A protein's properties are influenced by both its amino-acid sequence and its three-dimensional conformation. Ascertaining a protein's sequence is relatively easy using modern techniques, but determining its conformation requires much more expensive and time-consuming techniques. Consequently, it would be useful to identify a method that can accurately predict a protein's secondary-structure conformation using only the protein's sequence data. This problem is not trivial, however, because identical amino-acid subsequences in different contexts sometimes have disparate secondary structures, while highly dissimilar amino-acid subsequences sometimes have identical secondary structures. We propose (1) to develop a set of metrics that facilitates better comparisons between dissimilar subsequences and (2) to design a custom set of inputs for machine-learning models that can harness contextual dependence information between the secondary structures of successive amino acids in order to achieve better secondary-structure prediction accuracy.

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Channel catfish raising is an important aquaculture in the United States. Mississippi ranks No.1 in catfish production for continuous 4 years. However, catfish fillet processing generates huge amount of by-products, including heads, bone frames, visceras and skins, which contain significant amount of proteins. Removing and utilization of proteins from the by-product would add value to the catfish industry. Collagen was extracted from catfish skin by: (1) acid extraction; (2) homogenization-aided; and (3) pepsin-aided extraction methods. Kinetic analysis of the extraction was performed. SDS-PAGE was performed to analysis the composition of proteins in collagens extracted under different conditions. Collages extracted by three methods was characterized by solubility test, zeta potential, circular dichroism and gel strength. Protein recovery rate from minced skin extracted with pH 2.4 HCl containing 23.6 KU/g pepsin was the highest (64.19%). Papain, ficin, bromelain, neutrase, alcalase, protamex, novo-pro D and thermolysin were used for the hydrolysis of the mixture of heads and frames. Proteolytic activities of these proteases were examined using AzocollTM as a standard substrate. Degree of hydrolysis (DH) of hydrolysates and enzyme reaction kinetics were investigated. Results indicated that thermolysin had the highest activity (82.9×107 AzU/g) at 50 °C when using AzocollTM as the substrate. Ficin (80 AzU/g) was the most efficient in hydrolyzing the proteins in the ground catfish by-product (DH reaching 71.88%) in 120 min at 30°C among all the enzymes. Thermolysin could be used for industries to hydrolyze protein by-products in terms of hydrolysis efficiency and economy. The hydrolysis curves fit the Peleg model very well, all with R2 higher than 0.91. Myofibrillar proteins were extracted from the mixture of heads and frames with different pH conditions, and made into protein gels. Transglutaminase (TGase) was incorporated to improve the gel structure. Solubility and secondary structures of extracted myofibrillar proteins were studied. Gelling properties of the protein sol were studied by dynamic rheological measurement. Physicochemical, textural and thermal properties of protein gels treated with TGase were investigated. Protein pattern changes of TGase treated protein gel was studied by SDS-PAGE. Results indicated that alpha-helicity of myofibrillar proteins decreased with extraction pH over 9. Storage modulus (G’) of protein sol decreased as the increase of extraction pH. Rheological measurement of TGase treated protein sol showed that excessive TGase could weaken the gel structure. This study provides systematic information for the catfish fillet processing industry to utilize the by-products.

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