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BACKGROUND: Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. METHODS: We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. RESULTS: We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920-0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients). CONCLUSIONS: We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.
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Biomarcadores , Espectroscopia de Ressonância Magnética , Síndrome Metabólica , Metabolômica , Valor Preditivo dos Testes , Humanos , Síndrome Metabólica/diagnóstico , Síndrome Metabólica/sangue , Síndrome Metabólica/epidemiologia , Síndrome Metabólica/urina , Feminino , Masculino , Biomarcadores/sangue , Biomarcadores/urina , Pessoa de Meia-Idade , Medição de Risco , Adulto , Idoso , Lipoproteínas/sangue , Prognóstico , Fatores de Risco , Fatores de Risco Cardiometabólico , Adulto JovemRESUMO
BACKGROUND AND AIMS: We previously identified subsets of patients with NAFLD with different metabolic phenotypes. Here we align metabolomic signatures with cardiovascular disease (CVD) and genetic risk factors. APPROACH AND RESULTS: We analyzed serum metabolome from 1154 individuals with biopsy-proven NAFLD, and from four mouse models of NAFLD with impaired VLDL-triglyceride (TG) secretion, and one with normal VLDL-TG secretion. We identified three metabolic subtypes: A (47%), B (27%), and C (26%). Subtype A phenocopied the metabolome of mice with impaired VLDL-TG secretion; subtype C phenocopied the metabolome of mice with normal VLDL-TG; and subtype B showed an intermediate signature. The percent of patients with NASH and fibrosis was comparable among subtypes, although subtypes B and C exhibited higher liver enzymes. Serum VLDL-TG levels and secretion rate were lower among subtype A compared with subtypes B and C. Subtype A VLDL-TG and VLDL-apolipoprotein B concentrations were independent of steatosis, whereas subtypes B and C showed an association with these parameters. Serum TG, cholesterol, VLDL, small dense LDL5,6 , and remnant lipoprotein cholesterol were lower among subtype A compared with subtypes B and C. The 10-year high risk of CVD, measured with the Framingham risk score, and the frequency of patatin-like phospholipase domain-containing protein 3 NAFLD risk allele were lower in subtype A. CONCLUSIONS: Metabolomic signatures identify three NAFLD subgroups, independent of histological disease severity. These signatures align with known CVD and genetic risk factors, with subtype A exhibiting a lower CVD risk profile. This may account for the variation in hepatic versus cardiovascular outcomes, offering clinically relevant risk stratification.
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Doenças Cardiovasculares , Hepatopatia Gordurosa não Alcoólica , Animais , Apolipoproteínas B , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/etiologia , VLDL-Colesterol/metabolismo , Fatores de Risco de Doenças Cardíacas , Lipoproteínas VLDL , Fígado/patologia , Camundongos , Hepatopatia Gordurosa não Alcoólica/patologia , Fosfolipases/metabolismo , Fatores de Risco , Triglicerídeos/metabolismoRESUMO
For a long time, conventional medicine has analysed biomolecules to diagnose diseases. Yet, this approach has proven valid only for a limited number of metabolites and often through a bijective relationship with the disease (i.e. glucose relationship with diabetes), ultimately offering incomplete diagnostic value. Nowadays, precision medicine emerges as an option to improve the prevention and/or treatment of numerous pathologies, focusing on the molecular mechanisms, acting in a patient-specific dimension, and leveraging multiple contributing factors such as genetic, environmental, or lifestyle. Metabolomics grasps the required subcellular complexity while being sensitive to all these factors, which results in a most suitable technique for precision medicine. The aim of this chapter is to describe how NMR-based metabolomics can be integrated in the design of a precision medicine strategy, using the Precision Medicine Initiative of the Basque Country (the AKRIBEA project) as a case study. To that end, we will illustrate the procedures to be followed when conducting an NMR-based metabolomics study with a large cohort of individuals, emphasizing the critical points. The chapter will conclude with the discussion of some relevant biomedical applications.
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Diabetes Mellitus , Medicina de Precisão , Humanos , Estudos Prospectivos , Metabolômica/métodos , Diabetes Mellitus/metabolismo , BiomarcadoresRESUMO
An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.
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COVID-19 , Humanos , SARS-CoV-2 , Lipidômica , Pandemias , PlasmaRESUMO
COVID-19 is a systemic infectious disease that may affect many organs, accompanied by a measurable metabolic dysregulation. The disease is also associated with significant mortality, particularly among the elderly, patients with comorbidities, and solid organ transplant recipients. Yet, the largest segment of the patient population is asymptomatic, and most other patients develop mild to moderate symptoms after SARS-CoV-2 infection. Here, we have used NMR metabolomics to characterize plasma samples from a cohort of the abovementioned group of COVID-19 patients (n = 69), between 3 and 10 months after diagnosis, and compared them with a set of reference samples from individuals never infected by the virus (n = 71). Our results indicate that half of the patient population show abnormal metabolism including porphyrin levels and altered lipoprotein profiles six months after the infection, while the other half show little molecular record of the disease. Remarkably, most of these patients are asymptomatic or mild COVID-19 patients, and we hypothesize that this is due to a metabolic reflection of the immune response stress.
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COVID-19/metabolismo , Lipidômica , Espectroscopia de Ressonância Magnética/métodos , Metabolômica , SARS-CoV-2 , COVID-19/imunologia , HDL-Colesterol/sangue , LDL-Colesterol/sangue , HumanosRESUMO
Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping.
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COVID-19 , SARS-CoV-2 , Austrália , Biomarcadores , Humanos , LipoproteínasRESUMO
BACKGROUND: Metabolic syndrome (MetS) is a multimorbid long-term condition without consensual medical definition and a diagnostic based on compatible symptomatology. Here we have investigated the molecular signature of MetS in urine. METHODS: We used NMR-based metabolomics to investigate a European cohort including urine samples from 11,754 individuals (18-75 years old, 41% females), designed to populate all the intermediate conditions in MetS, from subjects without any risk factor up to individuals with developed MetS (4-5%, depending on the definition). A set of quantified metabolites were integrated from the urine spectra to obtain metabolic models (one for each definition), to discriminate between individuals with MetS. RESULTS: MetS progression produces a continuous and monotonic variation of the urine metabolome, characterized by up- or down-regulation of the pertinent metabolites (17 in total, including glucose, lipids, aromatic amino acids, salicyluric acid, maltitol, trimethylamine N-oxide, and p-cresol sulfate) with some of the metabolites associated to MetS for the first time. This metabolic signature, based solely on information extracted from the urine spectrum, adds a molecular dimension to MetS definition and it was used to generate models that can identify subjects with MetS (AUROC values between 0.83 and 0.87). This signature is particularly suitable to add meaning to the conditions that are in the interface between healthy subjects and MetS patients. Aging and non-alcoholic fatty liver disease are also risk factors that may enhance MetS probability, but they do not directly interfere with the metabolic discrimination of the syndrome. CONCLUSIONS: Urine metabolomics, studied by NMR spectroscopy, unravelled a set of metabolites that concomitantly evolve with MetS progression, that were used to derive and validate a molecular definition of MetS and to discriminate the conditions that are in the interface between healthy individuals and the metabolic syndrome.
Assuntos
Síndrome Metabólica/urina , Metaboloma , Metabolômica , Espectroscopia de Prótons por Ressonância Magnética , Adolescente , Adulto , Idoso , Biomarcadores/urina , Estudos de Casos e Controles , Progressão da Doença , Europa (Continente) , Feminino , Humanos , Masculino , Síndrome Metabólica/diagnóstico , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Urinálise , Adulto JovemRESUMO
Prostate cancer is the second most common tumor and the fifth cause of cancer-related death among men worldwide. PC cells exhibit profound signaling and metabolic reprogramming that account for the acquisition of aggressive features. Although the metabolic understanding of this disease has increased in recent years, the analysis of such alterations through noninvasive methodologies in biofluids remains limited. Here, we used NMR-based metabolomics on a large cohort of urine samples (more than 650) from PC and benign prostate hyperplasia (BPH) patients to investigate the molecular basis of this disease. Multivariate analysis failed to distinguish between the two classes, highlighting the modest impact of prostate alterations on urine composition and the multifactorial nature of PC. However, univariate analysis of urine metabolites unveiled significant changes, discriminating PC from BPH. Metabolites with altered abundance in urine from PC patients revealed changes in pathways related to cancer biology, including glycolysis and the urea cycle. We found out that metabolites from such pathways were diminished in the urine from PC individuals, strongly supporting the notion that PC reduces nitrogen and carbon waste in order to maximize their usage in anabolic processes that support cancer cell growth.
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Nitrogênio , Neoplasias da Próstata , Carbono , Humanos , Masculino , Metabolômica , Neoplasias da Próstata/diagnóstico , Espectroscopia de Prótons por Ressonância MagnéticaRESUMO
The MAPK (mitogen-activated protein kinase) p38 is an important mediator of inflammation and of inflammatory and neuropathic pain. We have described recently that docking-groove-dependent interactions are important for p38 MAPK-mediated signal transduction. Thus virtual screening was performed to identify putative docking-groove-targeted p38 MAPK inhibitors. Several compounds of the benzo-oxadiazol family were identified with low micromolar inhibitory activity both in a p38 MAPK activity assay, and in THP-1 human monocytes acting as inhibitors of LPS (lipopolysaccharide)-induced TNFα (tumour necrosis factor α) secretion. Positions 2 and 5 in the phenyl ring are essential for the described inhibitory activity with a chloride in position 5 and a methyl group in position 2 yielding the best results, giving an IC50 value of 1.8 µM (FGA-19 compound). Notably, FGA-19 exerted a potent and long-lasting analgesic effect in vivo when tested in a mouse model of inflammatory hyperalgesia. A single intrathecal injection of FGA-19 completely resolved hyperalgesia, being 10-fold as potent and displaying longer lasting effects than the established p38 MAPK inhibitor SB239063. FGA-19 also reversed persistent pain in a model of post-inflammatory hyperalgesia in LysM (lysozyme M)-GRK2 (G-protein-coupled-receptor kinase)(+/-) mice. These potent in vivo effects suggested p38 MAPK docking-site-targeted inhibitors as a potential novel strategy for the treatment of inflammatory pain.
Assuntos
Anti-Inflamatórios não Esteroides/farmacologia , Hiperalgesia/tratamento farmacológico , Macrófagos/efeitos dos fármacos , Monócitos/efeitos dos fármacos , Oxidiazóis/farmacologia , Inibidores de Proteínas Quinases/farmacologia , Proteínas Quinases p38 Ativadas por Mitógeno/antagonistas & inibidores , Analgésicos/química , Analgésicos/metabolismo , Analgésicos/farmacologia , Analgésicos/uso terapêutico , Animais , Anti-Inflamatórios não Esteroides/química , Anti-Inflamatórios não Esteroides/metabolismo , Anti-Inflamatórios não Esteroides/uso terapêutico , Linhagem Celular , Células Cultivadas , Avaliação Pré-Clínica de Medicamentos , Feminino , Humanos , Hiperalgesia/imunologia , Hiperalgesia/metabolismo , Macrófagos/imunologia , Macrófagos/metabolismo , Macrófagos/patologia , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Monócitos/imunologia , Monócitos/metabolismo , Oxidiazóis/química , Oxidiazóis/metabolismo , Oxidiazóis/uso terapêutico , Inibidores de Proteínas Quinases/química , Inibidores de Proteínas Quinases/metabolismo , Inibidores de Proteínas Quinases/uso terapêutico , Distribuição Aleatória , Relação Estrutura-Atividade , Proteínas Quinases p38 Ativadas por Mitógeno/química , Proteínas Quinases p38 Ativadas por Mitógeno/metabolismoRESUMO
ALFA is a fast computational tool for the conformational analysis of small molecules that uses a custom-made iterative algorithm to provide a set of representative conformers in an attempt to reproduce the diversity of states in which small molecules can exist, either isolated in solution or bound to a target. The results shown in this work prove that ALFA is fast enough to be integrated into massive high-throughput virtual screening protocols with the aim of incorporating ligand flexibility and also that ALFA reproduces crystallographic X-ray structures of bound ligands with great accuracy. Furthermore, the application includes a graphical user interface that allows its use through the popular molecular graphics program PyMOL to make it accessible to nonexpert users. ALFA is distributed free of charge upon request from the authors.
Assuntos
Conformação Molecular , Software , Algoritmos , Biologia Computacional , Gráficos por Computador , Cristalografia por Raios X , Ensaios de Triagem em Larga Escala , Ligantes , Eletricidade Estática , Interface Usuário-ComputadorRESUMO
BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) is a prevalent chronic noncurable disease associated with profound metabolic changes. The discovery of novel molecular indicators for unraveling IBD etiopathogenesis and the diagnosis and prognosis of IBD is therefore pivotal. We sought to determine the distinctive metabolic signatures from the different IBD subgroups before treatment initiation. METHODS: Serum and urine samples from newly diagnosed treatment-naïve IBD patients and age and sex-matched healthy control (HC) individuals were investigated using proton nuclear magnetic resonance spectroscopy. Metabolic differences were identified based on univariate and multivariate statistical analyses. RESULTS: A total of 137 Crohn's disease patients, 202 ulcerative colitis patients, and 338 HC individuals were included. In the IBD cohort, several distinguishable metabolites were detected within each subgroup comparison. Most of the differences revealed alterations in energy and amino acid metabolism in IBD patients, with an increased demand of the body for energy mainly through the ketone bodies. As compared with HC individuals, differences in metabolites were more marked and numerous in Crohn's disease than in ulcerative colitis patients, and in serum than in urine. In addition, clustering analysis revealed 3 distinct patient profiles with notable differences among them based on the analysis of their clinical, anthropometric, and metabolomic variables. However, relevant phenotypical differences were not found among these 3 clusters. CONCLUSIONS: This study highlights the molecular alterations present within the different subgroups of newly diagnosed treatment-naïve IBD patients. The metabolomic profile of these patients may provide further understanding of pathogenic mechanisms of IBD subgroups. Serum metabotype seemed to be especially sensitive to the onset of IBD.
Assuntos
Colite Ulcerativa , Doença de Crohn , Doenças Inflamatórias Intestinais , Humanos , Colite Ulcerativa/diagnóstico , Doença de Crohn/diagnóstico , Metabolômica , IntestinosRESUMO
Mesoamerican nephropathy (MeN) is a form of chronic kidney disease found predominantly in young men in Mesoamerica. Strenuous agricultural labor is a consistent risk factor for MeN, but the pathophysiologic mechanism leading to disease is poorly understood. We compared the urine metabolome among men in Nicaragua engaged in sugarcane harvest and seed cutting (n = 117), a group at high risk for MeN, against three referents: Nicaraguans working less strenuous jobs at the same sugarcane plantations (n = 78); Nicaraguans performing non-agricultural work (n = 102); and agricultural workers in Spain (n = 78). Using proton nuclear magnetic resonance, we identified 136 metabolites among participants. Our non-hypothesis-based approach identified distinguishing urine metabolic features in the high-risk group, revealing increased levels of hippurate and other gut-derived metabolites and decreased metabolites related to central energy metabolism when compared to referent groups. Our complementary hypothesis-based approach, focused on nicotinamide adenine dinucleotide (NAD+) related metabolites, and revealed a higher kynurenate/tryptophan ratio in the high-risk group (p = 0.001), consistent with a heightened inflammatory state. Workers in high-risk occupations are distinguishable by urinary metabolic features that suggest increased gut permeability, inflammation, and altered energy metabolism. Further study is needed to explore the pathophysiologic implications of these findings.
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An ultrafast docking and virtual screening program, CRDOCK, is presented that contains (1) a search engine that can use a variety of sampling methods and an initial energy evaluation function, (2) several energy minimization algorithms for fine tuning the binding poses, and (3) different scoring functions. This modularity ensures the easy configuration of custom-made protocols that can be optimized depending on the problem in hand. CRDOCK employs a precomputed library of ligand conformations that are initially generated from one-dimensional SMILES strings. Testing CRDOCK on two widely used benchmarks, the ASTEX diverse set and the Directory of Useful Decoys, yielded a success rate of ~75% in pose prediction and an average AUC of 0.66. A typical ligand can be docked, on average, in just ~13 s. Extension to a representative group of pharmacologically relevant G protein-coupled receptors that have been recently cocrystallized with some selective ligands allowed us to demonstrate the utility of this tool and also highlight some current limitations. CRDOCK is now included within VSDMIP, our integrated platform for drug discovery.
Assuntos
Avaliação Pré-Clínica de Medicamentos/métodos , Ligantes , Simulação de Acoplamento Molecular/métodos , Proteínas/metabolismo , Interface Usuário-Computador , Humanos , Conformação Proteica , Proteínas/química , Receptores Acoplados a Proteínas G/química , Receptores Acoplados a Proteínas G/metabolismo , Termodinâmica , Fatores de TempoRESUMO
After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts.
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A graphical user interface (GUI) for our previously published virtual screening (VS) and data management platform VSDMIP (Gil-Redondo et al. J Comput Aided Mol Design, 23:171-184, 2009) that has been developed as a plugin for the popular molecular visualization program PyMOL is presented. In addition, a ligand-based VS module (LBVS) has been implemented that complements the already existing structure-based VS (SBVS) module and can be used in those cases where the receptor's 3D structure is not known or for pre-filtering purposes. This updated version of VSDMIP is placed in the context of similar available software and its LBVS and SBVS capabilities are tested here on a reduced set of the Directory of Useful Decoys database. Comparison of results from both approaches confirms the trend found in previous studies that LBVS outperforms SBVS. We also show that by combining LBVS and SBVS, and using a cluster of ~100 modern processors, it is possible to perform complete VS studies of several million molecules in less than a month. As the main processes in VSDMIP are 100% scalable, more powerful processors and larger clusters would notably decrease this time span. The plugin is distributed under an academic license upon request from the authors.
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Desenho Assistido por Computador , Interface Usuário-Computador , Ligantes , Modelos Moleculares , Ligação Proteica , SoftwareRESUMO
There is an ongoing need of developing sensitive and specific methods for the determination of SARS-CoV-2 seroconversion. For this purpose, we have developed a multiplexed flow cytometric bead array (C19BA) that allows the identification of IgG and IgM antibodies against three immunogenic proteins simultaneously: the spike receptor-binding domain (RBD), the spike protein subunit 1 (S1) and the nucleoprotein (N). Using different cohorts of samples collected before and after the pandemic, we show that this assay is more sensitive than ELISAs performed in our laboratory. The combination of three viral antigens allows for the interrogation of full seroconversion. Importantly, we have detected N-reactive antibodies in COVID-19-negative individuals. Here we present an immunoassay that can be easily implemented and has superior potential to detect low antibody titers compared to current gold standard serology methods.
Assuntos
Anticorpos Antivirais/imunologia , COVID-19/diagnóstico , Citometria de Fluxo/métodos , Nucleoproteínas/imunologia , SARS-CoV-2/imunologia , Soroconversão , Antígenos Virais/imunologia , COVID-19/epidemiologia , COVID-19/virologia , Humanos , Imunoensaio/métodos , Imunoglobulina G/imunologia , Imunoglobulina M/imunologia , Pandemias , Reprodutibilidade dos Testes , SARS-CoV-2/fisiologia , Sensibilidade e EspecificidadeRESUMO
Essential cell division protein FtsZ forms the bacterial cytokinetic ring and is a target for new antibiotics. FtsZ monomers bind GTP and assemble into filaments. Hydrolysis to GDP at the association interface between monomers leads to filament disassembly. We have developed a homogeneous competition assay, employing the fluorescence anisotropy change of mant-GTP upon binding to nucleotide-free FtsZ, which detects compounds binding to the nucleotide site in FtsZ monomers and measures their affinities within the millimolar to 10 nM range. We have employed this method to determine the apparent contributions of the guanine, ribose, and the α-, ß-, and γ-phosphates to the free energy change of nucleotide binding. Similar relative contributions have also been estimated through molecular dynamics and binding free energy calculations, employing the crystal structures of FtsZ-nucleotide complexes. We find an energetically dominant contribution of the ß-phosphate, comparable to the whole guanosine moiety. GTP and GDP bind with similar observed affinity to FtsZ monomers. Loss of the regulatory γ-phosphate results in a predicted accommodation of GDP which has not been observed in the crystal structures. The binding affinities of a series of C8-substituted GTP analogues, known to inhibit FtsZ but not eukaryotic tubulin assembly, correlate with their inhibitory capacity on FtsZ polymerization. Our methods permit testing of FtsZ inhibitors targeting its nucleotide site, as well as compounds from virtual screening of large synthetic libraries. Our results give insight into the FtsZ-nucleotide interactions, which could be useful in the rational design of new inhibitors, especially GTP phosphate mimetics.
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Proteínas de Bactérias/química , Proteínas de Bactérias/metabolismo , Proteínas do Citoesqueleto/química , Proteínas do Citoesqueleto/metabolismo , Guanosina Trifosfato/química , Guanosina Trifosfato/metabolismo , Simulação de Dinâmica Molecular , ortoaminobenzoatos/química , ortoaminobenzoatos/metabolismo , Proteínas de Bactérias/antagonistas & inibidores , Sítios de Ligação , Ligação Competitiva/fisiologia , Divisão Celular/fisiologia , Cristalografia por Raios X , Proteínas do Citoesqueleto/antagonistas & inibidores , Mathanococcus/química , Mathanococcus/metabolismo , Pseudomonas aeruginosa/química , Pseudomonas aeruginosa/metabolismo , Reprodutibilidade dos TestesRESUMO
We present gCOMBINE, a Java-written graphical user interface (GUI) for performing comparative binding energy (COMBINE) analysis (Ortiz et al. J Med Chem 1995; 38:2681-2691) on a set of ligand-receptor complexeswith the aim of deriving highly informative quantitative structure-activity relationships. The essence of the method is to decompose the ligand-receptor interaction energies into a series of terms, explore the origins of the variance within the set using Principal Component Analysis, and then assign weights to selected ligandresidue interactions using partial least squares analysis to correlate with the experimental activities or binding affinities. The GUI allows plenty of interactivity and provides multiple plots representing the energy descriptors entering the analysis, scores, loadings, experimental versus predicted regression lines, and the evolution of parameterssuch as r(2) (correlation coefficient), q(2) (cross-validated r(2)), and prediction errors as the number of extracted latent variables increases. Other representative features include the implementation of a sigmoidal dielectric function for electrostatic energy calculations, alternative cross-validation procedures (leave-N-out and random groups), drawing of confidence ellipses, and the possibility to carry out several additional tasks such as optional truncation of positive interaction energy values and generation of ready-to-use PDB files containing information related to the importance for activity of individual protein residues. This information can be displayed and color-coded using a standard molecular graphics program such as PyMOL. It is expected that this user-friendly tool will expand the applicability of the COMBINE analysis method and encourage more groups to use it in their drug design research programs.
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Proteínas/química , Proteínas/metabolismo , Software , Desenho de Fármacos , Protease de HIV/química , Protease de HIV/metabolismo , Ligantes , Modelos Moleculares , Ligação Proteica , Relação Quantitativa Estrutura-Atividade , TermodinâmicaRESUMO
COVID-19 is a systemic infection that exerts significant impact on the metabolism. Yet, there is little information on how SARS-CoV-2 affects metabolism. Using NMR spectroscopy, we measured the metabolomic and lipidomic serum profile from 263 (training cohort) + 135 (validation cohort) symptomatic patients hospitalized after positive PCR testing for SARS-CoV-2 infection. We also established the profiles of 280 persons collected before the coronavirus pandemic started. Principal-component analysis discriminated both cohorts, highlighting the impact that the infection has on overall metabolism. The lipidomic analysis unraveled a pathogenic redistribution of the lipoprotein particle size and composition to increase the atherosclerotic risk. In turn, metabolomic analysis reveals abnormally high levels of ketone bodies (acetoacetic acid, 3-hydroxybutyric acid, and acetone) and 2-hydroxybutyric acid, a readout of hepatic glutathione synthesis and marker of oxidative stress. Our results are consistent with a model in which SARS-CoV-2 infection induces liver damage associated with dyslipidemia and oxidative stress.