Machine Learning-Based Amino Acid Substitution of Short Peptides: Acquisition of Peptides with Enhanced Inhibitory Activities against α-Amylase and α-Glucosidase

Data-mining unveils structure-property-activity correlation of viral infectivity enhancing self-assembling peptides

Gene therapy via retroviral vectors holds great promise for treating a variety of serious diseases. It requires the use of additives to boost infectivity. Amyloid-like peptide nanofibers (PNFs) were shown to efficiently enhance retroviral gene transfer. However, the underlying mode of action of these peptides remains largely unknown. Data-mining is an efficient method to systematically study structure-function relationship and unveil patterns in a database. This data-mining study elucidates the multi-scale structure-property-activity relationship of transduction enhancing peptides for retroviral gene transfer. In contrast to previous reports, we find that not the amyloid fibrils themselves, but rather µm-sized β-sheet rich aggregates enhance infectivity. Specifically, microscopic aggregation of β-sheet rich amyloid structures with a hydrophobic surface pattern and positive surface charge are identified as key material properties. We validate the reliability of the amphiphilic sequence pattern and the general applicability of the key properties by rationally creating new active sequences and identifying short amyloidal peptides from various pathogenic and functional origin. Data-mining-even for small datasets-enables the development of new efficient retroviral transduction enhancers and provides important insights into the diverse bioactivity of the functional material class of amyloids.

Application of machine learning on understanding biomolecule interactions in cellular machinery

Machine learning (ML) applications have become ubiquitous in all fields of research including protein science and engineering. Apart from protein structure and mutation prediction, scientists are focusing on knowledge gaps with respect to the molecular mechanisms involved in protein binding and interactions with other components in the experimental setups or the human body. Researchers are working on several wet-lab techniques and generating data for a better understanding of concepts and mechanics involved. The information like biomolecular structure, binding affinities, structure fluctuations and movements are enormous which can be handled and analyzed by ML. Therefore, this review highlights the significance of ML in understanding the biomolecular interactions while assisting in various fields of research such as drug discovery, nanomedicine, nanotoxicity and material science. Hence, the way ahead would be to force hand-in hand of laboratory work and computational techniques.

Screening of anti-atrophic peptides by using photo-cleavable peptide array and 96-well scale contractile human skeletal muscle atrophy models

Skeletal muscle atrophy is characterized by decreases in protein content, myofiber diameter, and contractile force generation. As muscle atrophy worsens the quality of life, the development of anti-atrophic substances is desirable. In this study, we aimed to demonstrate a screening process for anti-atrophic peptides using photo-cleavable peptide array technology and human contractile atrophic muscle models. We developed a 96-well system, and established a screening process with less variability. Dexamethasone-induced human atrophic tissue was constructed on the system. Eight peptides were selected from the literature and used for the screening of peptides for preventing the decrease of the contractile forces of tissues. The peptide QIGFIW, which showed preventive activity, was selected as the seed sequence. As a result of amino acid substitution, we obtained QIGFIQ as a peptide with higher anti-atrophic activity. These results indicate that the combinatorial use of the photo-cleavable peptide array technology and 96-well screening system could comprise a powerful approach to obtaining anti-atrophic peptides, and suggest that the 96-well screening system and atrophic model represent a practical and powerful tool for the development of drugs/functional food ingredients. This article is protected by copyright. All rights reserved.

Research on Virtual Human Motion Control Based on Computer-Assisted Multimedia Simulation

In order to reproduce realistic human motion in a virtual environment, a study of virtual human motion control based on computer-aided ergonomics simulation is proposed. First, we establish the required human body, workpiece, and production line simulation environment, and on this basis, we use OWAS, BSHA, and other analysis tools to carry out ergonomic simulation of virtual human motion simulation research, seek solutions to man-machine problems, and provide a new, efficient, and quantitative evaluation method for production line planning. The simulation results show that during the operation of virtual human 1, the ratio of the actual load on the left and right hands to the ultimate load has reached up to 70%. Therefore, it is necessary to revise the production line plan, and through analysis, it is concluded that the reason for the bad posture is due to the low height of the storage point and the machine tool. We believe that with continuous development, ProcessSimulate and ProcessDesigner will play a greater role in enterprise digitization.

Selective concentration of antimicrobial peptides to heat-treated porous silica gel using adsorption/desorption

Heat-treated porous silica gel (HT silica gel) previously developed by our group has selectively adsorbed cationic peptides at a pH of 7. Therefore, we focused on the use of antimicrobial peptides (AMPs) as bioactive peptides (BPs). First, 32 AMPs and 32 randomly designed peptides were generated using Fmoc solid synthesis, and their adsorption ratio to HT-silica gel was investigated. Thirty two AMPs showed a relatively higher adsorption ratio of 58.8% compared to that of randomly designed peptides, which was 35.3%. Desorption conditions were investigated using Amyl-1-18 antimicrobial peptides. Next, pepsin hydrolysate from rice endosperm protein (REP) powder was prepared by ourselves. The REP hydrolysate containing dry matter (7.5 mg) was applied to the adsorption/desorption (AD) procedure using HT silica gel to obtain 1.6 mg of AD hydrolysate. When the two hydrolysates were subjected to mass spectrometry, 305 concentrated peptides were obtained. In total, 26 peptides with high content and high enrichment ratios were listed and synthesized. When the antimicrobial activity of these 26 peptides was evaluated using Cutibacterium acnes, five peptides consisting of 12-27 amino acids were identified as novel AMPs. Two of these peptides, which were derived from rice glutelin, showed antimicrobial activity against all four microbes, including Porphyromonas gingivalis, Escherichia coli, and Streptococcus mutans. In the present study, we showed that AMPs could be easily enriched from protein hydrolysate using HT silica gel. The adsorption/desorption procedure using HT silica gel was confirmed to be a useful tool for convenient BP separation.

Agonist/Antagonist Activity of Oxytocin Variants Obtained from Free Cyclic Peptide Libraries Generated via Amino Acid Substitution

We established a method for synthesizing a free cyclic peptide library via peptide array synthesis to demonstrate the sequence activity of cyclic peptides. Variants of the cyclic nonapeptide oxytocin (OXT) were synthesized via residue substitution. Natural amino acids (AAs) were classified into eight groups based on their physical properties and the size of their side chains, and a representative AA from each group was selected for residue substitution. All OXT variants were systematically evaluated for agonist/antagonist activity. Consequently, no improvement in agonist activity was observed, although substitution of the P4 and P8 residues resulted in decreased activity due to AA substitution. A few OXT variants exhibited antagonistic activity. In particular, the variants with P2 Leu residue substitution (Y2L) and Phe substitutions at residues 4 (Q4F), 5 (N5F), and 7 (P7F) showed high antagonistic activity. Variant Y2W was found to have the highest inhibitory effect, with a dissociation constant of 44 nM, which was comparable to that of the commercial antagonist atosiban (21 nM). Therefore, a free cyclic peptide library constructed via substitution with a natural AA residue was confirmed to be a powerful tool for bioactive peptide screening.

In Silico Screening of a Bile Acid Micelle Disruption Peptide for Oral Consumptions from Edible Peptide Database

Recently, many bioactive peptides have been identified using bioinformatics tools. Previously, our group developed a method to screen dual-functional peptides that have direct intestinal delivery with porous silica gel and bile acid micelle disruption. However, newly designed peptides were not found in any storage protein. Therefore, in this study, in silico screening was performed using a 350,000 edible peptide library consisting of 4- to 7-mer independent peptides. As an initial screening, all edible peptides were applied to the random forest model to select predicted positive peptides. For a second screening, the peptides were assessed for the possibility of intestinal delivery using a 3D color map. From this approach, three novel dual-functional peptides, VYVFDE, WEFIDF, and VEEFYC were identified, and all of them were derived from storage proteins (legumin, myosin, and 11S globulin). In particular, VEEFYCS, in which a serine residue (S) is added to VEEFYC, was assumed to be released by thermolysin from the 11S-globulin derived from Ginkgo biloba by LC-MS/MS analysis. VEEFYCS was found to have suitable direct intestinal delivery and bile acid micelle disruption activity.

Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution

Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diabetes mellitus, and various small-molecule agonists have been developed. However, most FFAR1 agonists as well as endogenous ligands, such as linoleic acids, have high lipophilicity, and their high lipophilicity is related to off-target toxicity. Therefore, we need to focus on new ligand candidates with less toxicity. In this study, we screened peptides with FFAR1 agonist activity as new ligand candidates. First, we used phage display to identify peptides with high affinity to FFAR1. Next, the agonist activities of peptides determined by the phage display were evaluated by the TGF-α shedding assay. Finally, to improve the FFAR1 agonist activity of the peptide, we performed an inclusive single amino acid substitution and sequence analysis. Logistic regression (LR) analysis using 120 physiochemical properties was performed to predict peptides with high FFAR1 agonist activity. STTGTQY determined by phage display promoted glucose-stimulated insulin secretion in pancreatic MIN6 cells. Furthermore, STKGTF predicted by the LR analysis showed high insulin secretion at low concentrations compared to STTGTQY. The results of this study suggest that peptides could be new candidates as FFAR1 agonists.