Explore the vast range of titles available.

The phosphatases PP1 and PP2A are responsible for the majority of dephosphorylation reactions on phosphoserine (pSer) and phosphothreonine (pThr), and are involved in virtually all cellular processes and numerous diseases. The catalytic subunits exist in cells in form of holoenzymes, which impart substrate specificity. The contribution of the catalytic subunits to the recognition of substrates is unclear. By developing a phosphopeptide library approach and a phosphoproteomic assay, we demonstrate that the specificity of PP1 and PP2A holoenzymes towards pThr and of PP1 for basic motifs adjacent to the phosphorylation site are due to intrinsic properties of the catalytic subunits. Thus, we dissect this amino acid specificity of the catalytic subunits from the contribution of regulatory proteins. Furthermore, our approach enables discovering a role for PP1 as regulator of the GRB-associated-binding protein 2 (GAB2)/14-3-3 complex. Beyond this, we expect that this approach is broadly applicable to detect enzyme-substrate recognition preferences. The substrate specificity of phosphoprotein phosphatases PP1 and PP2A depends on their catalytic and regulatory subunits. Using proteomics approaches, the authors here provide insights into the sequence specificity of the catalytic subunits and their distinct contributions to PP1 and PP2A selectivity.

The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to study the binding mechanism of a transition state analogue (DADMe–immucillin-H) to the purine nucleoside phosphorylase (PNP) enzyme. Microsecond-long MD simulations allow us to observe several binding events, following different dynamical routes and reaching diverse binding configurations. These simulations are used to estimate kinetic and thermodynamic quantities, such as k on and binding free energy, obtaining a good agreement with available experimental data. In addition, we advance a hypothesis for the slow-onset inhibition mechanism of DADMe–immucillin-H against PNP. Combining extensive MD simulations with machine learning algorithms could therefore be a fruitful approach for capturing key aspects of drug–target recognition and binding. Understanding the dynamics of enzyme-substrate complexation provides an insight into potential drugs, but intermediate states are difficult to observe experimentally. Here, the authors use simulations and machine learning to analyse the binding of transition state inhibitors to purine nucleoside phosphorylase.

Binding site flexibility and dynamics strongly affect the ability of proteins to accommodate substrates and inhibitors. The significance of these properties is particularly pronounced for proteins that are inherently flexible, such as cytochrome P450 enzymes (CYPs). While the research on human CYPs provides detailed knowledge on both structural and functional level, such analyses are still lacking for their plant counterparts. This study aims to bridge this gap. We developed a novel computational pipeline consisting of two steps. Firstly, we use molecular dynamics (MD) simulations to capture the full conformational ensemble for a certain plant CYP. Subsequently, we developed and applied a comprehensive methodology to analyze a number of binding site properties—size, flexibility, shape, hydrophobicity, and accessibility—using the fpocket and mdpocket packages on MD-generated trajectories. The workflow was validated on human CYPs 1A2, 2A6, and 3A4, as their binding site characteristics are well known. Not only could we confirm known binding site properties, but we also identified and named previously unseen binding site channels for CYPs 1A2 and 2A6. The pipeline was then applied to plant CYPs, leading to the first categorization of 15 chosen plant CYPs based on their binding site’s (dis)similarities. This study provides a foundation for the largely uncharted fields of plant CYP substrate specificity and facilitates a more precise understanding of their largely unknown specific biological functions. It offers new insights into the structural and functional dynamics of plant CYPs, which may facilitate a more accurate understanding of the fate of agrochemicals or the biotechnological design and exploitation of enzymes with specific functions. Additionally, it serves as a reference for future structural–functional analyses of CYP enzymes across various biological kingdoms.

This review article focuses on the role of adenosine in coronary artery disease (CAD) diagnosis and treatment. Adenosine, an endogenous purine nucleoside, plays crucial roles in cardiovascular physiology and pathology. Its release and effects, mediated by specific receptors, influence vasomotor function, blood pressure regulation, heart rate, and platelet activity. Adenosine therapeutic effects include treatment of the no-reflow phenomenon and paroxysmal supraventricular tachycardia. The production of adenosine involves complex cellular pathways, with extracellular and intracellular synthesis mechanisms. Adenosine’s rapid metabolism underscores its short half-life and physiological turnover. Furthermore, adenosine’s involvement in side effects of antiplatelet therapy, particularly ticagrelor and cangrelor, highlights its clinical significance. Moreover, adenosine serves as a valuable tool in CAD diagnosis, aiding stress testing modalities and guiding intracoronary physiological assessments. Its use in assessing epicardial stenosis and microvascular dysfunction is pivotal for treatment decisions. Overall, understanding adenosine’s mechanisms and clinical implications is essential for optimizing CAD management strategies, encompassing both therapeutic interventions and diagnostic approaches.

Background: Atrial fibrillation (AF) is one of the most common heart rhythm disorders encountered in clinical practice. Emerging evidence suggests a significant role of inflammation in the pathogenesis of AF, but certain questions still remain unanswered, in particular whether AF-related inflammation is a cause or a consequence of the arrhythmia, and whether inflammation reflects underlying disease or AF itself. At the current state of the art, scientific evidence on the role of oral anticoagulants (OAC) in modulating pro-inflammatory cytokines implicated in the pathogenesis of AF remains scarce. The aim of our study was to evaluate, in a population of AF patients undergoing OAC, the different roles of anticoagulant therapy [Vitamin K antagonists (VKAs) and direct oral anti-coagulants (DOACs)] in modulating the levels of inflammatory biomarkers in AF. Methods: The Strat-AF study is an observational, prospective, single center, hospital-based study enrolling elderly patients with AF. Results refer to 170 subjects with complete clinical and biohumoral assessment. Results: At multivariate logistic regression analysis, adjusted for several covariates, VKA treatment was an independent protective predictor for having a high grade of inflammation not balanced by anti-inflammatory cytokine levels [OR = 0.26 (0.10–0.69), p = 0.007]. Conclusions: These results from the Strat-AF study are “generators of hypotheses” and provide preliminary evidence for the differential effects of VKAs and DOACs on inflammatory biomarkers (e.g., IL-6, TNF-α) in AF patients. These findings suggest that inflammatory biomarkers could enhance stroke risk prediction models, potentially improving a tailored AF management.

Ticagrelor is currently considered a first-line choice in dual antiplatelet therapy (DAPT) following revascularization of acute coronary syndrome (ACS). However, its use is correlated with an increased incidence of two side effects, dyspnea and bradyarrhythmias, whose molecular mechanisms have not yet been defined with certainty and, consequently, neither of the therapeutic decisions they imply. We report the case of a patient with acute myocardial infarction treated with ticagrelor and aspirin as oral antithrombotic therapy after primary percutaneous coronary intervention (PCI), manifesting in a significant bradyarrhythmic episode that required a switch of antiplatelet therapy. Starting from this case report, this article aims to gather the currently available evidence regarding the molecular mechanisms underlying these side effects and propose possible decision-making algorithms regarding their management in clinical practice.

Background: Atrial fibrillation (AF) is the most common supraventricular arrythmia and one of the most commonly encountered heart conditions in clinical practice. Emerging evidence suggests a significant role of inflammation in the pathogenesis of AF. Population studies have also suggested an association between AF and cognitive impairment and dementia. The aim of this study is therefore to assess, in a population of AF patients on oral anticoagulant therapy, the association between circulating biomarkers involved in the pathogenesis of AF and the cognitive and motor performances of the enrolled patients. Methods: The Strat-AF study is an observational, prospective, single-center, hospital-based study enrolling elderly patients with AF. Results refer to 180 subjects who underwent a complete clinical, biohumoral, cognitive, and functional evaluation. Results: At multivariate logistic regression, Clot Lysis Time (CLT) and circulating levels of von Willebrand Factor (vWF) remained significantly associated with pathological performances at the Stroop test (expressed as execution time) [OR 95% CI 1.54 (1.02–2.35), p = 0.042 and 1.75 (1.08–2.82), p = 0.023, respectively]. With regard to the Short Physical Performance Battery (SPPB), the circulating levels of IL-8 remained significantly associated with the clinical endpoint [OR 95% CI 2.19 (1.13–4.25), p = 0.020]. Conclusions: Our results suggest a potential innovative tool able to identify AF patients at risk of worse prognosis in terms of cognitive and motor performances. The clinical relevance of these results is due to the fact that we have no efficient methods to predict a deterioration in the cognitive performance and, consequently, the possible onset of dementia in AF patients undergoing oral anticoagulant therapy.

Background: Bicuspid aortic valve (BAV) is the most common congenital heart defect, and its complications (namely, dilatation of the thoracic ascending aorta) raise concerns regarding the proper timing of aortic surgery. The study aim is to unravel the genetic basis of BAV and its complications through a high-throughput sequencing (HTS) approach and segregation analysis if family members were available. Methods: Fifty-two Italian BAV patients were analyzed by HTS using the Illumina MiSeq platform. Targeted sequencing of 97 genes known to be or plausibly associated with connective tissue disorders or aorthopathy was performed. Thirty-five first-degree relatives of N = 10 probands underwent mutational screening for variants identified in the index cases. Results: HTS identified 194 rare (MAF < 0.01) variants in 63 genes. Regarding previously reported genes, five NOTCH1 variants in four BAV patients, four FBN1 variants in two patients and one GATA5 variant in one patient were identified. Interestingly, among further loci, the possible contribution of PDIA2, LRP1 and CAPN2 was suggested by (a) the increased prevalence of rare genetic variants, independently from their ACMG classification in the whole BAV cohort, and (b) segregation analyses of variants identified in family members. Moreover, the present data also suggest the possible contribution of rare variants to BAV complications, specifically MYLK in aortic dilatation, CAPN2 in BAV calcification and VHL and AGGF1 in valve stenosis. Conclusions: Our results underline clinical and genetic diagnosis complexity in traits considered monogenic, such as BAV, but characterized by variability in disease phenotypic expression (incomplete penetrance), as well as the contribution of different major and modifier genes to the development of complications.

Background Lipoprotein(a) [Lp(a)] level variability, related to atherothrombotic risk increase, is mainly attributed to LPA gene, encoding apolipoprotein(a), with kringle IV type 2 (KIV2) copy number variation (CNV) acting as the primary genetic determinant. Genetic characterization of Lp(a) is in continuous growth; nevertheless, the peculiar structural characteristics of this variant constitute a significant challenge to the development of effective detection methods. The aim of the study was to compare quantitative real‐time PCR (qPCR) and digital droplet PCR (ddPCR) in the evaluation of KIV2 repeat polymorphism. Methods We analysed 100 subjects tested for cardiovascular risk in which Lp(a) plasma levels were assessed. Results Correlation analysis between CNV values obtained with the two methods was slightly significant (R = 0.413, p = 0.00002), because of the wider data dispersion in qPCR compared with ddPCR. Internal controls C1, C2 and C3 measurements throughout different experimental sessions revealed the superior stability of ddPCR, which was supported by a reduced intra/inter‐assay coefficient of variation determined in this method compared to qPCR. A significant inverse correlation between Lp(a) levels and CNV values was confirmed for both techniques, but it was higher when evaluated by ddPCR than qPCR (R = −0.393, p = 0.000053 vs R = −0.220, p = 0.028, respectively). When dividing subjects into two groups according to 500 mg/L Lp(a) cut‐off value, a significantly lower number of KIV2 repeats emerged among subjects with greater Lp(a) levels, with stronger evidence in ddPCR than in qPCR (p = 0.000013 and p = 0.001, respectively). Conclusions Data obtained support a better performance of ddPCR in the evaluation of KIV2 repeat polymorphism. In this study, real‐time and digital droplet PCR were compared in the evaluation of KIV2 repeat copy number variation polymorphism, concerning LPA gene, which encode apolipoprotein (a), protein component of lipoprotein (a), which is a known genetic independent risk factor for atherothrombosis. Digital droplet PCR emerges as a promising method that can make improvements in the measurement of this kind of large repeat length CNV, which is used to assess the causality between Lp(a) and cardiovascular diseases.

In anticoagulated atrial fibrillation (AF) patients, the validity of models recommended for the stratification of the risk ratio between benefits and hemorrhage risk is limited. We hypothesize that both circulating and neuroimaging-based markers might improve the prediction of bleeding and thrombotic risk in anticoagulated AF patients. The Strat-AF study is an observational, prospective, single-center study enrolling 170 patients with AF; recruited patients are evaluated by means of a comprehensive protocol, with clinical, cerebral magnetic resonance imaging and circulating biomarkers assessment. The main outcome is the evaluation of cerebral microangiopathy related to the levels of circulating biomarkers of inflammation and extracellular matrix (ECM) remodeling. At multivariate logistic regression analysis adjusted for age, sex, CHA2DS2-VASc, HAS-BLED and type of anticoagulant, matrix metalloproteinases (MMP)-2 levels were significantly and positively associated with the presence of cerebral microbleeds (CMBs). A significant association between MMP-2, tissue inhibitor of metalloproteinases (TIMP)-1,-2,-4 levels and white matter hyperintensity was also found. Concerning the small vessel disease (SVD) score, MMP-2 and TIMP-1,-2 levels were associated with the presence of two and three or more signs of SVD, whereas TIMP-4 levels were associated with the presence of three signs of SVD with respect to patients with no instrumental signs of SVD. As regarding the presence of enlarged perivascular spaces (EPVS), a significant association was found for high levels of interleukin (IL)-8 and TIMP 1-2-3. These results demonstrate that patients with AF have evidence of impaired ECM degradation, which is an independent risk factor for thrombotic complications of AF patients on oral anticoagulant therapy. The incorporation of these markers in the prognostic schemes might improve their clinical capability in predicting stroke risk and thrombotic complications.