• Animal Bioscience
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• v.36 no.8
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• pp.1190-1198
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• 2023

Objective: To our knowledge, there are few studies on the correlation between internal structure of fermented products and nutrient delivery from by-products from coffee processing in the ruminant system. The objective of this project was to use advanced mid-infrared vibrational spectroscopic technique (ATR-FT/IR) to reveal interactive correlation between protein internal structure and ruminant-relevant protein and energy metabolic profiles of by-products from coffee processing affected by added-microorganism fermentation duration. Methods: The by-products from coffee processing were fermented using commercial fermentation product, called Saus Burger Pakan, consisting of various microorganisms: cellulolytic, lactic acid, amylolytic, proteolytic, and xylanolytic microbes, for 0, 7, 14, 21, and 28 days. Protein chemical profiles, Cornell Net Carbohydrate and Protein System crude protein and CHO subfractions, and ruminal degradation and intestinal digestion of protein were evaluated. The attenuated total reflectance-Ft/IR (ATR-FTIR) spectroscopy was used to study protein structural features of spectra that were affected by added microorganism fermentation duration. The molecular spectral analyses were carried using OMNIC software. Molecular spectral analysis parameters in fermented and non-fermented by-products from coffee processing included: Amide I area (AIA), Amide II (AIIA) area, Amide I heigh (AIH), Amide II height (AIIH), α-helix height (αH), β-sheet height (βH), AIA to AIIA ratio, AIH to AIIH ratio, and αH to βH ratio. The relationship between protein structure spectral profiles of by-products from coffee processing and protein related metabolic features in ruminant were also investigated. Results: Fermentation decreased rumen degradable protein and increased rumen undegradable protein of by-products from coffee processing (p<0.05), indicating more protein entering from rumen to the small intestine for animal use. The fermentation duration significantly impacted (p<0.05) protein structure spectral features. Fermentation tended to increase (p<0.10) AIA and AIH as well as β-sheet height which all are significantly related to the protein level. Conclusion: Protein structure spectral profiles of by-product form coffee processing could be utilized as potential evaluators to estimate protein related chemical profile and protein metabolic characteristics in ruminant system.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.359-366
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• 2009

Analysis of 3-dimensional (3D) protein structure plays an important role of structural bioinformatics. The protein structure alignment is the main subjects of the structural bioinformatics and the most fundamental problem. Protein Structures are flexible and undergo structural changes as part of their function, and most existing protein structure comparison methods treat them as rigid bodies, which may lead to incorrect alignment. We present a new method that carries out the flexible structure alignment by means of finding SSPs(Similar Substructure Pairs) and flexible points of the protein. In order to find SSPs, we encode the coordinates of atoms in the backbone of protein into RDA(Relative Direction Angle) using local similarity of protein structure. We connect the SSPs with Floyd-Warshall algorithm and make compatible SSPs. We compare the two compatible SSPs and find optimal flexible point in the protein. On our well defined performance experiment, 68 benchmark data set is used and our method is better than three widely used methods (DALI, CE, FATCAT) in terms of alignment accuracy.

• Genomics & Informatics
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• v.9 no.2
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• pp.74-78
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• 2011

Numerous restraints and simplifications have been developed for methods that anticipate protein structure to reduce the colossal magnitude of possible conformational states. In this study, we investigated if globularity is a general characteristic of proteins and whether they can be applied as a valid constraint in protein structure simulations with approximated measurements (Gb-index). Unexpectedly, most of the proteins showed strong structural globularity (i.e., mode of approximately 76% similarity to the perfect globe) with only a few percent of proteins being outliers. Small proteins tended to be significantly non-globular ($R^2$=0.79) and the minimum Gb-index showed a logarithmic increase with the increase in protein size ($R^2$=0.62), strongly implying that the non-globular characteristics might be more acceptable for smaller proteins than larger ones. The strong perfect globe-like character and the relationship between small size and the loss of globular structure of a protein may imply that living organisms have mechanisms to aid folding into the globular structure to reduce irreversible aggregation. This also implies the possible mechanisms of diseases caused by protein aggregation, including some forms of trinucleotide repeat expansion-mediated diseases.

• Toxicological Research
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• v.29 no.3
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• pp.149-155
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• 2013

G protein-coupled receptors (GPCRs) are membrane receptors; approximately 40% of drugs on the market target GPCRs. A precise understanding of the activation mechanism of GPCRs would facilitate the development of more effective and less toxic drugs. Heterotrimeric G proteins are important molecular switches in GPCR-mediated signal transduction. An agonist-activated receptor interacts with specific sites on G proteins and promotes the release of GDP from the $G{\alpha}$ subunit. Because of the important biological role of the GPCR-G protein coupling, conformational changes in the G protein upon receptor coupling have been of great interest. One of the most important questions was the interface between the GPCR and G proteins and the structural mechanism of GPCR-induced G protein activation. A number of biochemical and biophysical studies have been performed since the late 80s to address these questions; there was a significant breakthrough in 2011 when the crystal structure of a GPCR-G protein complex was solved. This review discusses the structural aspects of GPCR-G protein coupling by comparing the results of previous biochemical and biophysical studies to the GPCR-G protein crystal structure.

• BMB Reports
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• v.33 no.2
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• pp.133-137
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• 2000

To elucidate the effect of oxygen radicals on the molecular properties of proteins, the secondary and tertiary structure and molecular weight size of BSA and ${\beta}$-lactoglobulin were examined after irradiation of proteins at various doses. Gamma-irradiation of protein solutions caused the disruption of the ordered structure of protein molecules as well as degradation, cross-linking, and aggregation of the polypeptide chains. As a model system, BSA and ${\beta}$-lactoglobulin were used as a typical ${\alpha}$-helical and a ${\beta}$-sheet structure protein, respectively. A circular dichroism study showed that the increase of radiation decreased the ordered structure of proteins with a concurrent increase of aperiodic structure content. Fluorescence spectroscopy indicated that irradiation quenched the emission intensity excited at 280 nm. SDS-PAGE and a gel permeation chromatography study indicated that radiation caused initial fragmentation of proteins resulting in a subsequent aggregation due to cross-linking of protein molecules.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.728-733
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• 2018

Deep learning has been actively studied for predicting protein secondary structure based only on the sequence information of the amino acids constituting the protein. In this paper, we compared the performances of the convolutional neural networks of various structures to predict the protein secondary structure. To investigate the optimal depth of the layer of neural network for the prediction of protein secondary structure, the performance according to the number of layers was investigated. We also applied the structure of GoogLeNet and ResNet which constitute building blocks of many image classification methods. These methods extract various features from input data, and smooth the gradient transmission in the learning process even using the deep layer. These architectures of convolutional neural networks were modified to suit the characteristics of protein data to improve performance.

• Molecules and Cells
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• v.20 no.3
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• pp.442-445
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• 2005

HP0894 (SwissProt/TrEMBL ID O25554) is an 88-residue conserved hypothetical protein from Helicobacter pylori strain 26695 with a calculated pI of 8.5 and a molecular weight of 10.38 kDa. Proteins with sequence similarity to HP0894 exist in Vibrio choierae, Enterococcus faecalis, Campylobacter jejuni, Streptococcus pneumoniae, Haemophilus influenzae, Escherichia coli O157, etc. Here we report the sequence-specific backbone resonance assignments of HP0894. About 97.5% (418/429) of the HN, N, CO, $C{\alpha}$, $C{\beta}$ resonances of the 88 residues of HP0894 were assigned. On the basis of these assignments, three helical regions and four strand regions were identified using the CSI program. This study is a prerequisite for calculating the solution structure of HP0894, and studying its interaction with its substrates, if any, and/or with other proteins.

• Bulletin of the Korean Chemical Society
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• v.29 no.11
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• pp.2172-2182
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• 2008

• International Journal of Contents
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• v.9 no.4
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• pp.11-15
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• 2013

"Protein Folding Problem" is considered to be one of the "Great Challenges of Computer Science" and prediction of disordered protein is an important part of the protein folding problem. Machine learning models can predict the disordered structure of protein based on its characteristic of "learning from examples". Among many machine learning models, we investigate the possibility of multilayer perceptron (MLP) as the predictor of protein disorder. The investigation includes a single hidden layer MLP, multi hidden layer MLP and the hierarchical structure of MLP. Also, the target node cost function which deals with imbalanced data is used as training criteria of MLPs. Based on the investigation results, we insist that MLP should have deep architectures for performance improvement of protein disorder prediction.

• Journal of the Korean Magnetic Resonance Society
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• v.19 no.3
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• pp.112-118
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• 2015

Hsp31 protein is one of the members of DJ-1 superfamily proteins and has a dimeric structure of which molecular weight (MW) is 62 kDa. The mutation of DJ-1 is closely related to early onset of Parkinson's disease. Hsp31 displays $Zn^{+2}$-binding activity and was first reported to be a holding chaperone in E. coli. Its additional glyoxalase III active has recently been characterized. Moreover, an incubation at $60^{\circ}C$ induces Hsp31 protein to form a high MW oligomer (HMW) in vitro, which accomplishes an elevated holding chaperone activity. The NMR technique is elegant method to probe any local or global structural change of a protein in responses to environmental stresses (heat, pH, and metal). Although the presence of the backbone chemical shifts (bbCSs) is a prerequisite for detailed NMR analyses of the structural changes, general HSQC-based triple resonance experiments could not be used for 62 kDa Hsp31 protein. Here, we prepared the per-deuterated Hsp31 and performed the TROSY-based triple resonance experiments for the bbCSs assignment. Here, detailed processes of per-deuteration and the NMR experiments are described for other similar NMR approaches.