Search

Bicyclic peptides have attracted the interest of pharmaceutical companies because of their remarkable properties, putting them on a new path in medicine. Their conformational rigidity improves proteolytic stability and leads to rapid penetration into tissues via any possible route of administration. Moreover, elimination of renal metabolism is of great importance, for example, for people with a history of liver diseases. In addition, each ring can function independently, making bicyclic peptides extremely versatile molecules for further optimization. In this paper, we compared the potentiometric and spectroscopic properties studied by UV–vis, MCD, and EPR of four synthetic analogues of the bi-cyclic peptide c(PKKHP-c(CFWKTC)-PKKH) (BCL). In particular, we correlated the structural and spectral properties of complexes with coordinating abilities toward Cu(II) ions of MCL1 (Ac-PKKHPc(CFWKTC)PKKH-NH2) that contains the unbinding cycle and N- and C-terminal linear parts with two histidine residues, one per part; two monocyclic ligands containing one histidine residue, both in the N-terminal position, i.e., MCL2 (Ac-PKKHPc(CFWKTC)PKKS-NH2) and in the C-terminal position, i.e., MCL3 (Ac-PKKSPc(CFWKTC)PKKH-NH2), respectively; and the linear structure LNL (Ac-PKKHPSFWKTSPKKH-NH2). Potentiometric results have shown that the bicyclic structure promotes the involvement of the side chain imidazole donors in Cu(II) binding. On the other hand, the results obtained for the mono-cyclic analogues lead to the conclusion that the coordination of the histidine moiety as an anchoring group is promoted by its location in the peptide sequence further from the nonbinding cycle, strongly influencing the involvement of the amide donors in Cu(II) coordination. [ABSTRACT FROM AUTHOR]

• Structure and properties of β-casein mutants in dairy products were summarized. • Impact of A1/A2 β-casein on gastrointestinal health in vivo studies was analyzed. • The detection method of β-casomorhin7 and A1/A2 β-casein was summarized. • Limitations and future directions in this promising field were presented. β-casein is the second most abundant form of casein in milk. Changes in amino acid sequence at specific positions in the primary structure of β-casein in milk will produce gene mutations that affect the physicochemical properties of dairy products and the hydrolysis site of digestive enzymes. The screening method of β-casein allele frequency detection in dairy products also has attracted the extensive attention of scientists and farmers. The A1 and A2 β-casein is the two usual mutation types, distinguished by histidine and proline at position 67 in the peptide chain. This paper summarizes the effects of A1 and A2 β-casein on the physicochemical properties of dairy products and evaluates the effects on human health, and the genotyping methods were also concluded. Impressively, this review presents possible future opportunities and challenges for the promising field of A2 β-casein, providing a valuable reference for the development of the functional dairy market. [ABSTRACT FROM AUTHOR]

As a potential natural active substance, natural biologically active peptides (NBAPs) are recently attracting increasing attention. The traditional proteolysis methods of obtaining effective NBAPs are considerably vexing, especially since multiple proteases can be used, which blocks the exploration of available NBAPs. Although the development of virtual digesting brings some degree of convenience, the activity of the obtained peptides remains unclear, which would still not allow efficient access to the NBAPs. It is necessary to develop an efficient and accurate strategy for acquiring NBAPs. A new in silico scheme named SSA-LSTM-VD, which combines a sparrow search algorithm-long short-term memory (SSA-LSTM) deep learning and virtually digested, was presented to optimize the proteolysis acquisition of NBAPs. Therein, SSA-LSTM reached the highest Efficiency value reached 98.00 % compared to traditional machine learning algorithms, and basic LSTM algorithm. SSA-LSTM was trained to predict the activity of peptides in the proteins virtually digested results, obtain the percentage of target active peptide, and select the appropriate protease for the actual experiment. As an application, SSA-LSTM was employed to predict the percentage of neuroprotective peptides in the virtual digested result of walnut protein, and trypsin was ultimately found to possess the highest value (85.29 %). The walnut protein was digested by trypsin (WPTrH) and the peptide sequence obtained was analyzed closely matches the theoretical neuroprotective peptide. More importantly, the neuroprotective effects of WPTrH had been demonstrated in nerve damage mouse models. The proposed SSA-LSTM-VD in this paper makes the acquisition of NBAPs efficient and accurate. The approach combines deep learning and virtually digested skillfully. Utilizing the SSA-LSTM-VD based strategy holds promise for discovering and developing peptides with neuroprotective properties or other desired biological activities. [Display omitted] • Machine learning and virtual digestion were combined for the first time to enzymatic acquisition of naturally active peptides. • The SSA-LSTM machine learning model exhibited high accuracy performance in identifying neuroprotective peptides. • The neuroprotective efficacy of walnut protein hydrolysate obtained by SSA-LSTM-VD was verified by the mice model. [ABSTRACT FROM AUTHOR]