Alzheimer’s disease (AD) is a neurodegenerative pathology characterized by the presence of neurofibrillary tangles and amyloid plaques, the latter mainly composed of Aβ(1–40) and Aβ(1–42) peptides. The control of the Aβ aggregation process as a therapeutic strategy for AD has prompted the interest to investigate the conformation of the Aβ peptides, taking advantage of computational and experimental techniques. Mixtures composed of systematically different proportions of HFIP and water have been used to monitor, by NMR, the conformational transition of the Aβ(1–42) from soluble α-helical structure to β-sheet aggregates. In the previous studies, 50/50 HFIP/water proportion emerged as the solution condition where the first evident Aβ(1–42) conformational changes occur. In the hypothesis that this solvent reproduces the best condition to catch transitional helical-β-sheet Aβ(1–42) conformations, in this study, we report an extensive NMR conformational analysis of Aβ(1–42) in 50/50 HFIP/water v/v. Aβ(1–42) structure was solved by us, giving evidence that the evolution of Aβ(1–42) peptide from helical to the β-sheet may follow unexpected routes. Molecular dynamics simulations confirm that the structural model we calculated represents a starting condition for amyloid fibrils formation.

Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative pathology of the upper or lower motor neuron. Evaluation of ALS progression is based on clinical outcomes considering the impairment of body sites. ALS has been extensively investigated in the pathogenetic mechanisms and the clinical profile; however, no molecular biomarkers are used as diagnostic criteria to establish the ALS pathological staging. Using the source-reconstructed magnetoencephalography (MEG) approach, we demonstrated that global brain hyperconnectivity is associated with early and advanced clinical ALS stages. Using nuclear magnetic resonance (¹H-NMR) and high resolution mass spectrometry (HRMS) spectroscopy, here we studied the metabolomic profile of ALS patients’ sera characterized by different stages of disease progression—namely early and advanced. Multivariate statistical analysis of the data integrated with the network analysis indicates that metabolites related to energy deficit, abnormal concentrations of neurotoxic metabolites and metabolites related to neurotransmitter production are pathognomonic of ALS in the advanced stage. Furthermore, analysis of the lipidomic profile indicates that advanced ALS patients report significant alteration of phosphocholine (PCs), lysophosphatidylcholine (LPCs), and sphingomyelin (SMs) metabolism, consistent with the exigency of lipid remodeling to repair advanced neuronal degeneration and inflammation.

The supramolecular structure in peptides’ prolonged-released gel formulations is the most critical parameter for the determination of the pharmaceutical profile of the drug. Here, we report our investigation on lanreotide Autogel as a case study. For the first time, we describe the use of the pulsed field gradient (PFG) diffusion-ordered spectroscopy (DOSY) magic-angle spinning NMR to characterize the supramolecular self-assembly and molecular mobility of different samples of lanreotide Autogel formulations prepared according to different formulation protocols. The diffusion coefficient was used to calculate the hydrodynamic radii of supramolecular assemblies and build relative molecular models. DOSY data were integrated with NMR imaging (MRI) measurements and atomic force microscopy (AFM) imaging.

Antibodies are the macromolecules of choice to ensure specific recognition of biomarkers in biological assays. However, they present a range of shortfalls including a relatively high production cost and limited tissue penetration. Peptides are relatively small molecules able to reproduce sequences of highly specific paratopes and, although they have less biospecificity than antibodies, they offer advantages like ease of synthesis, modifications of their amino acid sequences and tagging with fluorophores and other molecules required for detection. This work presents a strategy to design peptide sequences able to recognize the CD44 hyaluronic acid receptor present in the plasmalemma of a range of cells including human bone marrow stromal mesenchymal cells. The protocol of identification of the optimal amino acid sequence was based on the combination of rational design and in silico methodologies. This protocol led to the identification of two peptide sequences which were synthesized and tested on human bone marrow mesenchymal stromal cells (hBM-MSCs) for their ability to ensure specific binding to the CD44 receptor. Of the two peptides, one binds CD44 with sensitivity and selectivity, thus proving its potential to be used as a suitable alternative to this antibody in conventional immunostaining. In the context of regenerative medicine, the availability of this peptide could be harnessed to functionalize tissue engineering scaffolds to anchor stem cells as well as to be integrated into systems such as cell sorters to efficiently isolate MSCs from biological samples including various cell subpopulations. The data here reported can represent a model for developing peptide sequences able to recognize hBM-MSCs and other types of cells and for their integration in a range of biomedical applications.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus identified as the cause of the coronavirus outbreak in December 2019 (COVID-19). Like all the RNA viruses, SARS-CoV-2 constantly evolves through mutations in its genome, accumulating 1–2 nucleotide changes every month, giving the virus a selective advantage through enhanced transmissibility, greater pathogenicity, and the possibility of circumventing immunity previously acquired by an individual either by natural infection or by vaccination. Several SARS-CoV-2 variants of concern (VoC) have been identified, among which we find Alpha (Lineage B.1.1.7), Beta (Lineage B.1.351), and Gamma (Lineage P.1) variants. Most of the mutations occur in the spike (S) protein, a surface glycoprotein that plays a crucial role in viral infection; the S protein binds the host cell receptor, the angiotensin-converting enzyme of type 2 (ACE2) via the receptor binding domain (RBD) and catalyzes the fusion of the viral membrane with the host cell. In this work, we present the development of a simplified system that would afford to study the change in the SARS-CoV-2 S RBD/ACE2 binding related to the frequent mutations. In particular, we synthesized and studied the structure of short amino acid sequences, mimicking the two proteins’ critical portions. Variations in the residues were easily managed through the one-point alteration of the sequences. Nuclear magnetic resonance (NMR) and circular dichroism (CD) spectroscopies provide insights into ACE2 and SARS-CoV-2 S RBD structure with its related three variants (Alpha, Beta, and Gamma). Spectroscopy data supported by molecular dynamics lead to the description of an ACE2/RBD binding model in which the effect of a single amino acid mutation in changing the binding of S protein to the ACE2 receptor is predictable.