Phytochemical Composition, Anti-Inflammatory Property, and Anti-Atopic Effect of Chaetomorpha linum Extract.

Utilizing plant-based resources, particularly their by-products, aligns with sustainability principles and circular bioeconomy, contributing to environmental preservation. The therapeutic potential of plant extracts is garnering increasing interest, and this study aimed to demonstrate promising outcomes from an extract obtained from an underutilized plant waste. Chaetomorpha linum, an invasive macroalga found in the Orbetello Lagoon, thrives in eutrophic conditions, forming persistent mats covering approximately 400 hectares since 2005. The biomass of C. linum undergoes mechanical harvesting and is treated as waste, requiring significant human efforts and economic resources-A critical concern for municipalities. Despite posing challenges to local ecosystems, the study identified C. linum as a natural source of bioactive metabolites. Phytochemical characterization revealed lipids, amino acids, and other compounds with potential anti-inflammatory activity in C. linum extract. In vitro assays with LPS-stimulated RAW 264.7 and TNF-α/IFN-γ-stimulated HaCaT cells showed the extract inhibited reactive oxygen species (ROS), nitric oxide (NO), and prostaglandin E2 (PGE2) productions, and reduced inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expressions via NF-κB nuclear translocation, in RAW 264.7 cells. It also reduced chemokines (TARC/CCL17, RANTES/CCL5, MCP-1/CCL2, and IL-8) and the cytokine IL-1ß production in HaCaT cells, suggesting potential as a therapeutic candidate for chronic diseases like atopic dermatitis. Finally, in silico studies indicated palmitic acid as a significant contributor to the observed effect. This research not only uncovered the untapped potential of C. linum but also laid the foundation for its integration into the circular bioeconomy, promoting sustainable practices, and innovative applications across various industries.

Machine learning application for patient stratification and phenotype/genotype investigation in a rare disease.

Alkaptonuria (AKU, OMIM: 203500) is an autosomal recessive disorder caused by mutations in the Homogentisate 1,2-dioxygenase (HGD) gene. A lack of standardized data, information and methodologies to assess disease severity and progression represents a common complication in ultra-rare disorders like AKU. This is the reason why we developed a comprehensive tool, called ApreciseKUre, able to collect AKU patients deriving data, to analyse the complex network among genotypic and phenotypic information and to get new insight in such multi-systemic disease. By taking advantage of the dataset, containing the highest number of AKU patient ever considered, it is possible to apply more sophisticated computational methods (such as machine learning) to achieve a first AKU patient stratification based on phenotypic and genotypic data in a typical precision medicine perspective. Thanks to our sufficiently populated and organized dataset, it is possible, for the first time, to extensively explore the phenotype-genotype relationships unknown so far. This proof of principle study for rare diseases confirms the importance of a dedicated database, allowing data management and analysis and can be used to tailor treatments for every patient in a more effective way.

Pharmacological Chaperones and Protein Conformational Diseases: Approaches of Computational Structural Biology.

Whenever a protein fails to fold into its native structure, a profound detrimental effect is likely to occur, and a disease is often developed. Protein conformational disorders arise when proteins adopt abnormal conformations due to a pathological gene variant that turns into gain/loss of function or improper localization/degradation. Pharmacological chaperones are small molecules restoring the correct folding of a protein suitable for treating conformational diseases. Small molecules like these bind poorly folded proteins similarly to physiological chaperones, bridging non-covalent interactions (hydrogen bonds, electrostatic interactions, and van der Waals contacts) loosened or lost due to mutations. Pharmacological chaperone development involves, among other things, structural biology investigation of the target protein and its misfolding and refolding. Such research can take advantage of computational methods at many stages. Here, we present an up-to-date review of the computational structural biology tools and approaches regarding protein stability evaluation, binding pocket discovery and druggability, drug repurposing, and virtual ligand screening. The tools are presented as organized in an ideal workflow oriented at pharmacological chaperones' rational design, also with the treatment of rare diseases in mind.

Genetic Analysis of Patients with Congenital Hypogonadotropic Hypogonadism: A Case Series.

Congenital hypogonadotropic hypogonadism (cHH)/Kallmann syndrome (KS) is a rare genetic disorder with variable penetrance and a complex inheritance pattern. Consequently, it does not always follow Mendelian laws. More recently, digenic and oligogenic transmission has been recognized in 1.5-15% of cases. We report the results of a clinical and genetic investigation of five unrelated patients with cHH/KS analyzed using a customized gene panel. Patients were diagnosed according to the clinical, hormonal, and radiological criteria of the European Consensus Statement. DNA was analyzed using next-generation sequencing with a customized panel that included 31 genes. When available, first-degree relatives of the probands were also analyzed to assess genotype-phenotype segregation. The consequences of the identified variants on gene function were evaluated by analyzing the conservation of amino acids across species and by using molecular modeling. We found one new pathogenic variant of the CHD7 gene (c.576T>A, p.Tyr1928) and three new variants of unknown significance (VUSs) in IL17RD (c.960G>A, p.Met320Ile), FGF17 (c.208G>A, p.Gly70Arg), and DUSP6 (c.434T>G, p.Leu145Arg). All were present in the heterozygous state. Previously reported heterozygous variants were also found in the PROK2 (c.163del, p.Ile55*), CHD7 (c.c.2750C>T, p.Thr917Met and c.7891C>T, p.Arg2631*), FLRT3 (c.1106C>T, p.Ala369Val), and CCDC103 (c.461A>C, p.His154Pro) genes. Molecular modeling, molecular dynamics, and conservation analyses were performed on three out of the nine variants identified in our patients, namely, FGF17 (p.Gly70Arg), DUSP6 (p.Leu145Arg), and CHD7 p.(Thr917Met). Except for DUSP6, where the L145R variant was shown to disrupt the interaction between ß6 and ß3, needed for extracellular signal-regulated kinase 2 (ERK2) binding and recognition, no significant changes were identified between the wild-types and mutants of the other proteins. We found a new pathogenic variant of the CHD7 gene. The molecular modeling results suggest that the VUS of the DUSP6 (c.434T>G, p.Leu145Arg) gene may play a role in the pathogenesis of cHH. However, our analysis indicates that it is unlikely that the VUSs for the IL17RD (c.960G>A, p.Met320Ile) and FGF17 (c.208G>A, p.Gly70Arg) genes are involved in the pathogenesis of cHH. Functional studies are needed to confirm this hypothesis.

Towards a Long-Read Sequencing Approach for the Molecular Diagnosis of RPGRORF15 Genetic Variants.

Sequencing of the low-complexity ORF15 exon of RPGR, a gene correlated with retinitis pigmentosa and cone dystrophy, is difficult to achieve with NGS and Sanger sequencing. False results could lead to the inaccurate annotation of genetic variants in dbSNP and ClinVar databases, tools on which HGMD and Ensembl rely, finally resulting in incorrect genetic variants interpretation. This paper aims to propose PacBio sequencing as a feasible method to correctly detect genetic variants in low-complexity regions, such as the ORF15 exon of RPGR, and interpret their pathogenicity by structural studies. Biological samples from 75 patients affected by retinitis pigmentosa or cone dystrophy were analyzed with NGS and repeated with PacBio. The results showed that NGS has a low coverage of the ORF15 region, while PacBio was able to sequence the region of interest and detect eight genetic variants, of which four are likely pathogenic. Furthermore, molecular modeling and dynamics of the RPGR Glu-Gly repeats binding to TTLL5 allowed for the structural evaluation of the variants, providing a way to predict their pathogenicity. Therefore, we propose PacBio sequencing as a standard procedure in diagnostic research for sequencing low-complexity regions such as RPGRORF15, aiding in the correct annotation of genetic variants in online databases.

An improved NMR approach for metabolomics of intact serum samples.

NMR metabolomics has inherent capabilities for studying biofluids, such as reproducibility, minimal sample preparation, non-destructiveness, and molecular structure elucidation; however, reliable quantitation of metabolites is still a challenge because of the complex matrix of the samples. The serum is one of the most common samples in clinical studies but possibly the most difficult for NMR analysis because of the high content of proteins, which hampers the detection and quantification of metabolites. Different processes for protein removal, such as ultrafiltration and precipitation, have been proposed, but require sample manipulation, increase time and cost, and possibly lead to loss of information in the metabolic profile. Alternative methods that rely on filtering protein signals by NMR pulse sequencing are commonly used, but standardisation of acquisition parameters and spectra calibration is far from being reached. The present technical note is a critical assessment of the sparsely suggested calibrants, pulse sequences and acquisition parameters toward an optimised combination of the three for accurate and reproducible quantification of metabolites in intact serum.

Untargeted NMR Metabolomics Reveals Alternative Biomarkers and Pathways in Alkaptonuria.

Alkaptonuria (AKU) is an ultra-rare metabolic disease caused by the accumulation of homogentisic acid (HGA), an intermediate product of phenylalanine and tyrosine degradation. AKU patients carry variants within the gene coding for homogentisate-1,2-dioxygenase (HGD), which are responsible for reducing the enzyme catalytic activity and the consequent accumulation of HGA and formation of a dark pigment called the ochronotic pigment. In individuals with alkaptonuria, ochronotic pigmentation of connective tissues occurs, leading to inflammation, degeneration, and eventually osteoarthritis. The molecular mechanisms underlying the multisystemic development of the disease severity are still not fully understood and are mostly limited to the metabolic pathway segment involving HGA. In this view, untargeted metabolomics of biofluids in metabolic diseases allows the direct investigation of molecular species involved in pathways alterations and their interplay. Here, we present the untargeted metabolomics study of AKU through the nuclear magnetic resonance of urine from a cohort of Italian patients; the study aims to unravel molecular species and mechanisms underlying the AKU metabolic disorder. Dysregulation of metabolic pathways other than the HGD route and new potential biomarkers beyond homogentisate are suggested, contributing to a more comprehensive molecular signature definition for AKU and the development of future adjuvant treatment.

Alteration of the Nucleotide Excision Repair (NER) Pathway in Soft Tissue Sarcoma.

Clinical responses to anticancer therapies in advanced soft tissue sarcoma (STS) are unluckily restricted to a small subgroup of patients. Much of the inter-individual variability in treatment efficacy is as result of polymorphisms in genes encoding proteins involved in drug pharmacokinetics and pharmacodynamics. The nucleotide excision repair (NER) system is the main defense mechanism for repairing DNA damage caused by carcinogens and chemotherapy drugs. Single nucleotide polymorphisms (SNPs) of NER pathway key genes, altering mRNA expression or protein activity, can be significantly associated with response to chemotherapy, toxicities, tumor relapse or risk of developing cancer. In the present study, in a cohort of STS patients, we performed DNA extraction and genotyping by SNP assay, RNA extraction and quantitative real-time reverse transcription PCR (qPCR), a molecular dynamics simulation in order to characterize the NER pathway in STS. We observed a severe deregulation of the NER pathway and we describe for the first time the effect of SNP rs1047768 in the ERCC5 structure, suggesting a role in modulating single-stranded DNA (ssDNA) binding. Our results evidenced, for the first time, the correlation between a specific genotype profile of ERCC genes and proficiency of the NER pathway in STS.

Interactive alkaptonuria database: investigating clinical data to improve patient care in a rare disease.

Alkaptonuria (AKU) is an ultrarare autosomal recessive disorder (MIM 203500) that is caused byby a complex set of mutations in homogentisate 1,2-dioxygenasegene and consequent accumulation of homogentisic acid (HGA), causing a significant protein oxidation. A secondary form of amyloidosis was identified in AKU and related to high circulating serum amyloid A (SAA) levels, which are linked with inflammation and oxidative stress and might contribute to disease progression and patients' poor quality of life. Recently, we reported that inflammatory markers (SAA and chitotriosidase) and oxidative stress markers (protein thiolation index) might be disease activity markers in AKU. Thanks to an international network, we collected genotypic, phenotypic, and clinical data from more than 200 patients with AKU. These data are currently stored in our AKU database, named ApreciseKUre. In this work, we developed an algorithm able to make predictions about the oxidative status trend of each patient with AKU based on 55 predictors, namely circulating HGA, body mass index, total cholesterol, SAA, and chitotriosidase. Our general aim is to integrate the data of apparently heterogeneous patients with AKUAKU by using specific bioinformatics tools, in order to identify pivotal mechanisms involved in AKU for a preventive, predictive, and personalized medicine approach to AKU.-Cicaloni, V., Spiga, O., Dimitri, G. M., Maiocchi, R., Millucci, L., Giustarini, D., Bernardini, G., Bernini, A., Marzocchi, B., Braconi, D., Santucci, A. Interactive alkaptonuria database: investigating clinical data to improve patient care in a rare disease.

Molecular definition of the interaction between a tumor-specific tetrabranched peptide and LRP6 receptor.

The tumor-specific tetrabranched peptide NT4 binds membrane sulfate glycosaminoglycans and receptors belonging to the low density lipoprotein receptor-related protein (LRP) family, like LRP6, which are overexpressed in cancer. The binding occurs through a multimeric positively-charged motif of NT4 that interacts with negatively charged motives in both glycosaminoglycans and LRP receptors. LRP6 has an essential function in canonical Wnt signaling, acting together with receptors of the Frizzled family as coreceptor for Wnt ligands. The extracellular domain of LRP6 contains four YWTD ß-propellers, which are fundamental for interactions with ligands, such as Wnt and Wnt inhibitors. To investigate the molecular interactions between the NT4 peptide and LRP6 receptor, we synthesized a library of epitope mapping peptides reproducing the YWTD ß-propeller 3 and 4 of LRP6. The peptides that showed to bind NT4 represented the portion of LRP6 located on the top face of ß-propeller 3 and contained negatively charged residues, including glutamic acid-708 which is known to be involved in Wnt3a interaction. The results pave the way for a possible development of peptide inhibitors of Wnt3a pathway to be used as drugs in oncology.

The patient's pathway for breast cancer in the COVID-19 era: An Italian single-center experience.

COVID-19 has been declared a pandemic by the World Health Organization. As of April 1, 2020, Italy was the country with the second highest number of cases in the world. The spread of COVID-19 has required a rapid reorganization of health service delivery in face of the pandemic. Breast cancer units have reprioritized their workload to guarantee the health of oncologic patients at the highest risk and regular screening activities. However, at the end of the pandemic emergency, many benign and reconstructive cases will return to our attention and their surgical treatment will be necessary as soon as possible.

Near-infrared quantum dots labelled with a tumor selective tetrabranched peptide for in vivo imaging.

BACKGROUND: Near-infrared quantum dots (NIR QDs) are a new class of fluorescent labels with excellent bioimaging features, such as high fluorescence intensity, good fluorescence stability, sufficient electron density, and strong tissue-penetrating ability. For all such features, NIR QDs have great potential for early cancer diagnosis, in vivo tumor imaging and high resolution electron microscopy studies on cancer cells. RESULTS: In the present study we constructed NIR QDs functionalized with the NT4 cancer-selective tetrabranched peptides (NT4-QDs). We observed specific uptake of NT4-QDs in human cancer cells in in vitro experiments and a much higher selective accumulation and retention of targeted QDs at the tumor site, compared to not targeted QDs, in a colon cancer mouse model. CONCLUSIONS: NIR QDs labelled with the tetrabranched NT4 peptide have very promising performance for selective addressing of tumor cells in vitro and in vivo, proving rising features of NT4-QDs as theranostics.

Investigations into the killing activity of an antimicrobial peptide active against extensively antibiotic-resistant K. pneumon iae and P. aeruginosa.

SET-M33 is a multimeric antimicrobial peptide active against Gram-negative bacteria in vitro and in vivo. Insights into its killing mechanism could elucidate correlations with selectivity. SET-M33 showed concentration-dependent bactericidal activity against colistin-susceptible and resistant isolates of P. aeruginosa and K. pneumoniae. Scanning and transmission microscopy studies showed that SET-M33 generated cell blisters, blebs, membrane stacks and deep craters in K. pneumoniae and P. aeruginosa cells. NMR analysis and CD spectra in the presence of sodium dodecyl sulfate micelles showed a transition from an unstructured state to a stable α-helix, driving the peptide to arrange itself on the surface of micelles. SET-M33 kills Gram-negative bacteria after an initial interaction with bacterial LPS. The molecule becomes then embedded in the outer membrane surface, thereby impairing cell function. This activity of SET-M33, in contrast to other similar antimicrobial peptides such as colistin, does not generate resistant mutants after 24h of exposure, non-specific interactions or toxicity against eukaryotic cell membranes, suggesting that SET-M33 is a promising new option for the treatment of Gram-negative antibiotic-resistant infections.

Hot spot mapping of protein surfaces with TEMPOL: Bovine pancreatic RNase A as a model system.

TEMPOL spin-label has been used to identify surface exposure of protein nuclei from NMR analysis of the induced paramagnetic relaxation enhancements (PRE). The absence of linear dependence between atom depths and observed PRE reveals that specific mechanisms drive the approach of the paramagnet to the protein surface. RNase A represents a unique protein system to explore the fine details of the information offered by TEMPOL induced PRE, due to the abundance of previous results, obtained in solution and in the crystal, dealing with surface dynamics behavior of this protein. MD simulations in explicit solvent have been performed, also in the presence of TEMPOL, in order to delineate the role of intermolecular hydrogen bonds (HB) on PRE extents. Comparison of our results with the ones obtained from multiple solvent crystal structure (MSCS) studies yields information on the specificities that these two techniques have for characterizing protein-ligand interactions, a fundamental step in the development of reliable surface druggability predictors.

Homogentisic acid induces aggregation and fibrillation of amyloidogenic proteins.

BACKGROUND: Alkaptonuria (AKU) is an ultra-rare inborn error of metabolism characterized by homogentisic acid (HGA) accumulation due to a deficient activity of the homogentisate 1.2-dioxygenase (HGD) enzyme. This leads to the production of dark pigments that are deposited onto connective tissues, a condition named 'ochronosis' and whose mechanisms are not completely clear. Recently, the potential role of hitherto unidentified proteins in the ochronotic process was hypothesized, and the presence of Serum Amyloid A (SAA) in alkaptonuric tissues was reported, allowing the classification of AKU as a novel secondary amyloidosis. METHODS: Gel electrophoresis, Western Blot, Congo Red-based assays and electron microscopy were used to investigate the effects of HGA on the aggregation and fibrillation propensity of amyloidogenic proteins and peptides [Aß(1-42), transthyretin, atrial natriuretic peptide, α-synuclein and SAA]. LC/MS and in silico analyses were undertaken to identify possible binding sites for HGA (or its oxidative metabolite, a benzoquinone acetate or BQA) in SAA. RESULTS: We found that HGA might act as an amyloid aggregation enhancer in vitro for all the tested proteins and peptides in a time- and dose- dependent fashion, and identified a small crevice at the interface between two HGD subunits as a candidate binding site for HGA/BQA. CONCLUSIONS: HGA might be an important amyloid co- component playing significant roles in AKU amyloidosis. GENERAL SIGNIFICANCE: Our results provide a possible explanation for the clinically verified onset of amyloidotic processes in AKU and might lay the basis to setup proper pharmacological approaches to alkaptonuric ochronosis, which are still lacking.

ApreciseKUre: an approach of Precision Medicine in a Rare Disease.

BACKGROUND: Alkaptonuria (AKU; OMIM:203500) is a classic Mendelian genetic disorder described by Garrod already in 1902. It causes urine to turn black upon exposure to air and also leads to ochronosis as well as early osteoarthritis. Our objective is the implementation of a Precision Medicine (PM) approach to AKU. We present here a novel ApreciseKUre database facilitating the collection, integration and analysis of patient data in order to create an AKU-dedicated "PM Ecosystem" in which genetic, biochemical and clinical resources can be shared among registered researchers. In order to exploit the ApreciseKUre database, we developed an analytic method based on Pearson's correlation coefficient and P value that generates as refreshable correlation matrix. A complete statistical analysis is obtained by associating every pair of parameters to examine the dependence between multiple variables at the same time. SHORT CONCLUSIONS: Employing this analytic approach, we showed that some clinically used biomarkers are not suitable as prognostic biomarkers in AKU for a more reliable patients' clinical monitoring. We believe this database could be a good starting point for the creation of a new clinical management tool in AKU, which will lead to the development of a deeper knowledge network on the disease and will advance its treatment. Moreover, our approach can serve as a personalization model paradigm for other inborn errors of metabolism or rare diseases in general.

Searching for protein binding sites from Molecular Dynamics simulations and paramagnetic fragment-based NMR studies.

Hotspot delineation on protein surfaces represents a fundamental step for targeting protein-protein interfaces. Disruptors of protein-protein interactions can be designed provided that the sterical features of binding pockets, including the transient ones, can be defined. Molecular Dynamics, MD, simulations have been used as a reliable framework for identifying transient pocket openings on the protein surface. Accessible surface area and intramolecular H-bond involvement of protein backbone amides are proposed as descriptors for characterizing binding pocket occurrence and evolution along MD trajectories. TEMPOL induced paramagnetic perturbations on (1)H-(15)N HSQC signals of protein backbone amides have been analyzed as a fragment-based search for surface hotspots, in order to validate MD predicted pockets. This procedure has been applied to CXCL12, a small chemokine responsible for tumor progression and proliferation. From combined analysis of MD data and paramagnetic profiles, two CXCL12 sites suitable for the binding of small molecules were identified. One of these sites is the already well characterized CXCL12 region involved in the binding to CXCR4 receptor. The other one is a transient pocket predicted by Molecular Dynamics simulations, which could not be observed from static analysis of CXCL12 PDB structures. The present results indicate how TEMPOL, instrumental in identifying this transient pocket, can be a powerful tool to delineate minor conformations which can be highly relevant in dynamic discovery of antitumoral drugs.

Atom depth analysis delineates mechanisms of protein intermolecular interactions.

The systematic analysis of amino acid distribution, performed inside a large set of resolved protein structures, sheds light on possible mechanisms driving non random protein-protein approaches. Protein Data Bank entries have been selected using as filters a series of restrictions ensuring that the shape of protein surface is not modified by interactions with large or small ligands. 3D atom depth has been evaluated for all the atoms of the 2,410 selected structures. The amino acid relative population in each of the structural layers formed by grouping atoms on the basis of their calculated depths, has been evaluated. We have identified seven structural layers, the inner ones reproducing the core of proteins and the outer one incorporating their most protruding moieties. Quantitative analysis of amino acid contents of structural layers identified, as expected, different behaviors. Atoms of Q, R, K, N, D residues are increasingly more abundant in going from core to surfaces. An opposite trend is observed for V, I, L, A, C, and G. An intermediate behavior is exhibited by P, S, T, M, W, H, F and Y. The outer structural layer hosts predominantly E and K residues whose charged moieties, protruding from outer regions of the protein surface, reorient free from steric hindrances, determining specific electrodynamics maps. This feature may represent a protein signature for long distance effects, driving the formation of encounter complexes and the eventual short distance approaches that are required for protein-protein functional interactions.

Probing the protein space for extending the detection of weak homology folds.

Redundancy of prediction methods has been used to explore the occurrence of weak homology protein motifs. A hybrid template-based algorithm has been implemented to predict different layers of protein structure by detecting domain building sub-structures, which share low sequence identity. Physicochemical determinants, secondary structure profiles, and multiple alignments have been analyzed to generate a broad set of structural sub-domains. Then, intensive computing procedures generated all the various tridimensional folds on the basis of secondary structure predictions, fragment assembly and detection of structural homologs. The proposed algorithm not only identifies common protein sub-structures, but also detects higher order architectures such as domain superfamilies/superfolds by linking backbone trajectories of supersecondary structures. Applying rigid transformation protocols, population of the detected domain building models with an average root mean square deviation from native structures of 2.3Å and an average template modeling score from native structures of 0.43 has been obtained. The fold detection algorithm here proposed yields more accurate results than previously proposed methods, predicting structural homology also for proteins sharing less than 20% sequence identity. Our tools are freely available at http://www.acbrc.org/tools.html.

Structure-Function Relationship of Homogentisate 1,2-dioxygenase: Understanding the Genotype-Phenotype Correlations in the Rare Genetic Disease Alkaptonuria.

Alkaptonuria (AKU), a rare genetic disorder, is characterized by the accumulation of homogentisic acid (HGA) in organs, which occurs because the homogentisate 1,2-dioxygenase (HGD) enzyme is not functional due to gene variants. Over time, HGA oxidation and accumulation cause the formation of the ochronotic pigment, a deposit that provokes tissue degeneration and organ malfunction. Here, we report a comprehensive review of the variants so far reported, the structural studies on the molecular consequences of protein stability and interaction, and molecular simulations for pharmacological chaperones as protein rescuers. Moreover, evidence accumulated so far in alkaptonuria research will be re-proposed as the bases for a precision medicine approach in a rare disease.