Correlation Between the Water Solubility and Secondary Structure of Tilapia-Soybean Protein Co-Precipitates

Tan, Li; Hong, Pengzhi; Yang, Ping; Zhou, Chunxia; Xiao, Dinghao; Zhong, Tanjun

doi:10.3390/molecules24234337

Cited by 38 publications

(24 citation statements)

References 52 publications

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“…Also, Tan et al identified the significant relationship between protein solubility and ordered secondary structure content such as helix and beta sheets (Tan et al 2019). They found large helix and beta sheet content within the most soluble proteins (Tan et al 2019). Thus, our results, which suggest that ordered secondary structures such as helix and beta sheets, as well as a larger fraction of solvent exposed residues with higher relative solvent accessibility cutoffs, contribute to protein solubility, correlate well with experimental findings.…”

Section: Effect Of Additional Biological Features On Dsressol Performancesupporting

confidence: 88%

“…identified the significant relationship between protein solubility and ordered secondary structure content such as helix and beta sheets [49]. They found large helix and beta sheet content within the most soluble proteins [49].…”

Section: Effect Of Additional Biological Features On Dsressol Performancementioning

confidence: 98%

“…They proposed that soluble proteins have larger negativelycharged surface area, and thus amenable to bind water (Kramer et al 2012). Also, Tan et al identified the significant relationship between protein solubility and ordered secondary structure content such as helix and beta sheets (Tan et al 2019). They found large helix and beta sheet content within the most soluble proteins (Tan et al 2019).…”

Section: Effect Of Additional Biological Features On Dsressol Performancementioning

confidence: 99%

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DSResSol: A sequence-based solubility predictor created with dilated squeeze excitation residual networks

Madani

Lin

Tarakanova

2021

Preprint

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Protein solubility is an important thermodynamic parameter critical for the characterization of a protein's function, and a key determinant for the production yield of a protein in both the research setting and within industrial applications. Thus, a highly accurate in silico bioinformatics tool for predicting protein solubility from protein sequence is sought. In this study, we developed a deep learning sequence-based solubility predictor, DSResSol, that takes advantage of the integration of squeeze excitation residual networks with dilated convolutional neural networks. The model captures the frequently occurring amino acid k-mers and their local and global interactions, and highlights the importance of identifying long-range interaction information between amino acid k-mers to achieve higher performance in comparison to existing deep learning-based models. DSResSol uses protein sequence as input, outperforming all available sequence-based solubility predictors by at least 5 percent in accuracy when the performance is evaluated by two different independent test sets. Compared to existing predictors, DSResSol not only reduces prediction bias for insoluble proteins but also predicts soluble proteins within the test sets with an accuracy that is at least 13 percent higher. We derive the key amino acids, dipeptides, and tripeptides contributing to protein solubility, identifying glutamic acid and serine as critical amino acids for protein solubility prediction. Overall, DSResSol can be used for fast, reliable, and inexpensive prediction of a protein's solubility to guide experimental design.

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Section: Effect Of Additional Biological Features On Dsressol Performancesupporting

confidence: 88%

Section: Effect Of Additional Biological Features On Dsressol Performancementioning

confidence: 98%

Section: Effect Of Additional Biological Features On Dsressol Performancementioning

confidence: 99%

See 1 more Smart Citation

DSResSol: A sequence-based solubility predictor created with dilated squeeze excitation residual networks

Madani

Lin

Tarakanova

2021

Preprint

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“…It can be seen that the main components of serum are protein, lipid and nucleic acids. The amide I protein (1700-1600cm −1 ) band mainly originated from the α-helix structure at 1646cm -1 ( 28 ). The amide II protein (1560-1500cm −1 ) band mainly originated from the N-H functional group at 1542cm -1 ( 29 ).…”

Section: Resultsmentioning

confidence: 99%

Diagnosis of Lung Cancer by ATR-FTIR Spectroscopy and Chemometrics

Yang

Qian

et al. 2021

Front. Oncol.

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Lung cancer is the leading cause of cancer-related death in the world. Early diagnosis has great significance for the survival of patients with lung cancer. In this paper, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics was used to study the serum samples from patients with lung cancer and healthy people. The results of spectral band area comparison showed that the concentrations of protein, lipid and nucleic acids molecules in serum of patients with lung cancer were increased compared with those in healthy people. The original spectra were preprocessed to improve the accuracy of principal component regression (PCR) and partial least squares-discriminant analysis (PLS-DA) models. PLS-DA results for first derivative spectral data in nucleic acids (1250-1000cm-1) band showed 80% sensitivity, 91.89% specificity and 87.10% accuracy with high Rc2 of 0.8949 and Rv2 of 0.8153, low RMSEC of 0.3136 and RMSEV of 0.4180. It is shown that ATR-FTIR spectroscopy combined with chemometrics might be developed as a simple method for clinical screening and diagnosis of lung cancer.

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“…The WSI of various processed ingredients was highest among the high protein ingredients like whey protein (87.62±0.01%) and skimmed milk powder (83.00±0.20%) followed by popped amaranth flour (48.62±0.01%), malted green gram (39.38±0.60%) while least per cent water solubility was observed in flaxseed (23.66± 0.77%). This was because the solubility in water is contributed by protein structure in protein rich product [30]. Developed enteral formulae were observed to have 62.66±0.20 per cent, 51.00±0.12 per cent and 49.66±0.23 per cent in HPEF, BEF and HEEF respectively.…”

Section: Respectivelymentioning

confidence: 99%

Evaluation of Functional Characteristics and Reconstitution Behavior of Formulated Ready to Reconstitute Enteral Formula for Nutrition Therapy

Bordoloi

Bhattacharyya

Gogoi

et al. 2020

IRJPAC

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Aims: The present investigation was undertaken to evaluate the functional properties and reconstitution behavior of enteral formulae i.e. Balanced Enteral Formula, High Protein Enteral Formula and High Energy Enteral Formula formulated using locally available natural ingredients. Place and Duration of Study: The study was conducted in the Department of Food Science and Nutrition, College of Community Science, Assam Agricultural University during the period of August 2017 to January 2018. Methodology: Three enteral formulae namely Balanced Enteral Formula, High Protein Enteral Formula and High Energy Enteral Formula were formulated using naturally available low cost ingredients. Standard protocols were followed to evaluate the quality of ingredients used and formulated enteral formulae. Results: Both ingredients and enteral formulae had good functional properties with bulk density, tapped density, particle density, porosity, cohesiveness, flowability, water absorption index and water solubility index ranging from 0.33 to 0.50 g/ml, 0.38 to 0.56 g/ml, 0.59 to 1.25 g/ml, 35.00 to 60.00per cent, 0.33 to 1.18, 0.00 to 17.77 per cent, 1.23 to 7.59 g/g and 23.66 to 87.62 per cent soluble solids respectively for the ingredients used and 0.44 to 0.47 g/ml; 0.50 to 0.53 g/ml; 0.89 to 0.90 g/ml; 41.00 to 44.44 per cent; 1.12 to 1.14; 11.30 to 12.00 per cent; 3.39 to 4.59 g/g and 42.66 to 51.00 per cent respectively for the formulated enteral formulae. Color analysis of the developed formulae using Hunter Lab showed desirable results with L*, a* and b* value in the range of 82.43 to 87.10; 1.35 to 2.38 and 13.75 to 13.95 respectively. The reconstitution of formulated enteral formulae with warm water revealed a reconstitution time varying from 5 to 6 minutes. Further the reconstituted formula feed on passage through Ryles tube showed superior flow rate in formulae prepared with 20 per cent solid concentration (W/V). Conclusion: The developed enteral formulae had excellent functional characteristics and reconstitution behavior indicating quality product suitable for enteral feeding.

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Correlation Between the Water Solubility and Secondary Structure of Tilapia-Soybean Protein Co-Precipitates

Cited by 38 publications

References 52 publications

DSResSol: A sequence-based solubility predictor created with dilated squeeze excitation residual networks

DSResSol: A sequence-based solubility predictor created with dilated squeeze excitation residual networks

Diagnosis of Lung Cancer by ATR-FTIR Spectroscopy and Chemometrics

Evaluation of Functional Characteristics and Reconstitution Behavior of Formulated Ready to Reconstitute Enteral Formula for Nutrition Therapy

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