Assessment of the Quality of Energy Functions for Protein Folding by Using a Criterion Derived With the Help of the Noisy Go Model

We propose a simple criterion based on the Z-scoreto assess the quality of energy functions for protein folding: one should obtain Z<–10 for the equilibrium ensembleat about native conditions. We derive this criterionby studying a Go model with random errors added to the native interactions. The dependence of the Z-score on the thermodynamic parameters,including the noise, can be precisely obtained in this case,as the ground state of the model is known exactly.We apply this criterion to rapidly rule out two otherwise promisingpairwise energy approximations.The advantage of adopting the present criterionis that it is not necessary to know the ground state of an energy function to assess its quality. It is sufficient to compute the Z-scorefrom a single equilibrium simulation at around the folding temperature.     

基于随机森林模型和GIS的假臭草全国适生区预测

假臭草Praxelisclematidea已对我国南方植物造成严重危害,通过预测其在中国的适生区,可为农林部门制定与加强防控措施提供科学依据。以我国296个假臭草分布记录点、国内气候因子和地形因子为基础,利用随机森林模型和地理信息系统(GIS)技术预测其在我国的潜在适生区。随机森林模型预测结果可信;影响假臭草分布的主要环境因子是最冷月份最低温度,其次是年均降水量,而地形因子和土地利用类型的影响较小;假臭草的主要适生区域位于我国南方各省(区),其中广东、广西、海南、福建、江西南部、云南西南部属于假臭草的高度适生区,占全国陆地面积8.08%;浙江沿海、江西中部、四川与重庆交界处等地区属于中度或一般适生区,占全国陆地面积2.32%和3.37%;低适生区和非适生区分别占全国陆地面积的9.09%和77.14%。在未来气候情景下,假臭草适生区总面积与现阶段相比无明显变化,但中度适生区面积增长明显,由2.32%增至4.33%。因此,在全球气候变暖的环境下,假臭草在国内还未达到最大繁殖范围,有持续扩散的可能性。     

Parameterizing Potential Exposure to Sulfur Mustard (HD) Using Mixed Model Regression

The possible threat posed by terrorists using chemical warfare agents (CWAs) against civilian targets is a major concern, reflecting the fact that CWAs are highly toxic to unprotected populations, with releases as vapors or aerosols likely to produce mass casualties on a highly localized basis within minutes or hours after an incident. A conceptual site model is developed and mixed model regression is used to estimate concentration values for the vesicant sulfur mustard (HD) based on the output from computational fluid dynamics (CFD) simulation following wind tunnel experimentation. The analysis provides a first-approximation of the spatial and temporal distribution of potential exposures within a set of 50 m × 50 m × 2 m grids across a 1000 m width by 300 m height by 2250 m length domain in a geographic information system (GIS) environment. The HD concentration values are calculated as log-averaged mean and the 95% confidence intervals for each grid at 1.9 d and 6.0 d after initial release. The technique offers a statistically valid means for rapidly generating unbiased first-approximations of concentration values subsequent to an initial release as an alternative to extensive monitoring or multiple runs of CFD models to parameterize potential exposure to HD spatially and temporally.     

Modeling-Dependent Protein Characterization of the Rice Aldehyde Dehydrogenase (ALDH) Superfamily Reveals Distinct Functional and Structural Features

The completion of the rice genome sequence has made it possible to identify and characterize new genes and to perform comparative genomics studies across taxa. The aldehyde dehydrogenase (ALDH) gene superfamily encoding for NAD(P)⁺-dependent enzymes is found in all major plant and animal taxa. However, the characterization of plant ALDHs has lagged behind their animal- and prokaryotic-ALDH homologs. In plants, ALDHs are involved in abiotic stress tolerance, male sterility restoration, embryo development and seed viability and maturation. However, there is still no structural property-dependent functional characterization of ALDH protein superfamily in plants. In this paper, we identify members of the rice ALDH gene superfamily and use the evolutionary nesting events of retrotransposons and protein-modeling–based structural reconstitution to report the genetic and molecular and structural features of each member of the rice ALDH superfamily in abiotic/biotic stress responses and developmental processes. Our results indicate that rice-ALDHs are the most expanded plant ALDHs ever characterized. This work represents the first report of specific structural features mediating functionality of the whole families of ALDHs in an organism ever characterized.     

Sweetpotato- and Cereal-Based Infant Foods: Protein Quality Assessment,and Effect on Body Composition Using Sprague Dawley Rats as a Model

The Protein Digestibility Corrected Amino Acid Score (PDCAAS) of sweetpotato-based complementary foods (OFSP ComFa and CFSP ComFa) and cereal-based infant products (Weanimix and Cerelac) was assessed using 3 wk-old male Sprague Dawley rats weighing between 53–67 g as a model for human infants. Also, the effect of consumption of the infant formulations on lean mass, bone mass content and fat mass was evaluated by Dual-Energy X-ray Absorptiometry (DEXA) using 6 wk-old Sprague Dawley rats (initial weight, 206-229 g). The ComFa products and Weanimix are household-level formulations, and Cerelac is a commercial infant cereal. The true protein digestibility score for Cerelac was 96.27%, and about 1.8% (P<0.0001) higher than that for OFSP ComFa, CFSP ComFa and Weanimix. However, OFSP ComFa had the highest un-truncated PDCAAS by a difference of 4.1%, than CFSP ComFa, and about 20% difference compared with both the Weanimix and Cerelac. All the products investigated had PDCAAS greater than 70%, the minimum protein quality requirement for complementary foods. Among the rats assigned to the four formulations, their bone mass and fat mass composition were not significantly different (P=0.08 and P=0.85, respectively). However, the rats on CFSP ComFa had higher lean mass than those on Cerelac (321.67 vs. 297.19 g; P=0.03). The findings from the PDCAAS and the DEXA-measured body composition studies indicate that complementary foods could be formulated from readily available agricultural resources at the household-level to support growth as would a nutritionally adequate industrial-manufactured infant cereal. Nonetheless, it should be noted that the findings of our studies are based on an animal model.     

Structural and Dynamical Features of Inteins and Implications on Protein Splicing

Protein splicing is a posttranslational modification where intervening proteins (inteins) cleave themselves from larger precursor proteins and ligate their flanking polypeptides (exteins) through a multistep chemical reaction. First thought to be an anomaly found in only a few organisms, protein splicing by inteins has since been observed in microorganisms from all domains of life. Despite this broad phylogenetic distribution, all inteins share common structural features such as a horseshoe-like pseudo two-fold symmetric fold, several canonical sequence motifs, and similar splicing mechanisms. Intriguingly, the splicing efficiencies and substrate specificity of different inteins vary considerably, reflecting subtle changes in the chemical mechanism of splicing, linked to their local structure and dynamics. As intein chemistry has widespread use in protein chemistry, understanding the structural and dynamical aspects of inteins is crucial for intein engineering and the improvement of intein-based technologies.     

Using Gross Energy Improves Metabolizable Energy Predictive Equations for Pet Foods Whereas Undigested Protein and Fiber Content Predict Stool Quality

Because animal studies are labor intensive, predictive equations are used extensively for calculating metabolizable energy (ME) concentrations of dog and cat pet foods. The objective of this retrospective review of digestibility studies, which were conducted over a 7-year period and based upon Association of American Feed Control Officials (AAFCO) feeding protocols, was to compare the accuracy and precision of equations developed from these animal feeding studies to commonly used predictive equations. Feeding studies in dogs and cats (331 and 227 studies, respectively) showed that equations using modified Atwater factors accurately predict ME concentrations in dog and cat pet foods (r² = 0.97 and 0.98, respectively). The National Research Council (NRC) equations also accurately predicted ME concentrations in pet foods (r² = 0.97 for dog and cat foods). For dogs, these equations resulted in an average estimate of ME within 0.16% and 2.24% of the actual ME measured (equations using modified Atwater factors and NRC equations, respectively); for cats these equations resulted in an average estimate of ME within 1.57% and 1.80% of the actual ME measured. However, better predictions of dietary ME in dog and cat pet foods were achieved using equations based on analysis of gross energy (GE) and new factors for moisture, protein, fat and fiber. When this was done there was less than 0.01% difference between the measured ME and the average predicted ME (r² = 0.99 and 1.00 in dogs and cats, respectively) whereas the absolute value of the difference between measured and predicted was reduced by approximately 50% in dogs and 60% in cats. Stool quality, which was measured by stool score, was influenced positively when dietary protein digestibility was high and fiber digestibility was low. In conclusion, using GE improves predictive equations for ME content of dog and cat pet foods. Nondigestible protein and fiber content of diets predicts stool quality.     

Protein Loop Modeling Using a New Hybrid Energy Function and Its Application to Modeling in Inaccurate Structural Environments

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.     

Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging

The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields predictions that surpass those of PLS. It is shown that it is possible to improve the models predictive ability by using two more input features, codon identification number and codon count, besides the already used codon bias and minimum free energy. In addition, applying ensemble averaging to the SVR or PLS models also improves the results even further. The present work motivates the test of different ensembles and features with the aim of improving the prediction models whose correlation coefficients are still far from perfect. These results are relevant for the optimization of codon usage and enhancement of protein expression levels in synthetic biology problems.     

Goldfish Tyrosinase Related Protein I (TRP-1): Deduced Amino Acid Sequence From cDNA and Comments on Structural Features

Previous workers have shown that mammals have tyrosinase and tyrosinase related proteins (TRPs) that share common structural domains, all of which are not present in microbial tyrosinases. We report here the deduced amino acid sequence of a TRP from fish that is highly homologous to mammalian TRP-1. Examination of the structures of these vertebrate tyrosinases and TRPs shows that, aside from the conserved cysteine-rich and histidine-rich domains previously noted, there are a large number of conserved prolines and glycines, leading to an abundance of turns and few conserved helical regions. These tyrosinases and TRP-1s also have in their cytosolic tails a consensus sequence that is not present in any other protein. It is proposed that this sequence may participate in directing these proteins to the melanosomes.     

Environmental Quality Assessment of Bizerte Lagoon (Tunisia) Using Living Foraminifera Assemblages and a Multiproxy Approach

This study investigated the environmental quality of the Bizerte Lagoon (Tunisia) through an integrated approach that combined environmental, biogeochemical, and living benthic foraminiferal analyses. Specifically, we analyzed the physicochemical parameters of the water and sediment. The textural, mineralogical, and geochemical characteristics of the sediment, including total organic carbon, total nitrogen, simultaneously extracted metals (SEM), acid volatile sulfides (AVS), chlorophyll a, CaCO₃, and changes in bacterial populations and carbon isotopes were measured. The SEM/AVS values indicated the presence of relatively high concentrations of toxic metals in only some areas. Foraminiferal assemblages were dominated by species such as A. parkinsoniana (20–91%), Bolivina striatula (<40%), Hopkinsina atlantica (<17%), and Bolivina ordinaria (<15%) that cannot be considered typical of impacted coastal lagoons both in Mediterranean and northeast Atlantic regions. The results of this work suggest that Bizerte Lagoon is a unique setting. This lagoon is populated by typical marine species that invaded this ecosystem, attracted not only by the prevailing favorable environmental conditions but also by the abundance and quality of food. The results indicate that the metal pollution found in some areas have a negative impact on the assemblages of foraminifera. At present, however, this negative impact is not highly alarming.     

猴痘病毒CrmB蛋白的结构特征及其抗原表位分析

为深入了解猴痘病毒(Monkeypox virus, MPXV)的CrmB(cytokine response modifier B)蛋白的结构特征和抗原表位，运用ORF Finder、ExPaSy、SignalP 6.0、TMHMM 2.0、Cell-Ploc、Conserved Domains、 SOPMA、SWISS-MODEL、NetNGlyc 1.0、NetPhos 3.1、IEDB、SYFPEITHI、Clustalx、MEGA 11.0、Prankweb、DrugBank等多种生物信息学方法，分析CrmB蛋白的开放阅读框、理化性质、信号肽、跨膜区、亚细胞定位、结构域、糖基化/磷酸化位点、二级/三级结构、B/T细胞抗原表位、抗原决定簇、蛋白同源性、配体结合位点、小分子抑制药物等。CrmB蛋白是由349个氨基酸组成的不稳定蛋白质，相对分子量为38 308.75;理论等电点为6.24,分子式为C₁₆₂₁H₂₅₅₀N₄₆₀O₅₅₀S₃₂;二级结构以不规则卷曲为主，有信号肽...     

Identification of DNA-binding Proteins Using Structural, Electrostatic and Evolutionary Features

DNA-binding proteins (DBPs) participate in various crucial processes in the life-cycle of the cells, and the identification and characterization of these proteins is of great importance. We present here a random forests classifier for identifying DBPs among proteins with known 3D structures. First, clusters of evolutionarily conserved regions (patches) on the surface of proteins were detected using the PatchFinder algorithm; earlier studies showed that these regions are typically the functionally important regions of proteins. Next, we trained a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein, including its dipole moment. Using 10-fold cross-validation on a dataset of 138 DBPs and 110 proteins that do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of published methods. Furthermore, when we tested five different methods on 11 new DBPs that did not appear in the original dataset, only our method annotated all correctly.The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA.     

Unified Saliency Detection Model Using Color and Texture Features

Saliency detection attracted attention of many researchers and had become a very active area of research. Recently, many saliency detection models have been proposed and achieved excellent performance in various fields. However, most of these models only consider low-level features. This paper proposes a novel saliency detection model using both color and texture features and incorporating higher-level priors. The SLIC superpixel algorithm is applied to form an over-segmentation of the image. Color saliency map and texture saliency map are calculated based on the region contrast method and adaptive weight. Higher-level priors including location prior and color prior are incorporated into the model to achieve a better performance and full resolution saliency map is obtained by using the up-sampling method. Experimental results on three datasets demonstrate that the proposed saliency detection model outperforms the state-of-the-art models.     

Deconvoluting Protein (Un)folding Structural Ensembles Using X-Ray Scattering,Nuclear Magnetic Resonance Spectroscopy and Molecular Dynamics Simulation

The folding and unfolding of protein domains is an apparently cooperative process, but transient intermediates have been detected in some cases. Such (un)folding intermediates are challenging to investigate structurally as they are typically not long-lived and their role in the (un)folding reaction has often been questioned. One of the most well studied (un)folding pathways is that of Drosophila melanogaster Engrailed homeodomain (EnHD): this 61-residue protein forms a three helix bundle in the native state and folds via a helical intermediate. Here we used molecular dynamics simulations to derive sample conformations of EnHD in the native, intermediate, and unfolded states and selected the relevant structural clusters by comparing to small/wide angle X-ray scattering data at four different temperatures. The results are corroborated using residual dipolar couplings determined by NMR spectroscopy. Our results agree well with the previously proposed (un)folding pathway. However, they also suggest that the fully unfolded state is present at a low fraction throughout the investigated temperature interval, and that the (un)folding intermediate is highly populated at the thermal midpoint in line with the view that this intermediate can be regarded to be the denatured state under physiological conditions. Further, the combination of ensemble structural techniques with MD allows for determination of structures and populations of multiple interconverting structures in solution.     

Designing of a Novel Fusion Protein Vaccine Candidate Against Human Visceral Leishmaniasis (VL) Using Immunoinformatics and Structural Approaches

Leishmaniasis is caused by an obligate intracellular protozoan parasite. The clinical forms of leishmaniasis differ from cutaneous leishmaniasis, mucocutaneous leishmaniasis and visceral leishmaniasis (VL) which depend on the parasite species and the host’s immune responses. There are significant challenges to the available anti-leishmanial drug therapy, particularly in severe forms of disease, and the rise of drug resistance has made it more difficult. Currently, no licensed vaccines have been introduced to the market for the control and elimination of VL. A potential target for use in candidate vaccines against leishmaniasis has been shown to be leishmania Kinetoplastid membrane protein-11 (KMP-11) antigen. In this study, we chose KMP-11 antigen as target antigen in our vaccine construct. In addition, B-type flagellin (fliC) was used as an adjuvant for enhancing vaccine immunogenicity. The GSGSGSGSGSG linker was applied to link the KMP-11 antigen and fliC (KMP-11-fliC) to construct our fusion protein. Bioinformatics approaches such as; 3D homology modeling, CTL, B-cell, MHC class I and II epitopes prediction, allergenicity, antigenicity evaluations, molecular docking, fast simulations of flexibility of docked complex and in silico cloning were employed to analysis and evaluation of various properties of the designed fusion construct. Computational results showed that our engineered structure has the potential for proper stimulation of cellular and humoral immune responses against VL. Consequently, it could be proposed as a candidate vaccine against VL according to these data and after verifying the efficacy of the candidate vaccine through in vivo and in vitro immunological tests.

     

基于最大信息熵模型的能源物种麻疯树潜在适宜区

麻疯树(Jatropha curcas L.)为传统能源植物,是作为生物柴油最具希望的植物资源之一。本研究通过收集麻疯树分布点的经纬度数据,基于气候、土壤和地形等37个相关生态因子,采用最大信息熵模型,预测麻疯树的潜在适宜区域,分析影响其生长的主要生态因子特征。结果显示,麻疯树生长最适宜区域主要分布在我国华南地区的广东、海南、香港、台湾和西南地区的广西、云南、四川;对麻疯树分布贡献率较大的主要生态因子为:最暖季度降水量(53.5%)、温度季节性变化标准差(15.8%)、降水量变异系数(9.3%)、年均温变化范围(5.8%)、最湿季度降水量(3.6%)、最干月降水量(3.2%);Maxent模型预测的AUC值大于0.9,表明对麻疯树潜在分布的预测结果较准确。本文对麻疯树潜在分布区域以及影响其分布的主要生态条件的研究结果,可为麻疯树的种植栽培提供科学依据。     

Tissue Quality Assessment Using a Novel Direct Elasticity Assessment Device (The E-Finger): A Cadaveric Study of Prostatectomy Dissection

Introduction

Minimally invasive radical prostatectomy (RP) (robotic and laparoscopic), have brought improvements in the outcomes of RP due to improved views and increased degrees of freedom of surgical devices. Robotic and laparoscopic surgeries do not incorporate haptic feedback, which may result in complications secondary to inadequate tissue dissection (causing positive surgical margins, rhabdosphincter damage, etc). We developed a micro-engineered device (6 mm² sized) [E-finger]) capable of quantitative elasticity assessment, with amplitude ratio, mean ratio and phase lag representing this. The aim was to assess the utility of the device in differentiating peri-prostatic tissue types in order to guide prostate dissection.

Material and Methods

Two embalmed and 2 fresh frozen cadavers were used in the study. Baseline elasticity values were assessed in bladder, prostate and rhabdosphincter of pre-dissected embalmed cadavers using the micro-engineered device. A measurement grid was created to span from the bladder, across the prostate and onto the rhabdosphincter of fresh frozen cadavers to enable a systematic quantitative elasticity assessment of the entire area by 2 independent assessors. Tissue was sectioned along each row of elasticity measurement points, and stained with haematoxylin and eosin (H&E). Image analysis was performed with Image Pro Premier to determine the histology at each measurement point.

Results

Statistically significant differences in elasticity were identified between bladder, prostate and sphincter in both embalmed and fresh frozen cadavers (p = <0.001). Intra-class correlation (ICC) reliability tests showed good reliability (average ICC = 0.851). Sensitivity and specificity for tissue identification was 77% and 70% respectively to a resolution of 6 mm².

Conclusions

This cadaveric study has evaluated the ability of our elasticity assessment device to differentiate bladder, prostate and rhabdosphincter to a resolution of 6 mm². The results provide useful data for which to continue to examine the use of elasticity assessment devices for tissue quality assessment with the aim of giving haptic feedback to surgeons performing complex surgery.