Comprehensive Peptide Cyclization Examination Yields Optimized APP Scaffolds with Improved Affinity toward Mint2

The Therapeutic Potential of Novel Carnosine Formulations: Perspectives for Drug Development

Carnosine (beta-alanyl-L-histidine) is an endogenous dipeptide synthesized via the activity of the ATP-dependent enzyme carnosine synthetase 1 and can be found at a very high concentration in tissues with a high metabolic rate, including muscles (up to 20 mM) and brain (up to 5 mM). Because of its well-demonstrated multimodal pharmacodynamic profile, which includes anti-aggregant, antioxidant, and anti-inflammatory activities, as well as its ability to modulate the energy metabolism status in immune cells, this dipeptide has been investigated in numerous experimental models of diseases, including Alzheimer's disease, and at a clinical level. The main limit for the therapeutic use of carnosine is related to its rapid hydrolysis exerted by carnosinases, especially at the plasma level, reason why the development of new strategies, including the chemical modification of carnosine or its vehiculation into innovative drug delivery systems (DDS), aiming at increasing its bioavailability and/or at facilitating the site-specific transport to different tissues, is of utmost importance. In the present review, after a description of carnosine structure, biological activities, administration routes, and metabolism, we focused on different DDS, including vesicular systems and metallic nanoparticles, as well as on possible chemical derivatization strategies related to carnosine. In particular, a basic description of the DDS employed or the derivatization/conjugation applied to obtain carnosine formulations, followed by the possible mechanism of action, is given. To the best of our knowledge, this is the first review that includes all the new formulations of carnosine (DDS and derivatives), allowing a decrease or complete prevention of the hydrolysis of this dipeptide exerted by carnosinases, the simultaneous blood-brain barrier crossing, the maintenance or enhancement of carnosine biological activity, and the site-specific transport to different tissues, which then offers perspectives for the development of new drugs.

Facilitating the structural characterisation of non-canonical amino acids in biomolecular NMR

Peptides and proteins containing non-canonical amino acids (ncAAs) are a large and important class of biopolymers. They include non-ribosomally synthesised peptides, post-translationally modified proteins, expressed or synthesised proteins containing unnatural amino acids, and peptides and proteins that are chemically modified. Here, we describe a general procedure for generating atomic descriptions required to incorporate ncAAs within popular NMR structure determination software such as CYANA, CNS, Xplor-NIH and ARIA. This procedure is made publicly available via the existing Automated Topology Builder (ATB) server (https://atb.uq.edu.au, last access: 17 February 2023) with all submitted ncAAs stored in a dedicated database. The described procedure also includes a general method for linking of side chains of amino acids from CYANA templates. To ensure compatibility with other systems, atom names comply with IUPAC guidelines. In addition to describing the workflow, 3D models of complex natural products generated by CYANA are presented, including vancomycin. In order to demonstrate the manner in which the templates for ncAAs generated by the ATB can be used in practice, we use a combination of CYANA and CNS to solve the structure of a synthetic peptide designed to disrupt Alzheimer-related protein-protein interactions. Automating the generation of structural templates for ncAAs will extend the utility of NMR spectroscopy to studies of more complex biomolecules, with applications in the rapidly growing fields of synthetic biology and chemical biology. The procedures we outline can also be used to standardise the creation of structural templates for any amino acid and thus have the potential to impact structural biology more generally.