Self-assembled peptide hydrogels have emerged in recent years as the new paradigm in biomaterials research. We have contributed to this field the development of hydrogels based on dehydrodipeptides N-capped with naproxen. The dehydrodipeptide hydrogels can be loaded with drugs, thus being potential nanocarriers for drug delivery. In this work novel dehydrodipeptides containing tyrosine and aspartic acid amino acid residues N-capped with naproxen and C-terminal dehydrophenylalanine were prepared and characterized. Superparamagnetic iron oxide nanoparticles (SPIONs) were incorporated into the dehydrodipeptide-based hydrogels and their effect on the self-assembly, structure and rheological and magnetic properties of the hydrogels was studied. Magnetic hydrogels, with incorporated SPIONs, displayed concentration-dependent T2-MRI contrast enhancement. Moreover, upon magnetic excitation (alternating magnetic field –AMF–) the SPIONs were able to generate a significant amount of heat. Hence, magnetic hyperthermia can be used as a remote trigger for release of drug cargos and SPIONs incorporated into the self-assembled dehydrodipeptide hydrogels.

The use of peptide–drug conjugates is emerging as a powerful strategy for targeted drug delivery. Previously, we have found that peptides conjugated to a non-steroidal anti-inflammatory drug (NSAID), more specifically naproxen–dehydrodipeptide conjugates, readily form nanostructured fibrilar supramolecular hydrogels. These hydrogels were revealed as efficacious nano-carriers for drug delivery applications. Moreover, the incorporation of superparamagnetic iron oxide nanoparticles (SPIONs) rendered the hydrogels responsive to external magnetic fields, undergoing gel-to-solution phase transition upon remote magnetic excitation. Thus, magnetic dehydrodipeptide-based hydrogels may find interesting applications as responsive Magnetic Resonance Imaging (MRI) contrast agents and for magnetic hyperthermia-triggered drug-release applications. Supramolecular hydrogels where the hydrogelator molecule is endowed with intrinsic pharmacological properties can potentially fulfill a dual function in drug delivery systems as (passive) nanocariers for incorporated drugs and as active drugs themselves. In this present study, we investigated the pharmacological activities of a panel of naproxen–dehydrodipeptide conjugates, previously studied for their hydrogelation ability and as nanocarriers for drug-delivery applications. A focused library of dehydrodipeptides, containing N-terminal canonical amino acids (Phe, Tyr, Trp, Ala, Asp, Lys, Met) N-capped with naproxen and linked to a C-terminal dehydroaminoacid (ΔPhe, ΔAbu), were evaluated for their anti-inflammatory and anti-cancer activities, as well as for their cytotoxicity to non-cancer cells, using a variety of enzymatic and cellular assays. All compounds except one were able to significantly inhibit lipoxygenase (LOX) enzyme at a similar level to naproxen. One of the compounds 4 was able to inhibit the cyclooxygenase-2 (COX-2) to a greater extent than naproxen, without inhibiting cyclooxygenase-1 (COX-1), and therefore is a potential lead in the search for selective COX-2 inhibitors. This hydrogelator is a potential candidate for dual COX/LOX inhibition as an optimised strategy for treating inflammatory conditions.

Abstract. Liver diseases have severe patients' consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

Self-assembled peptide-based hydrogels are archetypical nanostructured materials with a plethora of foreseeable applications in nanomedicine and as biomaterials. N-protected di- and tri-peptides are effective minimalist (molecular) hydrogelators. Independent variation of the capping group, peptide sequence and side chain modifications allows a wide chemical space to be explored and hydrogel properties to be tuned. In this work, we report the synthesis of a focused library of dehydrodipeptides N-protected with 1-naphthoyl and 2-naphthylacetyl groups. The 2-naphthylacetyl group was extensively reported for preparation of peptide-based self-assembled hydrogels, whereas the 1-naphthaloyl group was largely overlooked, owing presumably to the lack of a methylene linker between the naphthalene aromatic ring and the peptide backbone. Interestingly, dehydrodipeptides N-capped with the 1-naphthyl moiety afford stronger gels, at lower concentrations, than the 2-naphthylacetyl-capped dehydrodipeptides. Fluorescence and circular dichroism spectroscopy showed that the self-assembly of the dehydrodipeptides is driven by intermolecular aromatic π–π stacking interactions. Molecular dynamics simulations revealed that the 1-naphthoyl group allows higher order aromatic π–π stacking of the peptide molecules than the 2-naphthylacetyl group, together with hydrogen bonding of the peptide scaffold. The nanostructure of the gel networks was studied by TEM and STEM microscopy and was found to correlate well with the elasticity of the gels. This study contributes to understanding the interplay between peptide and capping group structure on the formation of self-assembled low-molecular-weight peptide hydrogels. Moreover, the results presented here add the 1-naphthoyl group to the palette of capping groups available for the preparation of efficacious low-molecular-weight peptide-based hydrogels.

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This paper describes a tool-supported method for the formal verification of timed properties of HTL programs, supported by the automated translation tool HTL2XTA, which extracts from a HTL program (i) an Uppaal model and (ii) a set of properties that state the compliance of the model with certain automatically inferred temporal constraints. These can be manually extended with other temporal properties provided by the user. The paper introduces the details of the proposed mechanisms as well as the results of our experimental validation.