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The study of rare diseases is important not only for the individuals affected but also for the advancement of medical knowledge and a deeper understanding of human biology and genetics. The wide repertoire of structural information now available from reliable and accurate prediction methods provides the opportunity to investigate the molecular origins of most of the rare diseases reviewed in the Orpha.net database. Thus, it has been possible to analyze the topology of the pathogenic missense variants found in the 2515 proteins involved in Mendelian rare diseases (MRDs), which form the database for our structural bioinformatics study. The amino acid substitutions responsible for MRDs showed different mutation site distributions at different three-dimensional protein depths. We then highlighted the depth-dependent effects of pathogenic variants for the 20,061 pathogenic variants that are present in our database. The results of this structural bioinformatics investigation are relevant, as they provide additional clues to mitigate the damage caused by MRD.

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Recent studies confirmed that people unexposed to SARS-CoV-2 have preexisting reactivity, probably due to previous exposure to widely circulating common cold coronaviruses. Such preexistent reactivity against SARS-CoV-2 comes from memory T cells that can specifically recognize a SARS-CoV-2 epitope of structural and non-structural proteins and the homologous epitopes from common cold coronaviruses. Therefore, it is important to understand the SARS-CoV-2 cross-reactivity by investigating these protein sequence similarities with those of different circulating coronaviruses. In addition, the emerging SARS-CoV-2 variants lead to an intense interest in whether mutations in proteins (especially in the spike) could potentially compromise vaccine effectiveness. Since it is not clear that the differences in clinical outcomes are caused by common cold coronaviruses, a deeper investigation on cross-reactive T-cell immunity to SARS-CoV-2 is crucial to examine the differential COVID-19 symptoms and vaccine performance. Therefore, the present study can be a starting point for further research on cross-reactive T cell recognition between circulating common cold coronaviruses and SARS-CoV-2, including the most recent variants Delta and Omicron. In the end, a deep learning approach, based on Siamese networks, is proposed to accurately and efficiently calculate a BLAST-like similarity score between protein sequences.

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With a structural bioinformatic approach, we have explored amino acid compositions at PISA defined interfaces between small molecules and proteins that are contained in an optimized subset of 11,351 PDB files. The use of a series of restrictions, to prevent redundancy and biases from interactions between amino acids with charged side chains and ions, yielded a final data set of 45,230 protein-small molecule interfaces. We have compared occurrences of natural amino acids in surface exposed regions and binding sites for all the proteins of our data set. From our structural bioinformatic survey, the most relevant signal arose from the unexpected Gly abundance at enzyme catalytic sites. This finding suggested that Gly must have a fundamental role in stabilizing concave protein surface moieties. Subsequently, we have tried to predict the effect of in silico Gly mutations in hen egg white lysozyme to optimize those conditions that can reshape the protein surface with the appearance of new pockets. Replacing amino acids having bulky side chains with Gly in specific protein regions seems a feasible way for designing proteins with additional surface pockets, which can alter protein surface dynamics, therefore, representing controllable switches for protein activity.

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Understanding the molecular mechanisms that correlate pathologies with missense mutations is of critical importance for disease risk estimations and for devising personalized therapies. Thus, we have performed a bioinformatic survey of ClinVar, a database of human genomic variations, to find signals that can account for missense mutation pathogenicity. Arginine resulted as the most frequently replaced amino acid both in benign and pathogenic mutations. By adding the structural dimension to this investigation to increase its resolution, we found that arginine mutations occurring at the protein-DNA interface increase pathogenicity 6.5 times with respect to benign variants. Glycine is the second amino acid among all the pathological missense mutations. Necessarily replaced by larger amino acids, glycine substitutions perturb the structural stability of proteins and, therefore, their functions, being mostly located in buried protein moieties. Arginine and glycine appear as representative of missense mutations causing respective changes in interaction processes and protein structural features, the two main molecular mechanisms of genome-induced pathologies.

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Correction for 'Exploring exchange processes in proteins by paramagnetic perturbation of NMR spectra' by Yamanappa Hunashal et al., Phys. Chem. Chem. Phys., 2020, 22, 6247-6259, DOI: .

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The recent release of COVID-19 spike glycoprotein allows detailed analysis of the structural features that are required for stabilizing the infective form of its quaternary assembly. Trying to disassemble the trimeric structure of COVID-19 spike glycoprotein, we analyzed single protomer surfaces searching for concave moieties that are located at the three protomer-protomer interfaces. The presence of some druggable pockets at these interfaces suggested that some of the available drugs in Drug Bank could destabilize the quaternary spike glycoprotein formation by binding to these pockets, therefore interfering with COVID-19 life cycle. The approach we propose here can be an additional strategy to fight against the deadly virus. Ligands of COVID-19 spike glycoprotein that we have predicted in the present computational investigation, might be the basis for new experimental studies in vitro and in vivo.

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The effect of extrinsic paramagnetic probes on NMR relaxation rates for surface mapping of proteins and other biopolymers is a widely investigated and powerful NMR technique. Here we describe a new application of those probes. It relies on the setting of the relaxation delay to generate magnetization equilibrium and off-equilibrium conditions, in order to tailor the extent of steady state signal recovery with and without the water-soluble nitroxide Tempol. With this approach it is possible to identify signals whose relaxation is affected by exchange processes and, from the relative assignments, to map the protein residues involved in association or conformational interconversion processes on a micro-to-millisecond time scale. This finding is confirmed by the comparison with the results obtained from relaxation dispersion measurements. This simple and convenient method allows preliminary inspection to highlight regions where structural or chemical exchange events are operative, in order to focus on quantitative subsequent determinations by transverse relaxation dispersion experiments or analogous NMR relaxation studies, and/or to gain insights into the predictions of calculations.

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Nowadays, it is well established that most of the human diseases which are not related to pathogen infections have their origin from DNA disorders. Thus, DNA mutations, waiting for the availability of CRISPR-like remedies, will propagate into proteomics, offering the possibility to select natural or synthetic molecules to fight against the effects of malfunctioning proteins. Drug discovery, indeed, is a flourishing field of biotechnological research to improve human health, even though the development of a new drug is increasingly more expensive in spite of the massive use of informatics in Medicinal Chemistry. CRISPR technology adds new alternatives to cure diseases by removing DNA defects responsible of genome-related pathologies. In principle, the same technology, however, could also be exploited to induce protein mutations whose effects are controlled by the presence of suitable ligands. In this paper, a new idea is proposed for the realization of mutated proteins, on the surface of which more spacious transient pockets are formed and, therefore, are more suitable for hosting drugs. In particular, new allosteric sites are obtained by replacing amino-acids with bulky side chains with glycine, Gly, the smallest natural amino-acid. We also present a machine learning approach to evaluate the druggability score of new (or enlarged) pockets. Preliminary experimental results are very promising, showing that 10% of the sites created by the Gly-pipe software are druggable.

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X-ray structure of methyl-CpG binding domain (MBD) of MeCP2, an intrinsically disordered protein (IDP) involved in Rett syndrome, offers a rational basis for defining the spatial distribution for most of the sites where mutations responsible of Rett syndrome, RTT, occur. We have ascribed pathogenicity for mutations of amino acids bearing positively charged side chains, all located at the protein-DNA interface, as positive charge removal cause reduction of the MeCP2-DNA adduct lifetime. Pathogenicity of the frequent proline replacements, outside the DNA contact moiety of MBD, can be attributed to the role of this amino acid for maintaining both unfolded states for unbound MeCP2 and, at the same time, to favor some higher conformational order for stabilizing structural determinants required by protein activity. These hypotheses can be extended to transcription repressor domain, TRD, the other MeCP2-DNA interaction site and, in general, to all the IDP that interact with nucleic acids.

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Notable advances in treatment have been made and increases in the cure rates of pediatric leukemia have been achieved. However, the majority of children with relapsed disease are not expected to survive, with chemotherapy resistance acting as the principal cause of treatment failure. Interaction between leukemic cells and the bone marrow microenvironment is the primary cause of relapse. It was identified that a multi­protein membrane complex, formed by potassium voltage­gated channel subfamily H member 2 (hERG1) channels, the ß1 integrin subunit and the stromal cell­derived factor 12 (CXCL12) receptor, C­X­C chemokine receptor type 4 (CXCR4), exerts a role in mesenchymal stromal cell (MSC)­mediated chemoresistance in pediatric leukemias. hERG1 blockade was able to overcome chemoresistance in vitro and in vivo. As an alternative strategy to overcome chemoresistance, the present study evaluated the effects of novel tools targeting the CXCR4/CXCL12 axis. The analysis of CXCL12 structural dynamics was used for the selection of a peptide (4­1­17) and a small molecule (8673), which interact with a transient hot spot, identified by a dynamic drug design approach. The present findings indicated that peptide 4­1­17 and small molecule 8673 inhibited leukemia cell proliferation and induced a pro­apoptotic effect, which was not reduced by the presence of MSCs. The combined treatment with 4­1­17 and 8673 had a stronger pro­apoptotic effect, particularly on cells cultured on MSCs in normoxic and hypoxic conditions, and was able to overcome MSC­induced resistance to cytarabine. Overall, the targeting of CXCL12 and the ensuing inhibition of the CXCR4/CXCL12 axis may be proposed as an alternative strategy to overcome chemoresistance in leukemia.

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Oxidative stress and an increase in the levels of free radicals are important markers associated with several pathologies, including Alzheimer's disease, cancer and diabetes. Friedreich's ataxia (FRDA) is an excellent paradigmatic example of a disease in which oxidative stress plays an important, albeit incompletely understood, role. FRDA is a rare genetic neurodegenerative disease that involves the partial silencing of frataxin, a small mitochondrial protein that was completely overlooked before being linked to FRDA. More than 20 years later, we now know how important this protein is in terms of being an essential and vital part of the machinery that produces iron-sulfur clusters in the cell. In this review, we revisit the most important steps that have brought us to our current understanding of the function of frataxin and its role in disease. We discuss the current hypotheses on the role of oxidative stress in FRDA and review some of the existing animal and cellular models. We also evaluate new techniques that can assist in the study of the disease mechanisms, as well as in our understanding of the interplay between primary and secondary phenotypes.

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Purpose: The aim of this article is to report the investigation of the structural features of ABCA4, a protein associated with a genetic retinal disease. A new database collecting knowledge of ABCA4 structure may facilitate predictions about the possible functional consequences of gene mutations observed in clinical practice. Methods: In order to correlate structural and functional effects of the observed mutations, the structure of mouse P-glycoprotein was used as a template for homology modeling. The obtained structural information and genetic data are the basis of our relational database (ABCA4Database). Results: Sequence variability among all ABCA4-deposited entries was calculated and reported as Shannon entropy score at the residue level. The three-dimensional model of ABCA4 structure was used to locate the spatial distribution of the observed variable regions. Our predictions from structural in silico tools were able to accurately link the functional effects of mutations to phenotype. The development of the ABCA4Database gathers all the available genetic and structural information, yielding a global view of the molecular basis of some retinal diseases. Conclusions: ABCA4 modeled structure provides a molecular basis on which to analyze protein sequence mutations related to genetic retinal disease in order to predict the risk of retinal disease across all possible ABCA4 mutations. Additionally, our ABCA4 predicted structure is a good starting point for the creation of a new data analysis model, appropriate for precision medicine, in order to develop a deeper knowledge network of the disease and to improve the management of patients.

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Alkaptonuria (AKU) is an inborn error of metabolism where mutation of homogentisate 1,2-dioxygenase (HGD) gene leads to a deleterious or misfolded product with subsequent loss of enzymatic degradation of homogentisic acid (HGA) whose accumulation in tissues causes ochronosis and degeneration. There is no licensed therapy for AKU. Many missense mutations have been individuated as responsible for quaternary structure disruption of the native hexameric HGD. A new approach to the treatment of AKU is here proposed aiming to totally or partially rescue enzyme activity by targeting of HGD with pharmacological chaperones, i.e. small molecules helping structural stability. Co-factor pockets from oligomeric proteins have already been successfully exploited as targets for such a strategy, but no similar sites are present at HGD surface; hence, transient pockets are here proposed as a target for pharmacological chaperones. Transient pockets are detected along the molecular dynamics trajectory of the protein and filtered down to a set of suitable sites for structural stabilization by mean of biochemical and pharmacological criteria. The result is a computational workflow relevant to other inborn errors of metabolism requiring rescue of oligomeric, misfolded enzymes.

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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.

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The lifetimes of protein-DNA adducts are strictly related to the various protein functions. This feature must be encoded by the amino acids located at the protein-DNA interface. The large number of structurally characterized protein-DNA complexes now available from the Protein Data Bank (PDB) allows extensive structural bioinformatics investigations on protein-DNA interfaces. The modes of protein binding to DNA have been explored by dividing 629 non-redundant PDB files of protein-DNA complexes into separate classes for structural proteins, transcription factors and DNA-related enzymes. From the selected PDB structures, we could define 2953 protein-DNA contact regions. A systematic analysis of amino acid occurrences at these protein-DNA contact regions yielded composition profiles, which are typical for each of the three protein classes. The critical role of some amino acids to influence intermolecular contact lifetimes is discussed here. The occurrence of arginine at the protein-DNA interface, by far the most abundant amino acid in this protein moiety, is found to be the main feature that differentiates proteins from the three classes. Structural proteins and, to a lesser extent, transcription factors exhibit the highest Arg occurrence at protein-DNA contact regions. Reduced Arg/Lys ratios together with increased contents of Asp and Glu are observed in all the DNA-interacting enzymes. The amount of negatively charged side chains, highly conserved among homologous DNA-related enzymes at protein-DNA interfaces, is suggested as a tool to modulate protein mobility along DNA chains. Arg/Lys, Asp/Asn and Glu/Gln substitutions at protein-DNA interfaces may represent a very feasible way to control protein motion on DNA rails.

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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.

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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.

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Genetic code redundancy would yield, on the average, the assignment of three codons for each of the natural amino acids. The fact that this number is observed only for incorporating Ile and to stop RNA translation still waits for an overall explanation. Through a Structural Bioinformatics approach, the wealth of information stored in the Protein Data Bank has been used here to look for unambiguous clues to decipher the rationale of standard genetic code (SGC) in assigning from one to six different codons for amino acid translation. Leu and Arg, both protected from translational errors by six codons, offer the clearest clue by appearing as the most abundant amino acids in protein-protein and protein-nucleic acid interfaces. Other SGC hidden messages have been sought by analyzing, in a protein structure framework, the roles of over- and under-protected amino acids.

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What is the mechanism that determines the denaturation of proteins at low temperatures, which is, by now, recognized as a fundamental property of all proteins? We present experimental evidence that clarifies the role of specific interactions that favor the entrance of water into the hydrophobic core, a mechanism originally proposed by Privalov but never proved experimentally. By using a combination of molecular dynamics simulation, molecular biology, and biophysics, we identified a cluster of negatively charged residues that represents a preferential gate for the entrance of water molecules into the core. Even single-residue mutations in this cluster, from acidic to neutral residues, affect cold denaturation much more than heat denaturation, suppressing cold denaturation at temperatures above zero degrees. The molecular mechanism of the cold denaturation of yeast frataxin is intrinsically different from that of heat denaturation.

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Osteosarcoma (OS) is a highly malignant bone tumour, affecting mainly children and young adults between 10 and 20 years of age. It represents the most frequent primitive malignant tumour of the skeletal system and is characterized by an extremely aggressive clinical course, with rapid development of lung metastases. In the last few years, targeting Src in the treatment of OS has become one of the major challenges in the development of new drugs, since an elevated Src kinase activity has been associated with the development and the maintenance of the OS malignant phenotype. Recently, SI-83, a novel pyrazolo[3,4-d]pyrimidine derivate Src inhibitor, was selected as a promising OS therapeutic drug because of its elevated anti-tumour effects toward human OS. In the present study, gel-based proteomics and phosphoproteomics revealed significant changes in proteins involved in many cancer related processes. We got insight into SI-83 proapoptotic and antiproliferative properties (overrepresentation of GRIA1, GRP78, and CALR and underrepresentation of NPM1, RCN, and P4HB). Nevertheless, the most significant findings of our work are the SI-83 induced dephosphorylation of ARPC5L, a subunit of the actin related Arp2/3 complex, and the decrease of other cytoskeleton proteins. These data, together with a dramatic impairment of SaOS-2 cell migration and adhesion, suggest that SI-83 may have antimetastatic features that enhance its use as a potent OS chemotherapeutic drug.

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