Martinez

Epitopes are short antigenic peptide sequences which are recognized by antibodies or immune cell receptors. These are central to the development of immunotherapies, vaccines, and diagnostics. However, the rational design of synthetic epitope libraries is challenging due to the large combinatorial sequence space, 20n combinations for linear epitopes of n amino acids, making screening and testing unfeasible, even with high throughput experimental techniques. In this study, we present a large language model, epiGPTope, pre-trained on protein data and specifically fine-tuned on linear epitopes, which for the first time can directly generate novel epitope-like sequences, which are found to possess statistical properties analogous to the ones of known epitopes. This generative approach can be used to prepare libraries of epitope candidate sequences. We further train statistical classifiers to predict whether an epitope sequence is of bacterial or viral origin, thus narrowing the candidate library and increasing the likelihood of identifying specific epitopes. We propose that such combination of generative and predictive models can be of assistance in epitope discovery. The approach uses only primary amino acid sequences of linear epitopes, bypassing the need for a geometric framework or hand-crafted features of the sequences. By developing a method to create biologically feasible sequences, we anticipate faster and more cost-effective generation and screening of synthetic epitopes, with relevant applications in the development of new biotechnologies.

Las proteínas de repetición son biopolímeros naturales ampliamente estudiados en el desarrollo de nuevas herramientas nanotecnológicas. La simplicidad de sus secuencias y la robustez de sus estructuras permiten el desarrollo de andamios versátiles y adaptables para un buen número de funciones. Además, la generación de híbridos proteína-nanomaterial eleva las posibilidades a un nuevo ámbito que ha comenzado a explorarse recientemente. En la presente revisión hemos actualizado algunos de los avances realizados en el campo, particularmente con las proteínas de repetición CTPR (del inglés Consensus Tetratico Peptide Repeats), y descrito mediante ejemplos el potencial de estos sistemas en diversas aplicaciones tecnológicas y biomédicas.

We report the fabrication of a conductive biomaterial based on engineered proteins and patterned gold nanoparticles to overcome the challenge of charge transport on macroscopic protein-based materials. This approach has great value for bioelectronics.

Metal nanoclusters and their unique properties are increasing in importance. In this review we acknowledge their application as sensors for biomarkers and the current state in preclinical and clinical uses.

Protein-based hybrid nanomaterials have recently emerged as promising platforms to fabricate tailored multifunctional biologics for biotechnological and biomedical applications. This work shows a simple, modular, and versatile strategy to design custom protein hybrid nanomaterials. This approach combines for the first time the engineering of a therapeutic protein module with the engineering of a nanomaterial-stabilizing module within the same molecule, resulting in a multifunctional hybrid nanocomposite unachievable through conventional material synthesis methodologies. As the first proof of concept, a multifunctional system was designed ad hoc for the therapeutic intervention and monitoring of myocardial fibrosis. This hybrid nanomaterial combines a designed Hsp90 inhibitory domain and a metal nanocluster stabilizing module resulting in a biologic drug labelled with a metal nanocluster. The engineered nanomaterial actively reduced myocardial fibrosis and heart hypertrophy in an animal model of cardiac remodeling. In addition to the therapeutic effect, the metal nanocluster allowed for in vitro, ex vivo, and in vivo detection and imaging of the fibrotic disease under study. This study evidences the potential of combining protein engineering and protein-directed nanomaterial engineering approaches to design custom nanomaterials as theranostic tools, opening up unexplored routes to date for the next generation of advanced nanomaterials in medicine.

A detailed investigation of the effect of electron injection on the chiral plasmon modes of helical nanorod assemblies is presented. An increased surface plasmon frequency of the electron gas due to the addition of electrons leads to a blue‐shift in the corresponding chiral surface plasmon modes. The mechanism behind the shift in plasmonic chirality due to nanorod charging is investigated using theoretical simulations. Charging of the nanorods alters the surface electron density, thereby modifying the plasma frequency and causing a change in the dielectric function. The nature of the plasmon shift and the intensity of chiral surface plasmons are found to be largely dependent on the extent of electron addition. At extended periods of time, the blue shifted band slowly shifts back toward the red, due to transfer of electrons back to the medium, leading to discharging of the nanorods.

Among all new nanomaterials, metal nanoclusters (NCs) have attracted special attention due to their interesting optical properties, among others. Metal NCs have been recently studied and used as sensors for different analytes. However, there is a need to explore the potential of these new sensors in a systematic manner and to develop new systems to broaden the possibilities that sensing offers to the industry. In this work, we show the potential use of repeat protein scaffolds as versatile templates for the synthesis and stabilization of various metal NCs, specifically Au, Ag, and CuNCs. The resulting protein-metal NCs hybrids are evaluated as sensors for different stimuli such as temperature, ions, or reactive oxygen species (ROS). Among the three protein-metal NCs, all performed nicely as temperature sensors, AuNCs responded to metal ions, and AgNCs were able to detect ROS.

We report on the fabrication of 3D printed pH-responsive and antimicrobial hydrogels with micrometer-scale resolution achieved by stereolithography (SLA) 3D printing. The preparation of the hydrogels was optimized by selecting the most appropriate difunctional polyethylene glycol di(meth)acrylates (testing crosslinking agents with chain lengths ranging from 2 up to 14 units ethylene glycol) and introducing acrylic acid (AA) as a monofunctional monomer. As a result of the incorporation of AA, the hydrogels described are able to reversibly swell and shrink upon environmental changes on the pH and the swelling extent is directly related to the amount of AA and can be thus finely tuned. More interestingly, upon optimization of the UV penetration depth employing a photoabsorber (Sudan I), a reliable procedure for the fabrication of 3D objects with high model accuracy is showed. Finally, the antimicrobial properties of all the hydrogels were demonstrated using Staphylococcus aureus as a bacterial model. We found that even those hydrogels with a low amount of AA monomeric units presented excellent antimicrobial properties against S. aureus.

Significance: This contribution reports on the application of gold nanorods to the detection of amyloids in Parkinson’s and prion diseases. We found that gold nanorods show no interaction with monomeric proteins but adsorb onto helical protein fibrils. Chiral amyloid templates induce helical arrangement of nanorods, giving rise to intense optical activity at the plasmon resonance wavelengths. This report shows the use of protein fibrils as templates for chiral nanoparticle assembly and development of a biodetection technique. We show this effect on a model recombinant protein, α-synuclein (involved in Parkinson’s disease), using CD, cryogenic transmission EM tomography, and theoretical simulations supporting the experimental findings. We additionally show application to identify patients with Parkinson’s disease from human brain homogenates.