The Dynamics of OXA-23 ß-Lactamase from Acinetobacter baumannii.

Antibiotic resistance is a pressing topic, which also affects ß-lactam antibiotic molecules. Until a few years ago, it was considered no more than an interesting species from an academic point of view, Acinetobacter baumanii is today one of the most serious threats to public health, so much so that it has been declared one of the species for which the search for new antibiotics, or new ways to avoid its resistance, is an absolute priority according to WHO. Although there are several molecular mechanisms that are responsible for the extreme resistance of A. baumanii to antibiotics, a class D ß-lactamase is the main cause for the clinical concern of this bacterial species. In this work, we analyzed the A. baumanii OXA-23 protein via molecular dynamics. The results obtained show that this protein is able to assume different conformations, especially in some regions around the active site. Part of the OXA-23 protein has considerable conformational motility, while the rest is less mobile. The importance of these observations for understanding the functioning mechanism of the enzyme as well as for designing new effective molecules for the treatment of A. baumanii is discussed.

A Gel-Based Proteomic Analysis Reveals Synovial α-Enolase and Fibrinogen ß-Chain Dysregulation in Knee Osteoarthritis: A Controlled Trial.

BACKGROUND: The identification of synovial fluid (SF) biomarkers that could anticipate the diagnosis of osteoarthritis (OA) is gaining increasing importance in orthopaedic clinical practice. This controlled trial aims to assess the differences between the SF proteome of patients affected by severe OA undergoing Total Knee Replacement (TKR) compared to control subjects (i.e., subjects younger than 35, undergoing knee arthroscopy for acute meniscus injury). METHODS: The synovial samples were collected from patients with Kellgren Lawrence grade 3 and 4 knee osteoarthritis undergoing THR (study group) and young patients with meniscal tears and no OA signs undergoing arthroscopic surgery (control group). The samples were processed and analyzed following the protocol defined in our previous study. All of the patients underwent clinical evaluation using the International Knee Documentation Committee (IKDC) subjective knee evaluation (main outcome), Knee Society Clinical Rating System (KSS), Knee injury and Osteoarthritis Outcome Score (KOOS), and Visual Analogue Scale (VAS) for pain. The drugs' assumptions and comorbidities were recorded. All patients underwent preoperative serial blood tests, including complete blood count and C-Reactive Protein (CRP). RESULTS: The synovial samples' analysis showed a significantly different fibrinogen beta chain (FBG) and alpha-enolase 1 (ENO1) concentration in OA compared to the control samples. A significant correlation between clinical scores, FBG, and ENO1 concentration was observed in osteoarthritic patients. CONCLUSIONS: Synovial fluid FBG and ENO1 concentrations are significantly different in patients affected by knee OA compared with non-OA subjects.

AI-Aided Search for New HIV-1 Protease Ligands.

The availability of drugs capable of blocking the replication of microorganisms has been one of the greatest triumphs in the history of medicine, but the emergence of an ever-increasing number of resistant strains poses a serious problem for the treatment of infectious diseases. The search for new potential ligands for proteins involved in the life cycle of pathogens is, therefore, an extremely important research field today. In this work, we have considered the HIV-1 protease, one of the main targets for AIDS therapy. Several drugs are used today in clinical practice whose mechanism of action is based on the inhibition of this enzyme, but after years of use, even these molecules are beginning to be interested by resistance phenomena. We used a simple artificial intelligence system for the initial screening of a data set of potential ligands. These results were validated by docking and molecular dynamics, leading to the identification of a potential new ligand of the enzyme which does not belong to any known class of HIV-1 protease inhibitors. The computational protocol used in this work is simple and does not require large computational power. Furthermore, the availability of a large number of structural information on viral proteins and the presence of numerous experimental data on their ligands, with which it is possible to compare the results obtained with computational methods, make this research field the ideal terrain for the application of these new computational techniques.

Oxidative Damage and Post-COVID Syndrome: A Cross-Sectional Study in a Cohort of Italian Workers.

In addition to the acute symptoms after infection, patients and society are also being challenged by the long-term effects of COVID-19, known as long COVID. Oxidative stress, as a pivotal point in the pathophysiology of COVID-19, could potentially be also involved in the development of the post-COVID syndrome. The aim of the present study was to evaluate the relationship between changes in oxidative status and the persistence of long-COVID symptoms in workers with a previous mild COVID-19 infection. A cross-sectional study was conducted among 127 employees of an Italian university (80 with a previous COVID-19 infection, and 47 healthy subjects). The TBARS assay was used to detect malondialdehyde serum levels (MDA), while total hydroperoxide (TH) production was measured by a d-ROMs kit. A significant difference in mean serum MDA values was found between previously infected subjects and healthy controls and (4.9 µm vs. 2.8 µm, respectively). Receiver-operating characteristic (ROC) curves showed high specificity and good sensibility (78.7% and 67.5%, respectively) for MDA serum levels. A random forest classifier identified the hematocrit value, MDA serum levels, and IgG titer against SARS-CoV-2 as features with the highest predictive value in distinguishing 34 long-COVID from 46 asymptomatic post-COVID subjects. Oxidative damage persists in subjects with previous COVID-19 infection, suggesting a possible role of oxidative stress mediators in the pathogenesis of long COVID.

Targeting mitochondrial impairment for the treatment of cardiovascular diseases: From hypertension to ischemia-reperfusion injury, searching for new pharmacological targets.

Mitochondria and mitochondrial proteins represent a group of promising pharmacological target candidates in the search of new molecular targets and drugs to counteract the onset of hypertension and more in general cardiovascular diseases (CVDs). Indeed, several mitochondrial pathways result impaired in CVDs, showing ATP depletion and ROS production as common traits of cardiac tissue degeneration. Thus, targeting mitochondrial dysfunction in cardiomyocytes can represent a successful strategy to prevent heart failure. In this context, the identification of new pharmacological targets among mitochondrial proteins paves the way for the design of new selective drugs. Thanks to the advances in omics approaches, to a greater availability of mitochondrial crystallized protein structures and to the development of new computational approaches for protein 3D-modelling and drug design, it is now possible to investigate in detail impaired mitochondrial pathways in CVDs. Furthermore, it is possible to design new powerful drugs able to hit the selected pharmacological targets in a highly selective way to rescue mitochondrial dysfunction and prevent cardiac tissue degeneration. The role of mitochondrial dysfunction in the onset of CVDs appears increasingly evident, as reflected by the impairment of proteins involved in lipid peroxidation, mitochondrial dynamics, respiratory chain complexes, and membrane polarization maintenance in CVD patients. Conversely, little is known about proteins responsible for the cross-talk between mitochondria and cytoplasm in cardiomyocytes. Mitochondrial transporters of the SLC25A family, in particular, are responsible for the translocation of nucleotides (e.g., ATP), amino acids (e.g., aspartate, glutamate, ornithine), organic acids (e.g. malate and 2-oxoglutarate), and other cofactors (e.g., inorganic phosphate, NAD+, FAD, carnitine, CoA derivatives) between the mitochondrial and cytosolic compartments. Thus, mitochondrial transporters play a key role in the mitochondria-cytosol cross-talk by leading metabolic pathways such as the malate/aspartate shuttle, the carnitine shuttle, the ATP export from mitochondria, and the regulation of permeability transition pore opening. Since all these pathways are crucial for maintaining healthy cardiomyocytes, mitochondrial carriers emerge as an interesting class of new possible pharmacological targets for CVD treatments.

cAMP/PKA Signaling Modulates Mitochondrial Supercomplex Organization.

The oxidative phosphorylation (OXPHOS) system couples the transfer of electrons to oxygen with pumping of protons across the inner mitochondrial membrane, ensuring the ATP production. Evidence suggests that respiratory chain complexes may also assemble into supramolecular structures, called supercomplexes (SCs). The SCs appear to increase the efficiency/capacity of OXPHOS and reduce the reactive oxygen species (ROS) production, especially that which is produced by complex I. Studies suggest a mutual regulation between complex I and SCs, while SCs organization is important for complex I assembly/stability, complex I is involved in the supercomplex formation. Complex I is a pacemaker of the OXPHOS system, and it has been shown that the PKA-dependent phosphorylation of some of its subunits increases the activity of the complex, reducing the ROS production. In this work, using in ex vivo and in vitro models, we show that the activation of cAMP/PKA cascade resulted in an increase in SCs formation associated with an enhanced capacity of electron flux and ATP production rate. This is also associated with the phosphorylation of the NDUFS4 subunit of complex I. This aspect highlights the key role of complex I in cellular energy production.

SARS-CoV-2 Main Protease Active Site Ligands in the Human Metabolome.

In late 2019, a global pandemic occurred. The causative agent was identified as a member of the Coronaviridae family, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we present an analysis on the substances identified in the human metabolome capable of binding the active site of the SARS-CoV-2 main protease (Mpro). The substances present in the human metabolome have both endogenous and exogenous origins. The aim of this research was to find molecules whose biochemical and toxicological profile was known that could be the starting point for the development of antiviral therapies. Our analysis revealed numerous metabolites-including xenobiotics-that bind this protease, which are essential to the lifecycle of the virus. Among these substances, silybin, a flavolignan compound and the main active component of silymarin, is particularly noteworthy. Silymarin is a standardized extract of milk thistle, Silybum marianum, and has been shown to exhibit antioxidant, hepatoprotective, antineoplastic, and antiviral activities. Our results-obtained in silico and in vitro-prove that silybin and silymarin, respectively, are able to inhibit Mpro, representing a possible food-derived natural compound that is useful as a therapeutic strategy against COVID-19.

Systematic Search for SARS-CoV-2 Main Protease Inhibitors for Drug Repurposing: Ethacrynic Acid as a Potential Drug.

In 2019 an outbreak occurred which resulted in a global pandemic. The causative agent has been identified in a virus belonging to theCoronaviridae family, similar to the agent of SARS, referred to as SARS-CoV-2. This epidemic spread rapidly globally with high morbidity and mortality. Although vaccine development is at a very advanced stage, there are currently no truly effective antiviral drugs to treat SARS-CoV-2 infection. In this study we present systematic and integrative antiviral drug repurposing effort aimed at identifying, among the drugs already authorized for clinical use, some active inhibitors of the SARS-CoV-2 main protease. The most important result of this analysis is the demonstration that ethacrynic acid, a powerful diuretic, is revealed to be an effective inhibitor of SARS-CoV-2 main protease. Even with all the necessary cautions, given the particular nature of this drug, these data can be the starting point for the development of an effective therapeutic strategy against SARS-CoV-2.

The oxygen-oxygen distance of water in crystallographic data sets.

Water is a key component of cellular biochemistry and numerous water molecules are visible in crystallographic structures. Here we report a series of data sets of crystallographic water: a high resolution data set, a cytochrome c oxidase (subunit I) data set and a carbonic anhydrase data set. These data support the evidence that short distance water molecule pairs are present both at the surface and inside the cavities of proteins. These data are related to article entitled "Oxygen-oxygen distances in protein-bound crystallographic water suggest the presence of protonated clusters" (Palese, 2020) [1].

Allosteric Cooperativity in Proton Energy Conversion in A1-Type Cytochrome c Oxidase.

Cytochrome c oxidase (CcO), the CuA, heme a, heme a3, CuB enzyme of respiratory chain, converts the free energy released by aerobic cytochrome c oxidation into a membrane electrochemical proton gradient (ΔµH+). ΔµH+ derives from the membrane anisotropic arrangement of dioxygen reduction to two water molecules and transmembrane proton pumping from a negative (N) space to a positive (P) space separated by the membrane. Spectroscopic, potentiometric, and X-ray crystallographic analyses characterize allosteric cooperativity of dioxygen binding and reduction with protonmotive conformational states of CcO. These studies show that allosteric cooperativity stabilizes the favorable conformational state for conversion of redox energy into a transmembrane ΔµH+.

Oxygen-oxygen distances in protein-bound crystallographic water suggest the presence of protonated clusters.

BACKGROUND: The availability of high-resolution X-ray structures has shown that proteins contain numerous water molecules, but their role is still not fully understood. Protonated and deprotonated water species are often involved in biochemical reactions. However protons are exceedingly difficult to detect directly because they are electron-poor species. METHODS: The oxygen­oxygen distance of the crystallographic water molecules was analyzed in a large high-resolution data set. Moreover, a detailed analysis was carried out on the protein-bound water in the available structures of carbonic anhydrase II and cytochrome c oxidase, chosen as protein models in which protonated and deprotonated water species play a significant role. RESULTS: The analysis shows an excess of water-water distances below the expected value for hydrogen bond. In the cavities and on the surface of the considered model proteins, clusters of water molecules are found, whose structure suggests the presence of chemical species deriving from self-ionization of water. CONCLUSIONS: The presence of a small maximum below the hydrogen bond threshold in the oxygen­oxygen distance distribution of crystallographic water molecules, along with the location of many of these water clusters, suggest the presence of Zundel-like structures in, or near, the proteins. Particularly significant is the presence of such structures in protein regions which have been identified as proton antennae or channels. GENERAL SIGNIFICANCE: This work shows the possibilities, still unexplored, offered by this type of analysis in detecting in structures obtained by X-ray diffraction the presence of aqueous protons or hydroxide ions, which are chemical species as important as elusive.

Explaining leak states in the proton pump of heme-copper oxidases observed in single-molecule experiments.

Heme-copper oxidases couple the exergonic oxygen reduction with the endergonic proton translocation. Redox-linked structural changes have been localized in deeply buried regions of the protein, near the low-potential heme. How these movements can modulate distant gating events along the intramolecular proton path, where the entry (exit) of pumped proton occurs, is a major concern for the proton pump models. Generally, these models associate, more or less directly, all translocation events with redox transitions. Although they can account for many phenomenological aspects of the pump, evidences from single-molecules experiments about leak states of the pump represent a formidable challenge. Disconnecting the redox-linked pKa shifts of the proton loading site from the external barriers, we obtain a simple stochastic mechanism which behaves similarly to the real enzyme, able to reverse the flow of the proton transfer.

A New Look at the Structures of Old Sepsis Actors by Exploratory Data Analysis Tools.

Sepsis is a life-threatening condition that accounts for numerous deaths worldwide, usually complications of common community infections (i.e., pneumonia, etc), or infections acquired during the hospital stay. Sepsis and septic shock, its most severe evolution, involve the whole organism, recruiting and producing a lot of molecules, mostly proteins. Proteins are dynamic entities, and a large number of techniques and studies have been devoted to elucidating the relationship between the conformations adopted by proteins and what is their function. Although molecular dynamics has a key role in understanding these relationships, the number of protein structures available in the databases is so high that it is currently possible to build data sets obtained from experimentally determined structures. Techniques for dimensionality reduction and clustering can be applied in exploratory data analysis in order to obtain information on the function of these molecules, and this may be very useful in immunology to better understand the structure-activity relationship of the numerous proteins involved in host defense, moreover in septic patients. The large number of degrees of freedom that characterize the biomolecules requires special techniques which are able to analyze this kind of data sets (with a small number of entries respect to the number of degrees of freedom). In this work we analyzed the ability of two different types of algorithms to provide information on the structures present in three data sets built using the experimental structures of allosteric proteins involved in sepsis. The results obtained by means of a principal component analysis algorithm and those obtained by a random projection algorithm are largely comparable, proving the effectiveness of random projection methods in structural bioinformatics. The usefulness of random projection in exploratory data analysis is discussed, including validation of the obtained clusters. We have chosen these proteins because of their involvement in sepsis and septic shock, aimed to highlight the potentiality of bioinformatics to point out new diagnostic and prognostic tools for the patients.

Human Ovarian Cancer Tissue Exhibits Increase of Mitochondrial Biogenesis and Cristae Remodeling.

Ovarian cancer (OC) is the most lethal gynecologic cancer characterized by an elevated apoptosis resistance that, potentially, leads to chemo-resistance in the recurrent disease. Mitochondrial oxidative phosphorylation was found altered in OC, and mitochondria were proposed as a target for therapy. Molecular evidence suggests that the deregulation of mitochondrial biogenesis, morphology, dynamics, and apoptosis is involved in carcinogenesis. However, these mitochondrial processes remain to be investigated in OC. Eighteen controls and 16 OC tissues (serous and mucinous) were collected. Enzymatic activities were performed spectrophotometrically, mitochondrial DNA (mtDNA) content was measured by real-time-PCR, protein levels were determined by Western blotting, and mitochondrial number and structure were measured by electron microscopy. Statistical analysis was performed using Student's t-test, Mann-Whitney U test, and principal component analysis (PCA). We found, in OC, that increased mitochondrial number associated with increased peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) and mitochondrial transcription factor A (TFAM) protein levels, as well as mtDNA content. The OC mitochondria presented an increased maximum length, as well as reduced cristae width and junction diameter, associated with increased optic atrophy 1 protein (OPA1) and prohibitin 2 (PHB2) protein levels. In addition, in OC tissues, augmented cAMP and sirtuin 3 (SIRT3) protein levels were observed. PCA of the 25 analyzed biochemical parameters classified OC patients in a distinct group from controls. We highlight a "mitochondrial signature" in OC that could result from cooperation of the cAMP pathway with the SIRT3, OPA1, and PHB2 proteins.

Cytochrome c oxidase structures suggest a four-state stochastic pump mechanism.

Cytochrome c oxidase catalyses the terminal step of cellular respiration in eukaryotes and in many prokaryotes. This enzyme reduces molecular oxygen by means of a process coupled with proton pumping. Models for proton pumping activity in cytochrome c oxidase can be divided into two groups, which are still strongly debated to date: one in which haem a is the key player, and another where this role is covered by the oxygen reduction site. Current models share the fact of requesting, more or less explicitly, an ordered sequence of events. Here, we show that all the available subunit I structures of this enzyme can be clustered in four groups. Starting from these structural observations, and considering the large corpus of available experimental data and theoretical considerations, a simple four-state (stochastic) pump model is proposed. This model implies a series of characteristics that reflect the behavior of the real enzyme in a natural way, where strictly sequential models require ad hoc assumptions (e.g. slipping mechanisms). Our results suggest that the stochastic conformational coupling could be a mechanism for energy transduction used by the protein machines.

Translational control mechanisms in cutaneous malignant melanoma: the role of eIF2α.

BACKGROUND: Melanoma cells develop adaptive responses in order to cope with particular conditions of tumor microenvironment, characterized by stress conditions and deregulated proliferation. Recently, the interplay between the stress response and the gene expression programs leading to metastatic spread has been reported. METHODS: We evaluated levels and localization of eIF2α/peIF2α in V600BRAF and wtBRAF metastatic melanoma cell lines by means of western blot and confocal microscopy analyses. Furthermore, we performed a sequence analyses and structure and dynamics studies of eIF2α protein to reveal the role of eIF2α and its correlations in different pathways involved in the invasive phase of melanoma. RESULTS: We found peIF2α both in cytoplasm and nucleus. Nuclear localization was more represented in V600BRAF melanoma cell lines. Our studies on eIF2α protein sequence indicated the presence of a predicted bipartite NLS as well as a nuclear export signal NES and an S1 domain, typical of RNA interacting proteins. Furthermore, we found high levels of transcription factor EB (TFEB), a component of the MiT/TFE family, and low ß-catenin levels in V600BRAF cells. CONCLUSIONS: Based on our results, we suggest that peIF2α nuclear localization can be crucial in ER stress response and in driving the metastatic spread of melanoma, through lysosomal signaling and Wnt/ß-catenin pathway. In conclusion, this is the first evidence of nuclear localization of peIF2α, representing a possible target for future therapeutic approaches for metastatic melanoma.

A random version of principal component analysis in data clustering.

Principal component analysis (PCA) is a widespread technique for data analysis that relies on the covariance/correlation matrix of the analyzed data. However, to properly work with high-dimensional data sets, PCA poses severe mathematical constraints on the minimum number of different replicates, or samples, that must be included in the analysis. Generally, improper sampling is due to a small number of data respect to the number of the degrees of freedom that characterize the ensemble. In the field of life sciences it is often important to have an algorithm that can accept poorly dimensioned data sets, including degenerated ones. Here a new random projection algorithm is proposed, in which a random symmetric matrix surrogates the covariance/correlation matrix of PCA, while maintaining the data clustering capacity. We demonstrate that what is important for clustering efficiency of PCA is not the exact form of the covariance/correlation matrix, but simply its symmetry.

Analysis of the conformations of the HIV-1 protease from a large crystallographic data set.

The HIV-1 protease performs essential roles in viral maturation by processing specific cleavage sites in the Gag and Gag-Pol precursor polyproteins to release their mature forms. Here the analysis of a large HIV-1 protease data set (containing 552 dimer structures) are reported. These data are related to article entitled "Conformations of the HIV-1 protease: a crystal structure data set analysis" (Palese, 2017) [1].

Conformations of the HIV-1 protease: A crystal structure data set analysis.

The HIV protease is an important drug target for HIV/AIDS therapy, and its structure and function have been extensively investigated. This enzyme performs an essential role in viral maturation by processing specific cleavage sites in the Gag and Gag-Pol precursor polyproteins so as to release their mature forms. This 99 amino acid aspartic protease works as a homodimer, with the active site localized in a central cavity capped by two flexible flap regions. The dimer presents closed or open conformations, which are involved in the substrate binding and release. Here the results of the analysis of a HIV-1 protease data set containing 552 dimer structures are reported. Different dimensionality reduction methods have been used in order to get information from this multidimensional database. Most of the structures in the data set belong to two conformational clusters. An interesting observation that comes from the analysis of these data is that some protease sequences are localized preferentially in specific areas of the conformational landscape of this protein.

Metaproteomics Applied to Activated Sludge for Industrial Wastewater Treatment Revealed a Dominant Methylotrophic Metabolism of Hyphomicrobium zavarzinii.

In biological wastewater treatments, microbial populations of the so-called activated sludge work together in the abatement of pollutants. In this work, the metabolic behavior of the biomass of a lab-scale plant treating industrial pharmaceutical wastewater was investigated through a metaproteomic approach. The complete treatment process included a membrane biological reactor (MBR) coupled with an advanced oxidation process (AOP) for partial breakdown of non-biodegradable molecules. Proteins from biomass samples collected pre- and post-AOP application were investigated by two-dimensional gel electrophoresis (2DE), mass spectrometry (MS), and finally identified by database search. Results showed that most proteins remained constant between pre- and post-AOP. Methanol dehydrogenase (MDH) belonging to Hyphomicrobium zavarzinii appeared as the most constantly expressed protein in the studied consortium. Other identified proteins belonging to Hyphomicrobium spp. revealed a predominant methylotrophic metabolism, and H. zavarzinii appeared as a key actor in the studied microbial community.