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Proteins hold multispectral patterns of different kinds of physicochemical features of amino acids in their structures, which can help understand proteins’ behavior. Here, we propose a method based on the graph-wavelet transform of signals of features of amino acids in protein residue networks derived from their structures to achieve their abstract numerical representations. Such abstract representations of protein structures hand in hand with amino-acid features can be used for different purposes, such as modelling the biophysical property of proteins. Our method outperformed graph-Fourier and convolutional neural-network-based methods in predicting the biophysical properties of proteins. Even though our method does not predict deleterious mutations, it can summarize the effect of an amino acid based on its location and neighbourhood in protein-structure using graph-wavelet to estimate its influence on the biophysical property of proteins. Such an estimate of the influence of amino-acid has the potential to explain the mechanism of the effect of deleterious non-synonymous mutations. Thus, our approach can reveal patterns of distribution of amino-acid properties in the structure of the protein in the context of a biophysical property for better classification and more insightful understanding.

The stability of proteins is an essential property that has several biological implications. Knowledge about protein stability is important in many ways, ranging from protein purification and structure determination to stability in cells and biotechnological applications. Experimental determination of thermal stabilities has been tedious and available data have been limited. The introduction of limited proteolysis and mass spectrometry approaches has facilitated more extensive cellular protein stability data production. We collected melting temperature information for 34,913 proteins and developed a machine learning predictor, ProTstab2, by utilizing a gradient boosting algorithm after testing seven algorithms. The method performance was assessed on a blind test data set and showed a Pearson correlation coefficient of 0.753 and root mean square error of 7.005. Comparison to previous methods indicated that ProTstab2 had superior performance. The method is fast, so it was applied to predict and compare the stabilities of all proteins in human, mouse, and zebrafish proteomes for which experimental data were not determined. The tool is freely available. [ABSTRACT FROM AUTHOR]

Rice protein has attracted considerable attention recently due to its physiological effects. This study extracted the proteins from paddy rice (PR) and germinated paddy rice (GPR) using three methods i.e., alkaline, sodium dodecyl sulfate (SDS) reagent and enzymatic extractions. The extracted proteins or protein fractions were assessed for their properties using various techniques. Data were analyzed by 2′3 factorial design experiment. It was found that germination and extraction methods significantly affected the concentration of protein fractions when analyzed by Bradford assay. Average protein fraction concentration of the GPR was lower than that of PR. SDS-PAGE patterns of protein fractions obtained from PR and GPR using any extraction method displayed similar protein profiles. Three major protein bands at about 13 kDa (prolamin), 22–23 kDa (basic glutelin) and 37–39 kDa (acidic glutelin) with small amount of 57 kDa proglutelin were observed. For amino acid profile, germination increased the content of most amino acids, resulting in the higher content of amino acids in GPR, excepted for some amino acids. When processed with in vitro digestion, protein fractions from GPR exhibited a higher level of digestibility than those from PR as evidenced by the less intensity of the protein bands obtained from SDS-PAGE. Alkaline and SDS reagent extractions provided more digestible protein fractions than enzymatic extraction. Extraction methods also influenced phase transition of protein fractions as investigated by a DSC. Alkaline extraction resulted in protein fractions with higher phase transition temperature than the other methods. For antioxidant capacity, extraction methods as well as germination significantly affected antioxidant capacity of the protein fractions. Enzymatic extraction provided protein fractions with the best antioxidant capacity.

The combined effect of tumbling marination methods (vacuum continuous tumbling marination, CT; vacuum intermittent tumbling marination, IT) and effective tumbling time (4, 6, 8, and 10 h) on the water status and protein properties of prepared pork chops was investigated. Results showed that regardless of tumbling time, CT method significantly decreased the muscle fiber diameter (MD) and significantly increased the total moisture content, product yield, salt soluble proteins (SSP) solubility, immobilized water component (p

Arabidopsis thaliana is an important model species for studies of plant gene functions. Research on Arabidopsis has resulted in the generation of high-quality genome sequences, annotations and related post-genomic studies. The amount of annotation, such as gene-coding regions and structures, is steadily growing in the field of plant research. In contrast to the genomics resource of animals and microorganisms, there are still some difficulties with characterization of some gene functions in plant genomics studies. The acquisition of information on protein structure can help elucidate the corresponding gene function because proteins encoded in the genome possess highly specific structures and functions. In this study, we calculated multiple physicochemical and secondary structural parameters of protein sequences, including length, hydrophobicity, the amount of secondary structure, the number of intrinsically disordered regions (IDRs) and the predicted presence of transmembrane helices and signal peptides, using a total of 208,333 protein sequences from the genomes of six representative plant species, Arabidopsis thaliana, Glycine max (soybean), Populus trichocarpa (poplar), Oryza sativa (rice), Physcomitrella patens (moss) and Cyanidioschyzon merolae (alga). Using the PASS tool and the Rosetta Stone method, we annotated the presence of novel functional regions in 1,732 protein sequences that included unannotated sequences from the Arabidopsis and rice proteomes. These results were organized into the Plant Protein Annotation Suite database (Plant-PrAS), which can be freely accessed online at http://plant-pras.riken.jp/. [ABSTRACT FROM AUTHOR]