Research updates and progress on nutritional significance of the amides I and II, alpha-helix and beta-sheet ratios, microbial protein synthesis, and steam pressure toasting condition with globar and synchrotron molecular microspectroscopic techniques with chemometrics.

This article aims to review research updates and progress on the nutritional significance of the amides I and II, the alpha-helix and beta-sheet ratios, the microbial protein synthesis, and the steam pressure toasting condition in food and feed with globar and synchrotron molecular microspectroscopic techniques plus chemometrics (both univariate and multivariate techniques). The review focused on (I) impact of the amides I and II, and the alpha-helix and beta-sheet-structure ratios in food and feeds; (II) Current research progress and update in synchrotron technique and application in feed and food molecular structure studies that are associated with nutrition delivery; (III) Impact of thermal processing- steam pressure toasting condition on feed and food; (IV). Impact of the microbial protein synthesis and methodology on feed and food; and (V). Impact on performance and production of ruminants with Faba beans.

Ascorbic acid inhibits human insulin aggregation and protects against amyloid induced cytotoxicity.

Protein aggregation into oligomers and fibrils are associated with many human pathophysiologies. Compounds that modulate protein aggregation and interact with preformed fibrils and convert them to less toxic species, expect to serve as promising drug candidates and aid to the drug development efforts against aggregation diseases. In present study, the kinetics of amyloid fibril formation by human insulin (HI) and the anti-amyloidogenic activity of ascorbic acid (AA) were investigated by employing various spectroscopic, imaging and computational approaches. We demonstrate that ascorbic acid significantly inhibits the fibrillation of HI in a dose-dependent manner. Interestingly ascorbic acid destabilise the preformed amyloid fibrils and protects human neuroblastoma cell line (SH- SY5Y) against amyloid induced cytotoxicity. The present data signifies the role of ascorbic acid that can serve as potential molecule in preventing human insulin aggregation and associated pathophysiologies.

A New Caged-Glutamine Derivative as a Tool To Control the Assembly of Glutamine-Containing Amyloidogenic Peptides.

We present the design, synthesis, and characterization of a novel photocaged glutamine derivative (modified on the side chain of glutamine), and describe its use in enhancing peptide stability and solubility. Our results demonstrate that this approach can be used to develop molecular switches to control the folding and ß-sheet formation of amyloidogenic peptides.

Rational design of structure-based vaccines targeting misfolded alpha-synuclein conformers of Parkinson's disease and related disorders.

Synucleinopathies, including Parkinson's disease (PD), multiple system atrophy (MSA), and dementia with Lewy bodies (DLB), are neurodegenerative disorders caused by the accumulation of misfolded alpha-synuclein protein. Developing effective vaccines against synucleinopathies is challenging due to the difficulty of stimulating an immune-specific response against alpha-synuclein without causing harmful autoimmune reactions, selectively targeting only pathological forms of alpha-synuclein. Previous attempts using linear peptides and epitopes without control of the antigen structure failed in clinical trials. The immune system was unable to distinguish between native alpha-synuclein and its amyloid form. The prion domain of the fungal HET-s protein was selected as a scaffold to introduce select epitopes from the surface of alpha-synuclein fibrils. Four vaccine candidates were generated by introducing specific amino acid substitutions onto the surface of the scaffold protein. The approach successfully mimicked the stacking of the parallel in-register beta-sheet structure seen in alpha-synuclein fibrils. All vaccine candidates induced substantial levels of IgG antibodies that recognized pathological alpha-synuclein fibrils derived from a synucleinopathy mouse model. Furthermore, the antisera recognized pathological alpha-synuclein aggregates in brain lysates from patients who died from DLB, MSA, or PD, but did not recognize linear alpha-synuclein peptides. Our approach, based on the rational design of vaccines using the structure of alpha-synuclein amyloid fibrils and strict control over the exposed antigen structure used for immunization, as well as the ability to mimic aggregated alpha-synuclein, provides a promising avenue toward developing effective vaccines against alpha-synuclein fibrils.

BetaDL: A protein beta-sheet predictor utilizing a deep learning model and independent set solution.

The sequence-based prediction of beta-residue contacts and beta-sheet structures contain key information for protein structure prediction. However, the determination of beta-sheet structures poses numerous challenges due to long-range beta-residue interactions and the huge number of possible beta-sheet structures. Recently gaining attention has been the prediction of residue contacts based on deep learning models whose results have led to improvement in protein structure prediction. In addition, to reduce the computational complexity of determining beta-sheet structures, it has been suggested that this problem be transformed into graph-based solutions. Consequently, the current work proposes BetaDL, a combination of a deep learning and a graph-based beta-sheet structure predictor. BetaDL adopts deep learning models to capture beta-residue contacts and improve beta-sheet structure predictions. In addition, a graph-based approach is presented to model the beta-sheets conformational space and a new score function is introduced to evaluate beta-sheets. Furthermore, the present study demonstrates that the beta-sheet structure can be predicted within an acceptable computational time by the utilization of a heuristic maximum weight independent set solution. When compared to state-of-the-art methods, experimental results from BetaSheet916 and BetaSheet1452 datasets indicate that BetaDL improves the accuracy of beta-residue contact and beta-sheet structure prediction. Using BetaDL, beta-sheet structures are predicted with a 4% and 6% improvement in the F1-score at the residue and strand levels, respectively. BetaDL's source code and data are available at http://kerg.um.ac.ir/index.php/datasets/#BetaDL.