Nutritional Changes and Early Warning of Moldy Rice under Different Relative Humidity and Storage Temperature

Processed unhusked rice is prone to mildew during storage. In this study, the storage conditions were simulated at temperatures of 20, 30, and 35 °C and a relative humidity of 40%, 60% and 80%, respectively. The water, fatty acid, and total starch content and the peak viscosity, mold colony number, protein secondary structure, and spatial structure of rice were monitored in order to propose the critical point of mildew during storage. In the process of rice from lively to moldy, the water content, fatty acid contents and the peak viscosity were increased. The total starch content decreased and then showed a slow increasing trend, while the microstructure of the powder particles changed from smooth and complete to loosen and hollow. With the increase in storage time, the vibration of the amide Ⅰ band of the rice samples decreased slightly, indicating that the total contents of β-fold, β-turn, α-helix, and random curl of the rice protein also changed. PCA (Principal Component Analysis) analysis showed that rice mildew index was closely related to temperature and humidity during storage. In our investigation, the best and most suitable temperature and relative humidity for rice storge is 20 °C and 40%, respectively. These results suggested that temperature and environmental humidity are vital factors affecting the physicochemical properties and nutrient changes, which provides a theoretical basis for the early warning of rice mildew during storage.

Helical structure motifs made searchable for functional peptide design

The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for Helicobacter pylori. We also show how the database can be used to design a new antimicrobial peptide that shows better Candida albicans clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/.

Prediction of Protein Secondary Structure Based on WS-BiLSTM Model

Protein secondary structure prediction is an important topic in bioinformatics. This paper proposed a novel model named WS-BiLSTM, which combined the wavelet scattering convolutional network and the long-short-term memory network for the first time to predict protein secondary structure. This model captures nonlocal interactions between amino acid sequences and remembers long-range interactions between amino acids. In our WS-BiLSTM model, the wavelet scattering convolutional network is used to extract protein features from the PSSM sliding window; the extracted features are combined with the original PSSM data as the input features of the long-short-term memory network to predict protein secondary structure. It is worth noting that the wavelet scattering convolutional network is asymmetric as a member of the continuous wavelet family. The Q3 accuracy on the test set CASP9, CASP10, CASP11, CASP12, CB513, and PDB25 reached 85.26%, 85.84%, 84.91%, 85.13%, 86.10%, and 85.52%, which were higher 2.15%, 2.16%, 3.5%, 3.19%, 4.22%, and 2.75%, respectively, than using the long-short-term memory network alone. Comparing our results with the state-of-art methods shows that our proposed model achieved better results on the CB513 and CASP12 data sets. The experimental results show that the features extracted from the wavelet scattering convolutional network can effectively improve the accuracy of protein secondary structure prediction.

In Silico Study of Secondary Structure of Hemoglobin Protein

Protein structure prediction is one of the important goals in the area of bioinformatics and biotechnology. Prediction methods include structure prediction of both secondary and tertiary structures of protein. Protein secondary structure prediction infers knowledge related to presence of helixes, sheets and coils in a polypeptide chain whereas protein tertiary structure prediction infers knowledge related to three dimensional structures of proteins. Protein secondary structures represent the possible motifs or regular expressions represented as patterns that are predicted from primary protein sequence in the form of alpha helix, betastr and and coils. The secondary structure prediction is useful as it infers information related to the structure and function of unknown protein sequence. There are various secondary structure prediction methods used to predict about helixes, sheets and coils. Based on these methods there are various prediction tools under study. This study includes prediction of hemoglobin using various tools. The results produced inferred knowledge with reference to percentage of amino acids participating to produce helices, sheets and coils. PHD and DSC produced the best of the results out of all the tools used.

Different Thermal Treatment Methods and TGase Addition Affect Gel Quality and Flavour Characteristics of Decapterus maruadsi Surimi Products

Decapterus maruadsi surimi products were prepared using the thermal treatment methods of boiling (BOI), steaming (STE), back-pressure sterilization (BAC), roasting (ROA), microwaving (MIC), and frying (FRI), respectively. The effect of glutamine transaminase (TGase) addition was also investigated. The moisture distribution, water retention, microstructure, color, fracture constant, protein secondary structure, chemical forces, and flavor components of each sample were determined. The differences in gel and favor characteristics between D. maruadsi surimi products caused by thermal treatment methods were analyzed. The results showed that BOI, STE, and FRI had the largest protein secondary structure transitions and formed dense gel structures with high fracture constant. The kinds of flavour components in BOI and STE were completer and more balanced. The high temperature treatment available at BAC and FRI (110 °C and 150 °C) accelerated the chemical reaction involved in flavor formation, which highlighted the flavor profiles dominated by furans or esters. The open thermal treatment environments of ROA, MIC, and FRI gave them a low moisture content and water loss. This allowed the MIC to underheat during the heat treatment, which formed a loose gel structure with a low fracture coefficient. The addition of TGase enhances the gel quality, most noticeably in the ROA. The aldehyde content of the FRI was enhanced in the flavor characteristic. The effect of adding TGase to enhance the quality of the gel is most evident in ROA. It also substantially increased the content of aldehydes in FRI. In conclusion, different heat treatments could change the gel characteristics of surimi products and provide different flavor profiles. The gel quality of BOI and STE was consistently better in all aspects.

Influence of Multifrequency Ultrasound-Assisted Freezing on the Flavour Attributes and Myofibrillar Protein Characteristics of Cultured Large Yellow Croaker (Larimichthys crocea)

The influence of multifrequency ultrasound-assisted freezing (UAF) as compared with single- and dual-UAF on the flavour, microstructure, and myofibrillar proteins (MPs) of cultured large yellow croaker was investigated to improve food quality in a sustainable way and address the major global challenges concerning food and nutrition security in the (near) future. Multifrequency UAF-treated samples had lower total volatile basic nitrogen values during freezing than single- and dual-UAF-treated samples. Thirty-six volatile compounds were identified by solid-phase microextraction (SPME) coupled to gas chromatography–mass spectrometry (GC-MS) during freezing, and the multifrequency UAF-treated samples showed significant decreases in the relative contents of fishy flavoured compounds, including 1-penten-3-ol and 1-octen-3-ol. In addition, multifrequency UAF treatment better maintained a well-organised protein secondary structure by maintaining higher α-helical and β-sheet contents and stabilising the tertiary structure. Scanning electron microscopy images indicated that the ice crystals developed by the multifrequency UAF were fine and uniformly distributed, resulting in less damage to the frozen large yellow croaker samples. Therefore, multifrequency UAF improved the flavour attributes and MP characteristics of the large yellow croaker samples. Overall, multifrequency UAF can serve as an efficient way for improving food quality and nutritional profile in a sustainable way.

Unravelling the Interaction of Piperlongumine with the Nucleotide-Binding Domain of HSP70: A Spectroscopic and In Silico Study

Piperlongumine (PPL) is an alkaloid extracted from several pepper species that exhibits anti-inflammatory and anti-carcinogenic properties. Nevertheless, the molecular mode of action of PPL that confers such powerful pharmacological properties remains unknown. From this perspective, spectroscopic methods aided by computational modeling were employed to characterize the interaction between PPL and nucleotide-binding domain of heat shock protein 70 (NBD/HSP70), which is involved in the pathogenesis of several diseases. Steady-state fluorescence spectroscopy along with time-resolved fluorescence revealed the complex formation based on a static quenching mechanism. Van’t Hoff analyses showed that the binding of PPL toward NBD is driven by equivalent contributions of entropic and enthalpic factors. Furthermore, IDF and Scatchard methods applied to fluorescence intensities determined two cooperative binding sites with Kb of (6.3 ± 0.2) × 104 M−1. Circular dichroism determined the thermal stability of the NBD domain and showed that PPL caused minor changes in the protein secondary structure. Computational simulations elucidated the microenvironment of these interactions, showing that the binding sites are composed mainly of polar amino acids and the predominant interaction of PPL with NBD is Van der Waals in nature.