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      Computational modelling of extrusion process temperatures on the interactions between black soldier fly larvae protein and corn flour starch

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          Abstract

          Insects such as the black soldier fly (BSF) are recently being studied as food sources to address concerns about how to meet the food demand of the growing world population, as conventional production lines for meat proteins are currently unsustainable sources. Studies have been conducted evaluating the use of insect proteins to produce extruded foods such as expanded snacks and meat analogues. However, this field of study is still quite new and not much has been studied beyond digestibility and growth performance. The purpose of this work was to evaluate the compatibility of protein extracted from BSF flour with corn flour starch within an extruded balanced shrimp feed model through molecular dynamics simulations, for which cohesive energy density and solubility parameter (δ) of both components were determined. The calculations’ results for the protein molecule systems yielded an average δ of 14.961 MPa 0.5, while the δ for starch was calculated to be 23.166 MPa 0.5. The range of difference between both δ (10 > δ > 7) suggests that the interaction of the BSF protein with corn starch is of a semi-miscible nature. These results suggest that it is possible to obtain a stable starch-protein mixture through the extrusion process.

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          The I-TASSER Suite: protein structure and function prediction.

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            I-TASSER: a unified platform for automated protein structure and function prediction.

            The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.
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              I-TASSER server for protein 3D structure prediction

              Yang Zhang (2008)
              Background Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions. Results An on-line version of I-TASSER is developed at the KU Center for Bioinformatics which has generated protein structure predictions for thousands of modeling requests from more than 35 countries. A scoring function (C-score) based on the relative clustering structural density and the consensus significance score of multiple threading templates is introduced to estimate the accuracy of the I-TASSER predictions. A large-scale benchmark test demonstrates a strong correlation between the C-score and the TM-score (a structural similarity measurement with values in [0, 1]) of the first models with a correlation coefficient of 0.91. Using a C-score cutoff > -1.5 for the models of correct topology, both false positive and false negative rates are below 0.1. Combining C-score and protein length, the accuracy of the I-TASSER models can be predicted with an average error of 0.08 for TM-score and 2 Å for RMSD. Conclusion The I-TASSER server has been developed to generate automated full-length 3D protein structural predictions where the benchmarked scoring system helps users to obtain quantitative assessments of the I-TASSER models. The output of the I-TASSER server for each query includes up to five full-length models, the confidence score, the estimated TM-score and RMSD, and the standard deviation of the estimations. The I-TASSER server is freely available to the academic community at .
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                Author and article information

                Contributors
                Journal
                Food Chem (Oxf)
                Food Chem (Oxf)
                Food Chemistry: Molecular Sciences
                Elsevier
                2666-5662
                31 March 2024
                30 July 2024
                31 March 2024
                : 8
                : 100202
                Affiliations
                [a ]TecNM/I.T.Durango. Posgrado en Ingeniería Bioquímica Felipe Pescador 1803, Nueva Vizcaya, 34080 Durango, Dgo., Mexico
                [b ]Facultad de Medicina Veterinaria y Zootecnia de la Universidad Juárez del Estado Durango/ Durango - Mezquital Km 11.5, 34307 Durango, Dgo., Mexico
                [c ]Food Science and Technology, Department of Family and Consumer Sciences, New Mexico State University, P.O. Box 30001, Las Cruces, NM 88003-8001, USA
                [d ]Department of Biology, Eastern New Mexico University, 1500 S Ave K Portales, NM 88130, USA
                [e ]Department of Biochemical Conversion, Deutsches Biomasseforschungszentrum gemeinnützige GmbH, Torgauer Straße116, 04347, Leipzig, Germany
                Author notes
                [* ]Corresponding author. damian.reyes@ 123456itdurango.edu.mx
                Article
                S2666-5662(24)00009-1 100202
                10.1016/j.fochms.2024.100202
                10995973
                38586156
                56d5d7c3-0380-450f-9001-61b86918c082
                © 2024 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 15 December 2023
                : 28 March 2024
                : 30 March 2024
                Categories
                Research Article

                protein,starch,extrusion,molecular dynamics simulation
                protein, starch, extrusion, molecular dynamics simulation

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