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By merging advanced dimensionality reduction (DR) and clustering algorithm (CA) techniques, our study advances the sampling procedure for predicting NMR chemical shifts (CS) in intrinsically disordered proteins (IDPs), making a significant leap forward in the field of protein analysis/modeling. We enhance NMR CS sampling by generating clustered ensembles that accurately reflect the different properties and phenomena encapsulated by the IDP trajectories. This investigation critically assessed different rapid CS predictors, both neural network (e.g., Sparta+ and ShiftX2) and database-driven (ProCS-15), and highlighted the need for more advanced quantum calculations and the subsequent need for more tractable-sized conformational ensembles. Although neural network CS predictors outperformed ProCS-15 for all atoms, all tools showed poor agreement with HN CSs, and the neural network CS predictors were unable to capture the influence of phosphorylated residues, highly relevant for IDPs. This study also addressed the limitations of using direct clustering with collective variables, such as the widespread implementation of the GROMOS algorithm. Clustered ensembles (CEs) produced by this algorithm showed poor performance with chemical shifts compared to sequential ensembles (SEs) of similar size. Instead, we implement a multiscale DR and CA approach and explore the challenges and limitations of applying these algorithms to obtain more robust and tractable CEs. The novel feature of this investigation is the use of solvent-accessible surface area (SASA) as one of the fingerprints for DR alongside previously investigated α carbon distance/angles or Ï/ψ dihedral angles. The ensembles produced with SASA tSNE DR produced CEs better aligned with the experimental CS of between 0.17 and 0.36 r2 (0.18-0.26 ppm) depending on the system and replicate. Furthermore, this technique produced CEs with better agreement than traditional SEs in 85.7% of all ensemble sizes. This study investigates the quality of ensembles produced based on different input features, comparing latent spaces produced by linear vs nonlinear DR techniques and a novel integrated silhouette score scanning protocol for tSNE DR.
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This work extends the multi-scale computational scheme for the quantum mechanics (QM) calculations of Nuclear Magnetic Resonance (NMR) chemical shifts (CSs) in proteins that lack a well-defined 3D structure. The scheme couples the sampling of an intrinsically disordered protein (IDP) by classical molecular dynamics (MD) with protein fragmentation using the adjustable density matrix assembler (ADMA) and density functional theory (DFT) calculations. In contrast to our early investigation on IDPs (Pavlíková Precechtelová et al., J. Chem. Theory Comput., 2019, 15, 5642-5658) and the state-of-the art NMR calculations for structured proteins, a partial re-optimization was implemented on the raw MD geometries in vibrational normal mode coordinates to enhance the accuracy of the MD/ADMA/DFT computational scheme. In addition, machine-learning based cluster analysis was performed on the scheme to explore its potential in producing protein structure ensembles (CLUSTER ensembles) that yield accurate CSs at a reduced computational cost. The performance of the cluster-based calculations is validated against results obtained with conventional structural ensembles consisting of MD snapshots extracted from the MD trajectory at regular time intervals (REGULAR ensembles). CS calculations performed with the refined MD/ADMA/DFT framework employed the 6-311++G(d,p) basis set that outperformed IGLO-III calculations with the same density functional approximation (B3LYP) and both explicit and implicit solvation. The partial geometry optimization did not universally improve the agreement of computed CSs with the experiment but substantially decreased errors associated with the ensemble averaging. A CLUSTER ensemble with 50 structures yielded ensemble averages close to those obtained with a REGULAR ensemble consisting of 500 MD frames. The cluster based calculations thus required only a fraction of the computational time.
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Proteínas Intrínsecamente Desordenadas , Proteínas Intrínsecamente Desordenadas/química , Aprendizaje Automático , Simulación de Dinámica Molecular , Teoría CuánticaRESUMEN
Coxsackievirus B4 strain E2 (CVB4-E2) and its association with type 1 diabetes (T1D) have been studied in experimental in vitro and in vivo murine models. CVB4-E2, known to be pancreotropic and diabetogenic in nature, is associated with acute pancreatitis in mice but shows differences in the induction of glycemia after intraperitoneal (i.p.) infection. Therefore, the aim of this work was to study the outcome of oral infection with CVB4-E2 in five mouse strains with different genetic backgrounds: two outbred (Swiss albino, CD1), two inbred (SJL, NOD) and one transgenic (NOD.SCID). Survival rates, fasting blood glucose, histopathology, viral titres and persistence were studied in selected organs and stool samples. Viral protein (VP1), proinflammatory cytokines, and interferon alpha (IFN-α) were analyzed by immunohistochemistry. We observed mortality only in infected NOD and NOD.SCID mice, with differing survival rates implying initial innate protection in the NOD.SCID mice and low virus clearance with replicating virus titres in the studied organs and stool up to day 40 post infection (p.i.). Independent of the mouse strain hyperglycemia, proinflammatory cytokines and histopathological changes were absent in the endocrine pancreas of infected mice. Only the pancreata of the dead NOD.SCID mice showed inflammation even in presence of IFN-α. Host-dependent viral RNA persistence was observed in all outbred mice. In conclusion, oral infection with CVB4-E2, despite the known affinity of this strain towards the pancreatic tissue and the presence of replicating virus, conferred total protection to the endocrine pancreas in all mice and failed to induce the proinflammatory cytokines studied by us.
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Diabetes Mellitus/virología , Enterovirus Humano B/clasificación , Enterovirus Humano B/patogenicidad , Páncreas/patología , Animales , Glucemia , Regulación de la Expresión Génica , Predisposición Genética a la Enfermedad , Inflamación/metabolismo , Interferón-alfa/metabolismo , Masculino , Ratones , Ratones Endogámicos , Ratones Transgénicos , ARN Viral , Proteínas Virales/metabolismo , Replicación Viral/fisiologíaRESUMEN
The correlation factor model is developed in which the spherically averaged exchange-correlation hole of Kohn-Sham theory is factorized into an exchange hole model and a correlation factor. The exchange hole model reproduces the exact exchange energy per particle. The correlation factor is constructed in such a manner that the exchange-correlation energy correctly reduces to exact exchange in the high density and rapidly varying limits. Four different correlation factor models are presented which satisfy varying sets of physical constraints. Three models are free from empirical adjustments to experimental data, while one correlation factor model draws on one empirical parameter. The correlation factor models are derived in detail and the resulting exchange-correlation holes are analyzed. Furthermore, the exchange-correlation energies obtained from the correlation factor models are employed to calculate total energies, atomization energies, and barrier heights. It is shown that accurate, non-empirical functionals can be constructed building on exact exchange. Avenues for further improvements are outlined as well.
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A persistent challenge in density functional theory is the construction of a nonempirical correlation functional that is compatible with the exact exchange energy. To solve this problem, we develop a correlation factor approach in which an exchange hole model, yielding the exact exchange energy, is multiplied by a correlation factor that turns the exchange hole into an exchange-correlation hole. This results in an accurate correlation energy functional that is determined solely through physical constraints. Subject to the properties of the employed exchange hole model, the proposed correlation factor model to the exchange-correlation energy becomes exact in the high-density limit. In this limit, the exchange-correlation energy is dominated by exchange.
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Coxsackievirus B2 (CVB2), one of six human pathogens of the group B coxsackieviruses within the enterovirus genus of Picornaviridae, causes a wide spectrum of human diseases ranging from mild upper respiratory illnesses to myocarditis and meningitis. The CVB2 prototype strain Ohio-1 (CVB2O) was originally isolated from a patient with summer grippe in the 1950s. Later on, CVB2O was adapted to cytolytic replication in rhabdomyosarcoma (RD) cells. Here, we present analyses of the correlation between the adaptive mutations of this RD variant and the cytolytic infection in RD cells. Using reverse genetics, we identified a single amino acid change within the exposed region of the VP1 protein (glutamine to lysine at position 164) as the determinant for the acquired cytolytic trait. Moreover, this cytolytic virus induced apoptosis, including caspase activation and DNA degradation, in RD cells. These findings contribute to our understanding of the host cell adaptation process of CVB2O and provide a valuable tool for further studies of virus-host interactions.
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Apoptosis , Proteínas de la Cápside/metabolismo , Enterovirus Humano B/metabolismo , Infecciones por Enterovirus/fisiopatología , Rabdomiosarcoma/fisiopatología , Animales , Proteínas de la Cápside/genética , Línea Celular , Chlorocebus aethiops , Enterovirus Humano B/genética , Infecciones por Enterovirus/virología , Humanos , Masculino , Ratones , Ratones Endogámicos A , Rabdomiosarcoma/virologíaRESUMEN
A comprehensive quantum chemical analysis of the influence of backbone torsion angles on (31)P chemical shifts in DNAs has been carried out. An extensive DFT study employed snapshots obtained from the molecular dynamics simulation of [d(CGCGAATTCGCG)]2 to construct geometries of a hydrated dimethyl phosphate, which was used as a model for the phosphodiester linkage. Our calculations provided differences of 2.1 ± 0.3 and 1.6 ± 0.3 ppm between the B(I) and B(II) chemical shifts in two B-DNA residues of interest, which is in a very good agreement with the difference of 1.6 ppm inferred from experimental data. A more negative (31)P chemical shift for a residue in pure BI conformation compared to residues in mixed B(I)/B(II) conformation states is provided by DFT, in agreement with the NMR experiment. Statistical analysis of the MD/DFT data revealed a large dispersion of chemical shifts in both B(I) and B(II) regions of DNA structures. δP ranges within 3.5 ± 0.8 ppm in the B(I) region and within 4.5 ± 1.5 ppm in the B(II) region. While the (31)P chemical shift becomes more negative with increasing α in B(I)-DNA, it has the opposite trend in B(II)-DNA when both α and ζ increase simultaneously. The (31)P chemical shift is dominated by the torsion angles α and ζ, while an implicit treatment of ß and ε is sufficient. The presence of an explicit solvent leads to a damping and a 2-3 ppm upfield shift of the torsion angle dependences.
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ADN Forma B/química , Simulación de Dinámica Molecular , Fósforo/química , Teoría Cuántica , Secuencia de Bases , ADN Forma B/genética , Espectroscopía de Resonancia Magnética , Conformación Molecular , RotaciónRESUMEN
Quantum mechanics (QM) calculations are applied to examine 1H, 13C, 15N, and 31P chemical shifts of two phosphorylation sites in an intrinsically disordered protein region. The QM calculations employ a combination of (1) structural ensembles generated by molecular dynamics, (2) a fragmentation technique based on the adjustable density matrix assembler, and (3) density functional methods. The combined computational approach is used to obtain chemical shifts (i) in the S19 and S40 residues of the nonphosphorylated and (ii) in the pS19 and pS40 residues of the doubly phosphorylated human tyrosine hydroxylase 1 as the system of interest. We study the effects of conformational averaging and explicit solvent sampling as well as the effects of phosphorylation on the computed chemical shifts. Good to great quantitative agreement with the experiment is achieved for all nuclei, provided that the systematic error cancellation is optimized by the choice of a suitable NMR standard. The effect of the standard reference on the computed 15N and 31P chemical shifts is demonstrated by employing three different referencing methods. Error bars associated with the statistical averaging of the computed 31P chemical shifts are larger than the difference between the 31P chemical shift of pS19 and pS40. The sequence trend of 31P shifts therefore could not be reliably reproduced. On the contrary, the calculations correctly predict the change of the 13C chemical shift for CB induced by the phosphorylation of the serine residues. The present work demonstrates that QM calculations coupled with molecular dynamics simulations and fragmentation techniques can be used as an alternative to empirical prediction tools in the structure characterization of intrinsically disordered proteins.
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Proteínas Intrínsecamente Desordenadas/química , Resonancia Magnética Nuclear Biomolecular , Teoría Cuántica , Humanos , Proteínas Intrínsecamente Desordenadas/síntesis química , Simulación de Dinámica Molecular , FosforilaciónRESUMEN
31P chemical shift anisotropy (CSA) tensors have been calculated for a set of selected DNA and RNA backbone conformations using density functional theory. The set includes canonical A-RNA, A-DNA, BI-DNA, BII-DNA, ZI-DNA, and ZII-DNA as well as four A-RNA-type, seven non-A-RNA-type, and three non-canonical DNA conformations. Hexahydrated dimethyl phosphate has been employed as a model. The 31P chemical shift tensors obtained are discussed in terms of similarities in the behavior observed for gauche-gauche (gg) and gauche-trans (gt) conformations around the P-O bonds. We show that torsion angles alpha and zeta are major determinants of the isotropic chemical shift deltaiso and of the deltaCSA11 component of the traceless chemical shift tensor, which is revealed in separate ranges of both deltaiso and deltaCSA11 for gg- and gt-conformers, respectively. A clear distinction between the two conformation types has not been found for the deltaCSA22 and deltaCSA33 components, which is attributed to their different directional properties. The 31P CSA tensors exhibit considerable variations resulting in large spans of approximately 16 ppm for deltaCSA11 and approximately 22 ppm for deltaCSA22 and deltaCSA33. We examine the consequences of the CSA variations for predicting the chemical shift changes upon partial alignment deltacsa and for the values of CSA order parameters extracted from the analysis of 31P NMR relaxation data. The theoretical 31P CSA tensors as well as the experimental 31P CSA tensor of barium diethyl phosphate (BDEP) are used to calculate deltacsa for two eclipsed orientations of the CSA and molecular alignment tensors. Percentage differences between the CSA order parameters obtained using the theoretical 31P CSA tensors and the experimental 31P CSA tensor of BDEP, respectively, are also determined.
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Simulación por Computador , Espectroscopía de Resonancia Magnética/métodos , Ácidos Nucleicos/química , Isótopos de Fósforo/química , Teoría Cuántica , Anisotropía , Conformación de Ácido Nucleico , Compuestos Organofosforados/química , Oxígeno/química , Fósforo/químicaRESUMEN
Density functional theory (DFT) has been applied to study the conformational dependence of 31P chemical shift tensors in B-DNA. The gg and gt conformations of backbone phosphate groups representing BI- and BII-DNA have been examined. Calculations have been carried out on static models of dimethyl phosphate (dmp) and dinucleoside-3',5'-monophosphate with bases replaced by hydrogen atoms in vacuo as well as in an explicit solvent. Trends in 31P chemical shift anisotropy (CSA) tensors with respect to the backbone torsion angles alpha, zeta, beta, and epsilon are presented. Although these trends do not change qualitatively upon solvation, quantitative changes result in the reduction of the chemical shift anisotropy. For alpha and zeta in the range from 270 degrees to 330 degrees and from 240 degrees to 300 degrees , respectively, the delta22 and delta33 principal components vary within as much as 30 ppm, showing a marked dependence on backbone conformation. The calculated 31P chemical shift tensor principal axes deviate from the axes of O-P-O bond angles by at most 5 degrees . For solvent models, our results are in a good agreement with experimental estimates of relative gg and gt isotropic chemical shifts. Solvation also brings the theoretical deltaiso of the gg conformation closer to the experimental gg data of barium diethyl phosphate.
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ADN/química , Hidrógeno/química , Modelos Moleculares , Conformación de Ácido Nucleico , Fosfatos de Dinucleósidos/química , Compuestos Organofosforados/química , Isótopos de Fósforo/química , Solventes/químicaRESUMEN
Standard spectral density mapping protocols, well suited for the analysis of (15)N relaxation rates, introduce significant systematic errors when applied to (13)C relaxation data, especially if the dynamics is dominated by motions with short correlation times (small molecules, dynamic residues of macromolecules). A possibility to improve the accuracy by employing cross-correlated relaxation rates and on measurements taken at several magnetic fields has been examined. A suite of protocols for analyzing such data has been developed and their performance tested. Applicability of the proposed protocols is documented in two case studies, spectral density mapping of a uniformly labeled RNA hairpin and of a selectively labeled disaccharide exhibiting highly anisotropic tumbling. Combination of auto- and cross-correlated relaxation data acquired at three magnetic fields was applied in the former case in order to separate effects of fast motions and conformational or chemical exchange. An approach using auto-correlated relaxation rates acquired at five magnetic fields, applicable to anisotropically moving molecules, was used in the latter case. The results were compared with a more advanced analysis of data obtained by interpolation of auto-correlated relaxation rates measured at seven magnetic fields, and with the spectral density mapping of cross-correlated relaxation rates. The results showed that sufficiently accurate values of auto- and cross-correlated spectral density functions at zero and (13)C frequencies can be obtained from data acquired at three magnetic fields for uniformly (13)C-labeled molecules with a moderate anisotropy of the rotational diffusion tensor. Analysis of auto-correlated relaxation rates at five magnetic fields represents an alternative for molecules undergoing highly anisotropic motions.
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Algoritmos , Espectroscopía de Resonancia Magnética con Carbono-13/métodos , Interpretación Estadística de Datos , ARN Interferente Pequeño/análisis , ARN Interferente Pequeño/química , Procesamiento de Señales Asistido por Computador , Campos Magnéticos , Reproducibilidad de los Resultados , Sensibilidad y EspecificidadRESUMEN
We review type 1 diabetes and host genetic components, as well as epigenetics and viruses associated with type 1 diabetes, with added emphasis on the enteroviruses, which are often associated with triggering the disease. Genus Enterovirus is classified into twelve species of which seven (Enterovirus A, Enterovirus B, Enterovirus C, and Enterovirus D and Rhinovirus A, Rhinovirus B, and Rhinovirus C) are human pathogens. These viruses are transmitted mainly by the fecal-oral route; they may also spread via the nasopharyngeal route. Enterovirus infections are highly prevalent, but these infections are usually subclinical or cause a mild flu-like illness. However, infections caused by enteroviruses can sometimes be serious, with manifestations of meningoencephalitis, paralysis, myocarditis, and in neonates a fulminant sepsis-like syndrome. These viruses are often implicated in chronic (inflammatory) diseases as chronic myocarditis, chronic pancreatitis, and type 1 diabetes. In this review we discuss the currently suggested mechanisms involved in the viral induction of type 1 diabetes. We recapitulate current basic knowledge and definitions.
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This work addresses the question of the ability of the molecular dynamics-density functional theory (MD/DFT) approach to reproduce sequence trend in (31)P chemical shifts (δP) in the backbone of nucleic acids. δP for [d(CGCGAATTCGCG)]2, a canonical B-DNA, have been computed using density functional theory calculations on model compounds with geometries cut out of snapshots of classical molecular dynamics (MD) simulations. The values of (31)P chemical shifts for two distinct B-DNA subfamilies BI and BII, δP/BI and δP/BII, have been determined as averages over the BI and BII subparts of the MD trajectory. This has been done for various samplings of MD trajectory and for two sizes of both the model and the solvent embedding. For all of the combinations of trajectory sampling, model size, and embedding size, sequence dependence of δP/BI in the order of 0.4-0.5 ppm has been obtained. Weighted averages for individual (31)P nuclei in the studied DNA double-helix have been calculated from δP/BI and δP/BII using BI and BII percentages from free MD simulations as well as from approaches employing NMR structural restraints. A good qualitative agreement is found between experimental sequence trends in δP and theoretical δP employing short (24 ns) MD run and BI, BII percentages determined by Hartmann et al. or via MD with the inclusion of NMR structural restraints. Theoretical δP exhibit a systematic offset of ca. 11 ppm and overestimation of trends by a factor of ca. 1.7. When scaled accordingly, theoretical δP/BI and δP/BII can be used to determine the expected percentage of BII to match the experimental value of δP. As evidenced by the calculations on snapshots from Car-Parrinello molecular dynamics, the systematic offsets of the theoretical δP obtained by MD/DFT approach result primarily from the unrealistic bond lengths employed by classical MD. The findings made in this work provide structure-δP relationships for possible use as NMR restraints and suggest that NMR calculations on MD snapshots can be in the future employed for the validation of newly developed force fields.
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Enteroviral infections go usually unnoticed, even during pregnancy, yet some case histories and mouse experiments indicate that these viruses may be transmitted vertically. More frequently, however, transmission occurs by (fecal) contamination during and shortly after birth. The aim of this study was to investigate the effect of maternal infection in mice (1) on gravidity outcome and (2) on subsequent challenge of the offspring with the same virus. CD1 outbred female mice were infected by the oral route with coxsackievirus B4 strain E2 or mock-infected at days 4, 10, or 17 of gestation. Weight and signs of sickness were noted daily. Pups were infected at day 25 after birth (4 days postweaning). Organs (brain, pancreas, and heart) were analyzed for viral RNA and histopathology. We observed that maternal infection at day 4 or day 17 of gestation had little effect on pregnancy outcome, whereas infection at day 10 affected dams and/or offspring. Infection of pups resulted in severe inflammation of the pancreas, but only when dams were previously infected, especially at day 17. The blood glucose levels were elevated. Because no trace of infection was found at the time of challenge, a role for immunopathology is suggested.