How the Conformational Movement of the Substrate Drives the Regioselective C-N Bond Formation in P450 TleB: Insights from Molecular Dynamics Simulations and Quantum Mechanical/Molecular Mechanical Calculations.

P450 TleB catalyzes the oxidative cyclization of the dipeptide N-methylvalyl-tryptophanol into indolactam V through selective intramolecular C-H bond amination at the indole C4 position. Understanding its catalytic mechanism is instrumental for the engineering or design of P450-catalyzed C-H amination reactions. Using multiscale computational methods, we show that the reaction proceeds through a diradical pathway, involving a hydrogen atom transfer (HAT) from N1-H to Cpd I, a conformational transformation of the substrate radical species, and a second HAT from N13-H to Cpd II. Intriguingly, the conformational transformation is found to be the key to enabling efficient and selective C-N coupling between N13 and C4 in the subsequent diradical coupling reaction. The underlined conformational transformation is triggered by the first HAT, which proceeds with an energy-demanding indole ring flip and is followed by the facile approach of the N13-H group to Cpd II. Detailed analysis shows that the internal electric field (IEF) from the protein environment plays key roles in the transformation process, which not only provides the driving force but also stabilizes the flipped conformation of the indole radical. Our simulations provide a clear picture of how the P450 enzyme can smartly modulate the selective C-N coupling reaction. The present findings are in line with all available experimental data, highlighting the crucial role of substrate dynamics in controlling this highly valuable reaction.

A threshold longitudinal Tobit quantile regression model for identification of treatment-sensitive subgroups based on interval-bounded longitudinal measurements and a continuous covariate.

Identification of a subgroup of patients who may be sensitive to a specific treatment is an important problem in precision medicine. This article considers the case where the treatment effect is assessed by longitudinal measurements, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. Recently, a linear mixed threshold regression model has been proposed but it assumes the longitudinal measurements are normally distributed. In many applications, longitudinal measurements, such as quality of life data obtained from answers to questions on a Likert scale, may be restricted in a fixed interval because of the floor and ceiling effects and, therefore, may be skewed. In this article, a threshold longitudinal Tobit quantile regression model is proposed and a computational approach based on alternating direction method of multipliers algorithm is developed for the estimation of parameters in the model. In addition, a random weighting method is employed to estimate the variances of the parameter estimators. The proposed procedures are evaluated through simulation studies and applications to the data from clinical trials.

Unveiling orientation dependence of anisotropic plasticity in polycrystalline copper by nanoindentation.

The mechanical properties of crystalline materials are influenced by their deformation behavior, which is associated with their microstructural characteristics. Specifically, crystallographic orientation greatly affects the microscale plastic deformation of individual grains. In this study, experiments and finite element simulations of Berkovich nanoindentations are conducted to investigate the impact of crystallographic orientation in polycrystalline copper. A crystal plasticity constitutive model is developed for copper materials, which accurately captures their indentation mechanical response. The results showed that the indentation behavior of polycrystalline copper exhibits a high degree of anisotropy due to significant variation in slip systems for different crystallographic orientations. This results in different mechanical responses of individual grains and distinct material pileup morphologies on the indented surface. Additionally, the study revealed that crystallographic orientation plays a critical role in determining the indentation size effect. These findings have important implications for the design of materials where plasticity is a crucial factor.

A composite semiparametric homogeneity test for the distributions of multigroup interval-bounded longitudinal data.

Motivated by comparing the distribution of longitudinal quality of life (QoL) data among different treatment groups from a cancer clinical trial, we propose a semiparametric test statistic for the homogeneity of the distributions of multigroup longitudinal measurements, which are bounded in a closed interval with excess observations taking the boundary values. Our procedure is based on a three-component mixed density ratio model and a composite empirical likelihood for the longitudinal data taking values inside the interval. A nonparametric bootstrap method is applied to calculate the p-value of the proposed test. Simulation studies are conducted to evaluate the proposed procedure, which show that the proposed test is effective in controlling type I errors and more powerful than the procedure which ignores the values on the boundaries. It is also robust to the model mispecification than the parametric test. The proposed procedure is also applied to compare the distributions of the scores of Physical Function subscale and Global Heath Status between the patients randomized to two treatment groups in a cancer clinical trial.

Novel Cuproptosis-Related Gene Signature for Precise Identification of High-Risk Populations in Low-Grade Gliomas.

Background: Patients with low-grade glioma (LGG) have wildly varying average lifespans. However, no effective way exists for identifying LGG patients at high risk. Cuproptosis is a recently described form of cell death associated with the abnormal aggregation of lipid acylated proteins. Few investigations have been conducted on cuproptosis-associated genes and LGG thus far. The purpose of this research is to establish a predictive model for cuproptosis-related genes in order to recognise LGG populations at high risk. Methods: We analyzed 926 LGGs from 2 public datasets, all of which were RNA sequencing datasets. On the basis of immune scores, the LGG population was split into different risk categories with X-tile. LASSO and Cox regressions were employed to filter cuproptosis-associated genes and construct prediction models. The accuracy of the predictive models was measured by using TCGA internal validation set and the CGGA external validation set. In addition, LGG immune cell infiltration was viewed using CIBERSORT and ssGSEA algorithms and correlation analysis was done with cuproptosis-related genes. Finally, immune escape capacity in LGG low- and high-risk groups was evaluated using the TIDE method. Results: The prediction model constructed by four cuproptosis-related genes was used to identify high-risk populations in LGG. It performed well in training and all validation sets (AUC values: 0.915, 0.894, and 0.774). Meanwhile, we found that FDX1 and ATP7A in the four cuproptosis-related genes were positively correlated with immune response, while GCSH and ATP7B were opposite. In addition, the high immune score group had a lower TIDE score, indicating that their immune escape capacity was weak. Conclusion: High-risk individuals in LGG can be reliably identified by the model based on cuproptosis-related genes. Furthermore, cuproptosis is closely related to tumor immune microenvironment, which gives a novel approach to treating LGG.

Detection of Interaction Effects in a Nonparametric Concurrent Regression Model.

Many methods have been developed to study nonparametric function-on-function regression models. Nevertheless, there is a lack of model selection approach to the regression function as a functional function with functional covariate inputs. To study interaction effects among these functional covariates, in this article, we first construct a tensor product space of reproducing kernel Hilbert spaces and build an analysis of variance (ANOVA) decomposition of the tensor product space. We then use a model selection method with the L1 criterion to estimate the functional function with functional covariate inputs and detect interaction effects among the functional covariates. The proposed method is evaluated using simulations and stroke rehabilitation data.

Reply to Correspondence on "Structural Insight into the Catalytic Mechanism of the Endoperoxide Synthase FtmOx1''.

The high-resolution X-ray crystal structure of the ternary complex FtmOx1 ⋅ 2OG ⋅ fumitremorgin B and the catalytic mechanism were recently reported by us (DOI 10.1002/anie.202112063). In their Correspondence, Zhang, Costello, Liu et al. criticize our work in several aspects. Herein, we address these questions one by one. These structural clarifications and new computational results further support the CarC-like mechanistic model.

Structural Insight into the Catalytic Mechanism of the Endoperoxide Synthase FtmOx1.

The 2-oxoglutarate (2OG)-dependent non-heme enzyme FtmOx1 catalyzes the endoperoxide biosynthesis of verruculogen. Although several mechanistic studies have been carried out, the catalytic mechanism of FtmOx1 is not well determined owing to the lack of a reliable complex structure of FtmOx1 with fumitremorgin B. Herein we provide the X-ray crystal structure of the ternary complex FtmOx1⋅2OG⋅fumitremorgin B at a resolution of 1.22 Å. Our structures show that the binding of fumitremorgin B induces significant compression of the active pocket and that Y68 is in close proximity to C26 of the substrate. Further MD simulation and QM/MM calculations support a CarC-like mechanism, in which Y68 acts as the H atom donor for quenching the C26-centered substrate radical. Our results are consistent with all available experimental data and highlight the importance of accurate complex structures in the mechanistic study of enzymatic catalysis.

Coordination Switch Drives Selective C-S Bond Formation by the Non-Heme Sulfoxide Synthases.

The non-heme iron ergothioneine synthase (EgtB) is a sulfoxide synthase that catalyzes oxidative C-S bond formation in the synthesis of ergothioneine, which plays roles against oxidative stress in cells. Despite extensive experimental and computational studies of the catalytic mechanisms of EgtB, the root causes for the selective C-S bond formation remain elusive. Using quantum mechanics/molecular mechanics (QM/MM) calculations, we show herein that a coordination switch of the sulfoxide intermediate is involved in the catalysis of the non-heme iron EgtB. This coordination switch from the S to the O atom is driven by the S/π electrostatic interactions, which efficiently promotes the observed stereoselective C-S bond formation while bypassing cysteine dioxygenation. The present mechanism is in agreement with all available experimental data, including regioselectivity, stereoselectivity and KIE results. This match underscores the critical role of coordination switching in the catalysis of non-heme enzymes.

Conformational Motion of Ferredoxin Enables Efficient Electron Transfer to Heme in the Full-Length P450TT.

Cytochrome P450 monooxygenases (P450s) are versatile biocatalysts used in natural products biosynthesis, xenobiotic metabolisms, and biotechnologies. In P450s, the electrons required for O2 activation are supplied by NAD(P)H through stepwise electron transfers (ETs) mediated by redox partners. While much is known about the machinery of the catalytic cycle of P450s, the mechanisms of long-range ET are largely unknown. Very recently, the first crystal structure of full-length P450TT was solved. This enables us to decipher the interdomain ET mechanism between the [2Fe-2S]-containing ferredoxin and the heme, by use of molecular dynamics simulations. In contrast to the "distal" conformation characterized in the crystal structure where the [2Fe-2S] cluster is ∼28 Šaway from heme-Fe, our simulations demonstrated a "proximal" conformation of [2Fe-2S] that is ∼17 Š[and 13.7 Šedge-to-edge] away from heme-Fe, which may enable the interdomain ET. Key residues involved in ET pathways and interdomain complexation were identified, some of which have already been verified by recent mutation studies. The conformational transit of ferredoxin between "distal" and "proximal" was found to be controlled mostly by the long-range electrostatic interactions between the ferredoxin domain and the other two domains. Furthermore, our simulations show that the full-length P450TT utilizes a flexible ET pathway that resembles either P450Scc or P450cam. Thus, this study provides a uniform picture of the ET process between reductase domains and heme domain.

How Oxygen Binding Enhances Long-Range Electron Transfer: Lessons From Reduction of Lytic Polysaccharide Monooxygenases by Cellobiose Dehydrogenase.

Long-range electron transfer (ET) in metalloenzymes is a general and fundamental process governing O2 activation and reduction. Lytic polysaccharide monooxygenases (LPMOs) are key enzymes for the oxidative cleavage of insoluble polysaccharides, but their reduction mechanism by cellobiose dehydrogenase (CDH), one of the most commonly used enzymatic electron donors, via long-range ET is still an enigma. Using multiscale simulations, we reveal that interprotein ET between CDH and LPMO is mediated by the heme propionates of CDH and solvent waters. We also show that oxygen binding to the copper center of LPMO is coupled with the long-range interprotein ET. This process, which is spin-regulated and enhanced by the presence of O2 , directly leads to LPMO-CuII -O2- , bypassing the formation of the generally assumed LPMO-CuI species. The uncovered ET mechanism rationalizes experimental observations and might have far-reaching implications for LPMO catalysis as well as the O2 - or CO-binding-enhanced long-range ET processes in other metalloenzymes.

Electric-Field Mediated Chemistry: Uncovering and Exploiting the Potential of (Oriented) Electric Fields to Exert Chemical Catalysis and Reaction Control.

This Perspective discusses oriented external-electric-fields (OEEF), and other electric-field types, as "smart reagents", which enable in principle control over wide-ranging aspects of reactivity and structure. We discuss the potential of OEEFs to control nonredox reactions and impart rate-enhancement and selectivity. An OEEF along the "reaction axis", which is the direction whereby electronic reorganization converts reactants' to products' bonding, will accelerate reactions, control regioselectivity, induce spin-state selectivity, and elicit mechanistic crossovers. Simply flipping the direction of the OEEF will lead to inhibition. Orienting the OEEF off the reaction axis enables control over stereoselectivity, enantioselectivity, and product selectivity. For polar/polarizable reactants, the OEEF itself will act as tweezers, which orient the reactants and drive their reaction. OEEFs also affect bond-dissociation energies and dissociation modes (covalent vs ionic), as well as alteration of molecular geometries and supramolecular aggregation. The "key" to gaining access to this toolbox provided by OEEFs is microscopic control over the alignment between the molecule and the applied field. We discuss the elegant experimental methods which have been used to verify the theoretical predictions and describe various alternative EEF sources and prospects for upscaling OEEF catalysis in solvents. We also demonstrate the numerous ways in which the OEEF effects can be mimicked by use of (designed) local-electric fields (LEFs), i.e., by embedding charges or dipoles into molecules. LEFs and OEEFs are shown to be equivalent and to obey the same ground rules. Outcomes are exemplified for Diels-Alder cycloadditions, oxidative addition of bonds by transition-metal complexes, H-abstractions by oxo-metal species, ionic cleavage of halogen bonds, methane activation, etc.

Sequential adaptive variables and subject selection for GEE methods.

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process-such as the active-learning methods found in the machine-learning literature-will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method.

Oriented-External Electric Fields Create Absolute Enantioselectivity in Diels-Alder Reactions: Importance of the Molecular Dipole Moment.

The manuscript studies the enantioselectivity and stereoselectivity of Diels-Alder (DA) cycloadditions between cyclopentadiene (CPD) and a variety of dienophiles (ranging from halo-ethenes to cyano-ethenes), under oriented external electric fields (OEEFs). Applying OEEFs oriented in the X/ Y directions, perpendicular to the reaction axis ( Z), will achieve complete isomeric and enantiomeric discrimination of the products. Unlike the Z-OEEF, which involves charge-transfer from the diene to the dienophile, and thereby brings about catalysis due to increased intramolecular bonding, an OEEF along X, aligned parallel to the C1-C4 atoms of CPD, will lead to R/ S enantiomeric discrimination by means of intramolecular-bond polarization. A Y field will discriminate endo/exo stereoisomers in a similar mechanism. The XY field-combination will resolve both R/S and endo/exo. The resolution is complete and can be achieved at will by flipping the direction of the field along the X and Y axes. The preconditions for achieving the enantiomeric and isomeric discrimination are discussed and require fixing of the CPD onto a surface. In so doing the chiral discrimination is achieved by dipole-moment selection rules, such that the field filters out one of the enantiomers, which is highly raised in energy by dipole selection. The dependence of the discrimination on the polarity of the dienophiles leads to a predictive trend.

Dynamics of bridge helix bending in RNA polymerase II.

One of critical issues for RNA polymerase is how the enzyme translocates along the DNA substrate during transcription elongation cycle. Comparisons of the structure of RNA polymerase II (Pol II) with that of bacterial enzyme have suggested that the transition of the bridge helix (BH) from straight to flipped-out conformations facilitates the translocation of upstream DNA-RNA hybrid. However, the flipped-out conformation of BH in Pol II has not been observed up to now and the detailed mechanism of how the BH facilitating upstream hybrid translocation still remains obscure. Here we use all-atom molecular dynamics simulations to study the transition dynamics of BH in Pol II. Two different flipped-out conformations (termed as F1 and F2) are derived from our simulation trajectories, both of which could contribute to upstream hybrid translocation. In particular, the structure of BH in F2 conformation shows nearly identical to that observed in free bacterial enzyme, showing the existence of the flipped-out conformation in Pol II. Analysis of hydrogen bonds and salt bridge formed intra BH in different conformations indicates that the flipped-out conformations are more unstable than the straight conformation. Moreover, a detailed understanding of how the transition of BH conformations facilitating upstream hybrid translocation is given. Proteins 2017; 85:614-629. © 2016 Wiley Periodicals, Inc.

Self-assembly of glutamic acid linked paclitaxel dimers into nanoparticles for chemotherapy.

In this work, a glutamic acid linked paclitaxel (PTX) dimer (Glu-PTX2) with high PTX content of 88.9wt% was designed and synthesized. Glu-PTX2 could self-assemble into nanoparticles (Glu-PTX2 NPs) in aqueous solution to increase the water solubility of PTX. Glu-PTX2 NPs were characterized by electron microscopy and dynamic light scattering, exhibiting spherical morphology and favorable structural stability in aqueous media. Glu-PTX2 NPs could be internalized by cancer cells as revealed by confocal laser scanning microscopy and exert potent cytotoxicity. It is envisaged that Glu-PTX2 NPs would be an alternative formulation for PTX, and such amino acid linked drug dimers could also be applied to other therapeutic agents.

Screening of Critical Genes and MicroRNAs in Blood Samples of Patients with Ruptured Intracranial Aneurysms by Bioinformatic Analysis of Gene Expression Data.

BACKGROUND This study aimed to identify more potential genes and miRNAs associated with the pathogenesis of intracranial aneurysms (IAs). MATERIAL AND METHODS The dataset of GSE36791 (accession number) was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened for in the blood samples from patients with ruptured IAs and controls, followed by functional and pathway enrichment analyses. In addition, gene co-expression network was constructed and significant modules were extracted from the network by WGCNA R package. Screening for miRNAs that could regulate DEGs in the modules was performed and an analysis of regulatory relationships was conducted. RESULTS A total of 304 DEGs (167 up-regulated and 137 down-regulated genes) were screened for in blood samples from patients with ruptured IAs compared with those from controls. Functional enrichment analysis showed that the up-regulated genes were mainly associated with immune response and the down-regulated DEGs were mainly concerned with the structure of ribosome and translation. Besides, six functional modules were significantly identified, including four modules enriched by up-regulated genes and two modules enriched by down-regulated genes. Thereinto, the blue, yellow, and turquoise modules of up-regulated genes were all linked with immune response. Additionally, 16 miRNAs were predicted to regulate DEGs in the three modules associated with immune response, such as hsa-miR-1304, hsa-miR-33b, hsa-miR-125b, and hsa-miR-125a-5p. CONCLUSIONS Several genes and miRNAs (such as miR-1304, miR-33b, IRS2 and KCNJ2) may take part in the pathogenesis of IAs.

In silico analyses of antigenicity and surface structure variation of an emerging porcine circovirus genotype 2b mutant, prevalent in southern China from 2013 to 2015.

Porcine circovirus type 2 (PCV2) is the pivotal pathogen causing porcine circovirus-associated diseases. In this study, 62 PCV2 isolates were identified from seven farms in southern China from 2013 to 2015 and phylogenetic trees were reconstructed based on whole-genome sequences or the cap gene. In this investigation, PCV2b was the main genotype in circulation throughout these farms. Furthermore, an emerging mutant (PCV2b-1C), isolated from PCV2-vaccinated farms, was the predominant strain prevalent on these farms. In addition, we isolated a new cluster that may represent evolution of the virus through recombination of PCV2b-1A/1B and PCV2b-1C. Finally, we discuss evidence that antigenicity and surface structure variation of the capsid resulted from mutation of the C-terminal loop (Loop CT) of the PCV2b-1C Cap in silico.

Generation of E. coli-derived virus-like particles of porcine circovirus type 2 and their use in an indirect IgG enzyme-linked immunosorbent assay.

Porcine circovirus type 2 (PCV2) causes increased mortality and poor growth or weight loss in apparently healthy swine. Therefore, methods to detect PCV2-specific antibodies in swine serum are important for prevention, diagnosis, and control of PCV2-associated diseases (PCVAD). In this study, PCV2 virus-like particles (VLPs) were used to develop a rapid, simple and economical indirect enzyme-linked immunosorbent assay to detect (with high sensitivity) PCV2-specific antibodies in swine serum. The PCV2 capsid protein (Cap) was overexpressed in E. coli after optimizing the cap gene. Subsequently, the soluble Cap was rapidly purified in one step by automated fast protein liquid chromatography (FPLC). The purified PCV2 Cap was shown by transmission electron microscopy and gel filtration chromatography to be capable of self-assembling into VLPs in vitro. Using the purified VLPs as antigens, optimal operating conditions for the VLP ELISA were determined. The concentration of PCV2 VLPs was 1 µg/ml per well, and the dilution factors for swine serum and horseradish peroxidase (HRP)-labeled goat anti-pig antibody were 1:150 and 1:4000, respectively. Out of 241 serum samples tested with this assay, 83.4 % were found to be positive. Importantly, the VLP ELISA had a total coincidence rate of 97.4 % (74/76) compared to an Ingezim PCV2 ELISA IgG assay. In summary, this rapid, inexpensive VLP ELISA has the potential to greatly facilitate large-scale investigations of PCV2-associated serotypes.

Assessing the predictive power of newly added biomarkers.

As medical research and technology advance, there are always new biomarkers found and predictive models proposed for improving the diagnostic performance of diseases. Therefore, in addition to the existing biomarkers and predictive models, how to assess new biomarkers becomes an important research problem. Many classification performance measures, which are usually based on the performance on the whole cut-off values, were applied directly to this type of problems. However, in a medical diagnosis, some cut-off points are more important, such as those points within the range of high specificity. Thus, as the partial area under the ROC curve to the area under ROC curve, we study the partial integrated discriminant improvement (pIDI) for evaluating the predictive ability of a newly added marker at a prespecified range of cut-offs. Theoretical property of estimate of the proposed measure is reported. The performance of this new measure is then compared with that of the partial area under an ROC curve. The numerical results use synthesized are presented, and a liver cancer dataset is used for demonstration purposes.