Search results for: protein tertiary structure prediction

Authors: Chaoran Liu

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Bioactive polysaccharides and polysaccharide-protein complex derived from mushrooms and fungi have a wide range of immunomodulatory activity with low side-effects and have therefore the potential to be developed as an adjuvant in cancer therapies. Mushrooms sclerotium is rich in polysaccharides and the polysaccharides isolated from the sclerotium of Polyporus rhinocerus have shown potent in vivo and in vitro immunomodulatory effects. Macrophages are considered to be an important component of the innate immune response against bacterial infection and cancer. To better understanding the immunomodulatory effects and its underlying mechanisms of sclerotial water-soluble polysaccharides extracted from P. rhinocerus on macrophages, the objectives of this study are to purify the water-soluble novel sclerotial polysaccharides and to characterize the structure and properties as well as to study the detailed molecular mechanisms of the in vitro immunomodulating effects in murine macrophages. The hot water-soluble fraction PRW from the sclerotium of P. rhinocerus was obtained using solvent extraction. PRW was further fractionated by membrane ultrafiltration to a give a fraction (PRW1) with molecular mass less than 50 kDa. PRW1 was characterized to be a polysaccharide-protein complex composed of 45.7% polysaccharide and 44.2% protein. The chemical structure of the carbohydrate moiety of PRW1 was elucidated by GC and FTIR to be mainly beta-D-glucan with trace amount of galactose and mannose. The immunomodulatory effects of PRW1 on murine RAW 264.7 macrophages were demonstrated in terms of the increase in nitric oxide production and cytokine production. Mechanistically, PRW1 initiates ERK phosphorylation to activate macrophages within 15 min and significantly improves the expression level of inducible NOS (iNOS) from 6 h after treatment. In summary, this study indicates that PRW1 is a potent immunomodulatory agent for macrophages and suggests that mushroom sclerotia from Polyporus rhinocerus requires for further investigation in cancer research.

Keywords: Polyporus rhinocerus, mushroom sclerotia, Polysaccharide-Protein Complex, macrophage activation

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Authors: Arpit Kumar Shrivastava, Subrat Kumar, Rajani Kanta Mohapatra, Priyadarshi Soumyaranjan Sahu

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Computational approaches to predict structure, function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are not effective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical epitopic protein in C. hominis genome through BLASTP analysis. A 3D model of the hypothetical protein was generated using I-Tasser server through threading methodology. The quality of the model was validated through Ramachandran plot by PROCHECK server. The functional annotation of the hypothetical protein through DALI server revealed structural similarity with human Transportin 3. Phylogenetic analysis for this hypothetical protein also showed C. hominis hypothetical protein (CUV04613) was the closely related to human transportin 3 protein. The 3D protein model is further subjected to virtual screening study with inhibitors from the Zinc Database by using Dock Blaster software. Docking study reported N-(3-chlorobenzyl) ethane-1,2-diamine as the best inhibitor in terms of docking score. Docking analysis elucidated that Leu 525, Ile 526, Glu 528, Glu 529 are critical residues for ligand–receptor interactions. The molecular dynamic simulation was done to access the reliability of the binding pose of inhibitor and protein complex using GROMACS software at 10ns time point. Trajectories were analyzed at each 2.5 ns time interval, among which, H-bond with LEU-525 and GLY- 530 are significantly present in MD trajectories. Furthermore, antigenic determinants of the protein were determined with the help of DNA Star software. Our study findings showed a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for control as well as prevention of cryptosporidiosis among humans and animals.

Keywords: cryptosporidium hominis, hypothetical protein, molecular docking, molecular dynamics simulation

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: A. Ojha, Y. K. Gupta

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Organophosphate (OP) pesticides are among the most widely used synthetic chemicals for controlling a wide variety of pests throughout the world. Chlorpyrifos (CPF), methyl parathion (MPT), and malathion (MLT) are among the most extensively used OP pesticides in India. DNA strand breaks and DNA-protein crosslinks (DPC) are toxic lesions associated with the mechanisms of toxicity of genotoxic compounds. In the present study, we have examined the potential of CPF, MPT, and MLT individually and in combination, to cause DNA strand breakage and DPC formation. Peripheral blood lymphocytes of rat were exposed to 1/4 and 1/10 LC50 dose of CPF, MPT, and MLT for 2, 4, 8, and 12h. The DNA strand break was measured by the comet assay and expressed as DNA damage index while DPC estimation was done by fluorescence emission. There was significantly marked increase in DNA damage and DNA-protein crosslink formation in time and dose dependent manner. It was also observed that MPT caused the highest level of DNA damage as compared to other studied OP compounds. Thus, from present study, we can conclude that studied pesticides have genotoxic potential. The pesticides mixture does not potentiate the toxicity of each other. Nonetheless, additional in vivo data are required before a definitive conclusion can be drawn regarding hazard prediction to humans.

Keywords: organophosphate, pesticides, DNA damage, DNA protein crosslink, genotoxic

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Authors: Lucas Viani, Benedetta Mennucci, Soo Young Park, Johannes Gierschner

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Organic semiconductors have attracted the attention of the scientific community in the past decades due to their unique physicochemical properties, allowing new designs and alternative device fabrication methods. Until today, organic electronic devices are largely based on conjugated polymers mainly due to their easy processability. In the recent years, due to moderate ET and CT efficiencies and the ill-defined nature of polymeric systems the focus has been shifting to small conjugated molecules with well-defined chemical structure, easier control of intermolecular packing, and enhanced CT and ET properties. It has led to the synthesis of new small molecules, followed by the growth of their crystalline structure and ultimately by the device preparation. This workflow is commonly followed without a clear knowledge of the ET and CT properties related mainly to the macroscopic systems, which may lead to financial and time losses, since not all materials will deliver the properties and efficiencies demanded by the current standards. In this work, we present a theoretical workflow designed to predict the key properties of ET of these new materials prior synthesis, thus speeding up the discovery of new promising materials. It is based on quantum mechanical, hybrid, and classical methodologies, starting from a single molecule structure, finishing with the prediction of its packing structure, and prediction of properties of interest such as static and averaged excitonic couplings, and exciton diffusion length.

Keywords: organic semiconductor, organic crystals, energy transport, excitonic couplings

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Authors: Oluwatofunmi Otobo

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This paper presents a review of the challenges of e-learning and e-learning technologies in tertiary institutions. This review is based on the researchers observations of the challenges of making use of ICT for learning in Nigeria using Adeyemi College of Education as a case study; this is in comparison to tertiary institutions in the UK, US and other more developed countries. In Nigeria and probably Africa as a whole, power is the major challenge. Its inconsistency and fluctuations pose the greatest challenge to making use of online education inside and outside the classroom. Internet and its supporting infrastructures in many places in Nigeria are slow and unreliable. This, in turn, could frustrate any attempt at making use of online education and e-learning technologies. Lack of basic knowledge of computer, its technologies and facilities could also prove to be a challenge as many young people up until now are yet to be computer literate. Personal interest on both the parts of lecturers and students is also a challenge. Many people are not interested in learning how to make use of technologies. This makes them resistant to changing from the ancient methods of doing things. These and others were reviewed by this paper, suggestions, and recommendations were proffered.

Keywords: education, e-learning, Nigeria, tertiary institutions

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Authors: Nais Pinta Adetya, H. Hadiyanto

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Microalgae has a potential to be utilized as food and natural colorant. The microalgae components consists of three main parts, these are lipid, protein, and carbohydrate. Crucial step in producing lipid and protein from microalgae is extraction. Microalgae has high water level (70-90%), it causes drying process of biomass needs much more energy and also has potential to distract lipid and protein from microalgae. Extraction of lipid from wet biomass is able to take place efficiently with cell disruption of microalgae by osmotic shock method. In this study, osmotic shock method was going to be integrated with ultrasound to maximalize the extraction yield of lipid and protein from wet biomass Spirulina sp. with osmotic shock method assisted ultrasound. This study consisted of two steps, these were osmotic shock process toward wet biomass and ultrasound extraction assisted. NaCl solution was used as osmotic agent, with the variation of concentrations were 10%, 20%, and 30%. Extraction was conducted in 40°C for 20 minutes with frequency of ultrasound wave was 40kHz. The optimal yield of protein (2.7%) and (lipid 38%) were achieved at 20% osmotic agent concentration.

Keywords: extraction, lipid, osmotic shock, protein, ultrasound

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Mitsuhiro Hirai, Satoshi Ajito, Nobutaka Shimizu, Noriyuki Igarashi, Hiroki Iwase, Shinichi Takata

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Sugars and polyols are known to be bioprotectants preventing such as protein denaturation and enzyme deactivation and widely used as a nontoxic additive in various industrial and medical products. The mechanism of their protective actions has been explained by specific bindings between biological components and additives, changes in solvent viscosities, and surface tension and free energy changes upon transfer of those components into additive solutions. On the other hand, some organisms having tolerances against extreme environment produce stress proteins and/or accumulate sugars in cells, which is called cryptobiosis. In particular, trehalose has been drawing attention relevant to cryptobiosis under external stress such as high or low temperature, drying, osmotic pressure, and so on. The function of cryptobiosis by trehalose has been explained relevant to the restriction of the intra-and/or-inter-molecular movement by vitrification or from the replacement of water molecule by trehalose. Previous results suggest that the structure and interaction between sugar and water are a key determinant for understanding cryptobiosis. Recently, we have shown direct evidence that the protein hydration (solvation) and structural stability against chemical and thermal denaturation significantly depend on sugar species and glycerol. Sugar and glycerol molecules tend to be preferentially or weakly excluded from the protein surface and preserved the native protein hydration shell. Due to the protective action of the protein hydration shell by those molecules, the protein structure is stabilized against chemical (guanidinium chloride) and thermal denaturation. The protective action depends on sugar species. To understand the above trend and difference in detail, it is essentially important to clarify the characteristics of solutions containing those additives. In this study, by using wide-angle X-ray scattering technique covering a wide spatial region (~3-120 Å), we have clarified structures of sugar solutions with the concentration from 5% w/w to 65% w/w. The sugars measured in the present study were monosaccharides (glucose, fructose, mannose) and disaccharides (sucrose, trehalose, maltose). Due to observed scattering data with a wide spatial resolution, we have succeeded in obtaining information on the internal structure of individual sugar molecules and on the correlation between them. Every sugar gradually shortened the average inter-molecular distance as the concentration increased. The inter-molecular interaction between sugar molecules was essentially showed an exclusive tendency for every sugar, which appeared as the presence of a repulsive correlation hole. This trend was more weakly seen for trehalose compared to other sugars. The intermolecular distance and spread of individual molecule clearly showed the dependence of sugar species. We will discuss the relation between the characteristic of sugar solution and its protective action of biological materials.

Keywords: hydration, protein, sugar, X-ray scattering

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Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

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Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, chemometrics, molecular modeling, molecular descriptors, QSPR

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Authors: Jer-Yuh Liu, Je-Chiuan Ye, Jin-Ming Hwang

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Protein kinase C alpha (PKCα) is a key signaling molecule in human cancer development. As a therapeutic strategy, targeting PKCα is difficult because the molecule is ubiquitously expressed in non-malignant cells. PKCα is regulated by the cooperative interaction of the transcription factors myeloid zinc finger 1 (MZF-1) and Ets-like protein-1 (Elk-1) in human cancer cells. By conducting tissue array analysis, herein, we determined the protein expression of MZF-1/Elk-1/PKCα in various cancers. The data show that the expression of MZF-1/Elk-1 is correlated with that of PKCα in hepatocellular carcinoma (HCC), but not in bladder and lung cancers. In addition, the PKCα down-regulation by shRNA Elk-1 was only observed in the HCC SK-Hep-1 cells. Blocking the interaction between MZF-1 and Elk-1 through the transfection of their binding domain MZF-160–72 decreased PKCα expression. This step ultimately depressed the epithelial-mesenchymal transition potential of the HCC cells. These findings could be used to develop an alternative therapeutic strategy for patients with the PKCα-derived HCC.

Keywords: protein kinase C alpha, myeloid zinc finger 1, ets-like protein-1, hepatocellular carcinoma

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Authors: Geng Xiangren, Liu Lei, Gui Ye-Wei, Tang Wei, Wang An-ling

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The malfunction of thermal protection system (TPS) caused by aerodynamic heating is a latent trouble to aircraft structure safety. Accurately predicting the structure temperature field is quite important for the TPS design of hypersonic vehicle. Since Thornton’s work in 1988, the coupled method of aerodynamic heating and heat transfer has developed rapidly. However, little attention has been paid to the influence of structural deformation on aerodynamic heating and structural temperature field. In the flight, especially the long-endurance flight, the structural deformation, caused by the aerodynamic heating and temperature rise, has a direct impact on the aerodynamic heating and structural temperature field. Thus, the coupled interaction cannot be neglected. In this paper, based on the method of static aero-thermo-elasticity, considering the influence of aero-thermo-elasticity deformation, the aerodynamic heating and heat transfer coupled results of hypersonic vehicle wing model were calculated. The results show that, for the low-curvature region, such as fuselage or center-section wing, structure deformation has little effect on temperature field. However, for the stagnation region with high curvature, the coupled effect is not negligible. Thus, it is quite important for the structure temperature prediction to take into account the effect of elastic deformation. This work has laid a solid foundation for improving the prediction accuracy of the temperature distribution of aircraft structures and the evaluation capacity of structural performance.

Keywords: aerothermoelasticity, elastic deformation, structural temperature, multi-field coupling

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Authors: Odunayo E. Popoola, Charles A. Aladesaye, Sunday O. Gbenro

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The study investigated the impact of technological advancement on the academic performance of Mathematics students in tertiary institutions in Ekiti State, Nigeria. The quasi-experimental research design was adopted for the study. The population for the study consisted of all the 100 level undergraduates and all Mathematics lecturers in the Department of Mathematics in all the five tertiary institutions in the State. The sample of this study was made of one hundred (100) students and fifty (50) lecturers randomly selected using stratified sampling technique. Hypotheses were postulated to find out whether (i) advancement in technology influences the academic performance of students in Mathematics (ii) teaching method and gender disparity influences the academic performance of students in Mathematics. The study revealed that teaching method, gender, and technology influence academic performance of students in Mathematics. Based on the findings, it is recommended that curriculum and assessment in school Mathematics should explicitly require that all undergraduate become proficient in using digital technologies for mathematical purposes so as to enhance the better performance of students in Mathematics.

Keywords: mathematics, performance, tertiary institutions, technology

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Authors: Usha Kiran, M. Z. Abdin

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Osmotin is an abundant cationic multifunctional protein discovered in cells of tobacco (Nicotiana tabacum L. var Wisconsin 38) adapted to an environment of low osmotic potential. It provides plants protection from pathogens, hence placed in the PRP family of proteins. The osmotin induced proline accumulation has been reported in plants including transgenic tomato and strawberry conferring tolerance against both biotic and abiotic stresses. The exact mechanism of induction of proline by osmotin is however, not known till date. These observations have led us to hypothesize that osmotin induced proline accumulation could be due to its involvement as transcription factor and/or cell signal pathway modulator in proline biosynthesis. The present investigation was therefore, undertaken to analyze the osmotin protein as transcription factor /cell signalling modulator using bioinformatics tools. The results of available online DNA binding motif search programs revealed that osmotin does not contain DNA-binding motifs. The alignment results of osmotin protein with the protein sequence from DATF showed the homology in the range of 0-20%, suggesting that it might not contain a DNA binding motif. Further to find unique DNA-binding domain, the superimposition of osmotin 3D structure on modeled Arabidopsis transcription factors using Chimera also suggested absence of the same. We, however, found evidence implicating osmotin in cell signaling. With these results, we concluded that osmotin is not a transcription factor but regulating proline biosynthesis and accumulation through cell signaling during abiotic stresses.

Keywords: osmotin, cell signaling modulator, bioinformatic tools, protein

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Authors: Tayeb Chihi, Messaoud Fatmi

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We present calculations of the structural, elastic and electronic properties of nonferrous Ti, Zr, and Hf pure metals in both parent and martensite phases in bcc and hcp structures respectively. They are based on the generalized gradient approximation (GGA) within the density functional theory (DFT). The shear modulus, Young's modulus and Poisson's ratio for Ti, Zr, and Hf metals have were calculated and compared with the corresponding experimental values. Using elastic constants obtained from calculations GGA, the bulk modulus along the crystallographic axes of single crystals was calculated. This is in good agreement with experiment for Ti and Zr, whereas the hcp structure for Hf is a prediction. At zero temperature and zero pressure, the bcc crystal structure is found to be mechanically unstable for Ti, Zr, and Hf. In our calculations the hcp structures is correctly found to be stable at the equilibrium volume. In the electronic density of states (DOS), the smaller n(EF) is, the more stable the compound is. Therefore, in agreement with the results obtained from the total energy minimum.

Keywords: Ti, Zr, Hf, pure metals, transformation, energy

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Authors: Hatairuk Tungkasen, Somrudee Phetchrid, Suwapat Jaidee, Supinya Yoomak, Chantana Kankamol, Mayuree Pumipaiboon, Mayuva Areekijseree

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Ovaries of reproductive female pigs were obtained from local slaughterhouses in Nakorn Pathom Province, Thailand. Follicular fluid of medium follicle (5-6 diameters) and large follicles (7-8 mm and 10 mm in diameter) were aspirated and collected by sterile technique and analyzed protein pattern. The follicular fluid protein bands were found by SDS-PAGE which has no protein band in difference compared to standard protein band. So we chose protein band molecular weight 50, 62-65, 75-80, 90, 120-160, and >220 kDa were analyzed by LC/MS/MS. The result was found immunoglobulin gamma chain, keratin, transferrin, heat shock protein, and plasminogen precursor, ceruloplasmin, and hemopexin, and protease, respectively. All proteins play important roles in promotion and regulation on growth and development of reproductive cells. The result of this study found many proteins which were useful and important for in vitro oocyte maturation and embryonic development of cell technology in animals. The further study will be use porcine follicular fluid protein of medium and large follicles as feeder cells in in vitro condition to promote oocyte and embryo maturation.

Keywords: follicular fluid protein, LC/MS/MS, porcine oocyte, SDS-PAGE

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Authors: Chaiyaporn Yuksen

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Backgroud: Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). Method: The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. Result: 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times Conclusion: The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: clinical prediction score, SVT, recurrence, emergency department

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Authors: Hanan Azzam1, Nashwa Abousamra1, Amany Mansour1, Yaser Abd El-dayem2, , Solafa Elsharawy1

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Background: Inherited thrombophilias are a heterogenous group of conditions which have been implicated in a variety of pregnancy complications. More recently, deficiency of protein Z (PZ) has been liked to pregnancy complications, including preterm delivery. Aim: We designed this study to evaluate the association of inherited thrombophilias including [Protein C (PC), Protein S (PS), Anti thrombin III (ATIII) deficiency and activated protein C (APC) resistance] and protein Z deficiency with a variety of pregnancy complications. Patients and Methods: 60 women with different pregnancy complications, including 20 patients with preeclampsia, 20 patients with intrauterine growth resistance (IUGR), and 20 patients with intrauterine fetal death (IUFD), in addition to 30 healthy pregnant women were recruited for the present study. PC and free PS antigen, ATIII activity, modified functional APC-resistance, and PZ levels were determined. Results: There was no significant association between inherited thrombophilias and complicated pregnancies as regards PC deficiency (p=1.0), AT III and PS deficiency (p=0.312), and APC-resistance (P=0.083). PZ was significantly associated with complicated pregnancies (p=0.012). Patients with protein Z levels below 1.5 µg/ml were considered deficient. Accordingly, we demonstrated protein Z deficiency in 30% of complicated pregnancies (RR 6.0, 95% CI 1.29-27.90;p=0.022), 20% of preeclampsia (RR 3.5, 95% CI 0.57 – 21.28; P = 0.174), 40% of IUGR (RR 9.3 95% CI 1.72-50.61; P = 0.010) and 30% of IUFD (RR 6, 95% CI 1.07 – 33.64; P = 0.042). Conclusions: These findings indicate the absence of association of inherited thrombophilias, including PC, PS, AT III deficiency, and APC resistance with pregnancy complications. However, PZ deficiency is associated with increased risk of pregnancy complications, especially intrauterine growth restriction and intrauterine fetal death.

Keywords: protein C, protein S, thrombophelia, pregnancy, protein Z

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Sireethorn Nimitvilai, Ussanee Poolvivatchaikarn, Nuchanart Tomeun

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Objective: To determine the simple laboratory parameters to predict disease severity among COVID-19 patients in resource-limited settings. Material and methods: A retrospective cohort study was conducted at Nakhonpathom Hospital, a 722-bed tertiary care hospital, with an average of 50,000 admissions per year, during April 15 and May 15, 2021. Eligible patients were adults aged ≥ 15 years who were hospitalized with COVID-19. Baseline characteristics, comorbid conditions ad laboratory findings at admission were collected. Predictive factors for severe COVID-19 infection were analyzed. Result: There were 207 patients (79 male and 128 female) and the mean age was 46.7 (16.8) years. Of these, 39 cases (18.8%) were severe and 168 (81.2%) cases were non-severe. Factors associated with severe COVID-19 were neutrophil to lymphocyte ratio ≥ 4 (OR 8.1, 95%CI 2.3-20.3, P < 0.001) and C-reactive protein to albumin ratio ≥ 10 (OR 3.49, 95%CI 1.3-9.1, p 0.01). Conclusions: Complete blood counts, C-reactive protein and albumin are simple, inexpensive, widely available tests and can be used to predict severe COVID-19 in resource-limited settings.

Keywords: COVID-19, predictor of severity, resource-limiting settings, simple laboratory parameters

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Sihame Amakrane, Zineb Ouahdi, Mohammed Salah, Said Belaaouad

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\This research explores the efficacy of novel pyrimidine derivatives on bacterial strains such as Escherichia coli, Staphylococcus aureus, and Myccobacterium tuberculosis, utilizing bending energy calculations. Of the 25 compounds examined, 13 displayed potent activity against all the bacterial strains under study, exhibiting bending energy measurements between -7.4 and -10.7 kcal/mol. The -7.4 kcal/mol value corresponds to the bending energy of the SA12 and SA13 compounds with the 2xct protein (Staphylococcus aureus), whereas the -10.7 kcal/molis linked with the bending energy of SA6 and SA11 compounds with the 6GAV protein (Myccobacterium tuberculosis). Further research will involve a QSAR (Quantitative Structure-Activity Relationship) study aimed at constructing a reliable model to combat the aforementioned bacterial strains and a molecular dynamics study to evaluate the stability of ligand-protein complexes.

Keywords: docking, QSAR, bending energy, e. coli

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Authors: Ayoola, Simeon Oluwatoyin, Omogoriola Hannah Omoloye

Abstract:

The effects of 17α-Methyltestosterone Hormone on blood composition of the Sex Reversed Sarotherodon melanotheron were investigated. S. melanotheron fry were reared in six (6) plastic tanks for three (3) months, of which three (3) tanks served as treatment tanks while the other three (3) served as the control. The fry were fed with 17α-methyl testosterone enzyme, which functions as a sex reversal hormone. The fry were administered this hormone for 30 days, to ensure complete sex reversal. All the S. melanotheron fry were reared to table size for duration of three (3) months, after which, blood samples were taken from both the control and treatment fishes. The blood parameters showed no significant differences with the same values of White Blood Cell count (WBC) and Total plasma protein for the control and experimental fishes. A total protein value for sex reversed specimens was 3.99g/dL, while urea and creatinine values were 0.2g/dL. Alkaline Phosphatase, Aspartate transaminase and Alanine transaminase for the treatment specimen were 183nm/mg protein/min, 98nm/mg protein/min and 105nm/mg protein/min respectively. A total protein value for control specimens was 2.81g/dL, while urea and creatinine values were 0.2g/dL. Alkaline Phosphatase, Aspartate transaminase and Alanine transaminase for the control species were 174nm/mg protein/min, 93nm/mg protein/min and 106nm/mg protein/min respectively. The safety of MT on S. melanotheron is therefore proved since there is no adverse effect on the fish.

Keywords: 17α-Methyltestosterone, haematology, sex reversal, sarotherodon melanotheron

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Authors: Alise Senberga, Laila Dubova, Liene Strauta, Ina Alsina, Ieva Erdberga

Abstract:

Legume symbiotic relationship with nitrogen fixating bacteria Rhizobim leguminosarum is an important factor used to improve the productivity of legumes, due to the fact that rhizobia can supply plant with the necessary amount of nitrogen. R. leguminosarum strains have shown different activity in fixing nitrogen. Depending on the chosen R. leguminosarum strain, host plant biochemical content can be altered. In this study we focused particularly on the changes in protein content in beans (using two different varieties) and peas (five different varieties) due to the use of several different R. leguminosarum strains (four strains for both beans and peas). Overall, the protein content increase was observed after seed inoculation with R. leguminosarum. Strain and plant cultivar interaction specification was observed. The effect of R. leguminosarum inoculation on the content of protein was dependent on the R. leguminosarum strain used. Plant cultivar also appeared to have a decisive role in protein content formation with the help of R. leguminosaru.

Keywords: legumes, protein content, rhizobia strains, soil

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Authors: Akanksha Agrawal, Richa Rathor, Geetha Suryakumar

Abstract:

Muscle represents about ¾ of the body mass, and a healthy muscular system is required for human performance. A healthy muscular system is dynamically balanced via the catabolic and anabolic process. High altitude associated hypoxia altered this redox balance via producing reactive oxygen and nitrogen species that ultimately modulates protein structure and function, hence, disrupts proteostasis or protein homeostasis. The mechanism by which proteostasis is clinched includes regulated protein translation, protein folding, and protein degradation machinery. Perturbation in any of these mechanisms could increase proteome imbalance in the cellular processes. Altered proteostasis in skeletal muscle is likely to be responsible for contributing muscular atrophy in response to hypoxia. Therefore, we planned to elucidate the mechanism involving altered proteostasis leading to skeletal muscle atrophy under chronic hypobaric hypoxia. Material and Methods-Male Sprague Dawley rats weighing about 200-220 were divided into five groups - Control (Normoxic animals), 1d, 3d, 7d and 14d hypobaric hypoxia exposed animals. The animals were exposed to simulated hypoxia equivalent to 282 torr pressure (equivalent to an altitude of 7620m, 8% oxygen) at 25°C. On completion of chronic hypobaric hypoxia (CHH) exposure, rats were sacrificed, muscle was excised and biochemical, histopathological and protein synthesis signaling were studied. Results-A number of changes were observed with the CHH exposure time period. ROS was increased significantly on 07 and 14 days which were attributed to protein oxidation via damaging muscle protein structure by oxidation of amino acids moiety. The oxidative damage to the protein further enhanced the various protein degradation pathways. Calcium activated cysteine proteases and other intracellular proteases participate in protein turnover in muscles. Therefore, we analysed calpain and 20S proteosome activity which were noticeably increased at CHH exposure as compared to control group representing enhanced muscle protein catabolism. Since inflammatory markers (myokines) affect protein synthesis and triggers degradation machinery. So, we determined inflammatory pathway regulated under hypoxic environment. Other striking finding of the study was upregulation of Akt/PKB translational machinery that was increased on CHH exposure. Akt, p-Akt, p70 S6kinase, and GSK- 3β expression were upregulated till 7d of CHH exposure. Apoptosis related markers, caspase-3, caspase-9 and annexin V was also increased on CHH exposure. Conclusion: The present study provides evidence of disrupted proteostasis under chronic hypobaric hypoxia. A profound loss of muscle mass is accompanied by the muscle damage leading to apoptosis and cell death under CHH. These cellular stress response pathways may play a pivotal role in hypobaric hypoxia induced skeletal muscle atrophy. Further research in these signaling pathways will lead to development of therapeutic interventions for amelioration of hypoxia induced muscle atrophy.

Keywords: Akt/PKB translational machinery, chronic hypobaric hypoxia, muscle atrophy, protein degradation

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Authors: Mona G. Alharbi

Abstract:

A new family of methionine-sulfoxide reductase (Msr) was recently discovered and was named free methionine sulfoxide reductase (fRMsr). This family includes enzymes with a reductase activity toward the free R isomer of a methionine sulfoxide substrate. The fRMsrs have a GAF domain topology, a domain, which was previously identified as having in some cases a cyclic nucleotide phosphodiesterase activity. The classification of fRMsrs as GAF domains revealed a new function can be added to the GAF domain family. Interestingly the four members identified in the fRMsr family share the GAF domain structure and the presence of three conserved cysteines in the active site with free R methionine sulfoxide substrate specificity. This thesis presents the crystal structures of reduced, free Met-SO substrate-bound and MES-bound forms of a new fRMsr from Burkholderia pseudomallei (BPSL2418). BPSL2418 was cloned, overexpressed and purified to enable protein crystallization. The crystallization trials for reduced, Met-SO-bound and MES-bound forms of BPSL2418 were prepared and reasonable crystals of each form were produced. The crystal structures of BPSL2418MES, BPSL2418Met-SO and BPSL2418Reduced were solved at 1.18, 1.4 and 2.0Å, respectively by molecular replacement. The BPSL2418MES crystal belongs to space group P 21 21 21 while BPSL2418Met-SO and BPSL2418Reduced crystals belong to space group P 1 21 1. All three forms share the GAF domain structure of six antiparallel β-strands and four α-helices with connecting loops. The antiparallel β-strands (β1, β2, β5 and β6) are located in the center of the BPSL2418 structure flanked on one side by a three α-helices (α1, α2 and α4) and on the other side by a (loop1, β3, loop2, α3, β4 loop4) unit where loop4 forms a capping flap and covers the active site. The structural comparison of the three forms of BPSL2418 indicates that the catalytically important cysteine is CYS109, where the resolving cysteine is CYS75, which forms a disulfide bond with CYS109. They also suggest that the third conserved cysteine in the active site, CYS85, which is located in α3, is a non-essential cysteine for the catalytic function but it may play a role in the binding of the substrate. The structural comparison of the three forms reveals that conformational changes appear in the active site particularly involving loop4 and CYS109 during catalysis. The 3D structure of BPSL2418 shows strong structure similarity to fRMsrs enzymes, which further suggests that BPSL2418 acts as a free Met-R-SO reductase and shares the catalytic mechanism of fRMsr family.

Keywords: Burkholderia pseudomallei, GAF domain protein, methionine sulfoxide reductase, protein crystallization

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

Abstract:

Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Khaleel Saleh Al-Rababah

Abstract:

Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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Authors: Nishal Parbhoo, John B. Dewar, Samantha Gildenhuys

Abstract:

Rotavirus is the major cause of severe gastroenteritis worldwide in children aged 5 and younger. Death rates are high particularly in developing countries. The mature rotavirus is a non-enveloped triple-layered nucleocapsid containing 11 double-stranded RNA segments. Here a global view on the sequence and structure of the three main capsid proteins, VP7, VP6, and VP2 is taken by generating a consensus sequence for each of these rotavirus proteins, for each species obtained from published data of representative rotavirus genotypes from across the world and across species. The degree of conservation between species was represented on homology models for each of the proteins. VP7 shows the highest level of variation with 14 - 45 amino acids showing conservation of less than 60%. These changes are localized to the outer surface which is exposed to antibodies alluding to a possible mechanism in evading the immune system. The middle layer, VP6 shows lower variability with only 14-32 sites having lower than 70% conservation. The inner structural layer made up of VP2 showed the lowest variability with only 1-16 sites having less than 70% conservation across species. The results correlate with proteins’ multiple structural roles. Although the nucleotide sequences vary due to an error-prone replication and lack of proofreading, the corresponding amino acid sequence of VP2, 6 and 7 remains conserved. Sequence conservation maintained for the virus results in stable protein structures, fit for function. This can be exploited in drug design, molecular studies and biotechnological applications.

Keywords: amino acid sequence conservation, capsid protein, protein structure, vaccine candidate

Procedia PDF Downloads 268