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Computer-Aided Screening and Action Mechanism of Bioactive Peptides

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 10849

Special Issue Editor


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Guest Editor
School of Food Science and Engineering, Hainan University, Haikou 570228, China
Interests: bioactive peptides; virtual screening; proteomics; metabolomics; bioavailability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Interest in research into bioactive peptides is growing because of their health-promoting ability. Several bioactivities have been ascribed to peptides, including antioxidant, antihypertensive, and antimicrobial properties. The implementation of a peptide’s potential biological effect depends largely on its structure and bioavailability. The purpose of this Special Issue is to report the recent progress achieved in virtual screening and action mechanism of bioactive peptides. This includes, but is not limited to, isolation and identification of peptides, molecular docking, prediction, proteomics, metabolomics, bioavailability, permeability of peptides, and network pharmacology. The bioinformatics tools and databases assisting action mechanism are also welcomed.

Prof. Dr. Zhipeng Yu
Guest Editor

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Keywords

  • peptides
  • screening
  • proteomics
  • metabolomics
  • bioavailability
  • molecular docking
  • molecular dynamics simulation
  • identification
  • absorption enhancers

Published Papers (5 papers)

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Research

15 pages, 1973 KiB  
Article
Using the Random Forest for Identifying Key Physicochemical Properties of Amino Acids to Discriminate Anticancer and Non-Anticancer Peptides
by Yiting Deng, Shuhan Ma, Jiayu Li, Bowen Zheng and Zhibin Lv
Int. J. Mol. Sci. 2023, 24(13), 10854; https://doi.org/10.3390/ijms241310854 - 29 Jun 2023
Cited by 1 | Viewed by 1305
Abstract
Anticancer peptides (ACPs) represent a promising new therapeutic approach in cancer treatment. They can target cancer cells without affecting healthy tissues or altering normal physiological functions. Machine learning algorithms have increasingly been utilized for predicting peptide sequences with potential ACP effects. This study [...] Read more.
Anticancer peptides (ACPs) represent a promising new therapeutic approach in cancer treatment. They can target cancer cells without affecting healthy tissues or altering normal physiological functions. Machine learning algorithms have increasingly been utilized for predicting peptide sequences with potential ACP effects. This study analyzed four benchmark datasets based on a well-established random forest (RF) algorithm. The peptide sequences were converted into 566 physicochemical features extracted from the amino acid index (AAindex) library, which were then subjected to feature selection using four methods: light gradient-boosting machine (LGBM), analysis of variance (ANOVA), chi-squared test (Chi2), and mutual information (MI). Presenting and merging the identified features using Venn diagrams, 19 key amino acid physicochemical properties were identified that can be used to predict the likelihood of a peptide sequence functioning as an ACP. The results were quantified by performance evaluation metrics to determine the accuracy of predictions. This study aims to enhance the efficiency of designing peptide sequences for cancer treatment. Full article
(This article belongs to the Special Issue Computer-Aided Screening and Action Mechanism of Bioactive Peptides)
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22 pages, 4683 KiB  
Article
In Silico Exploration of Metabolically Active Peptides as Potential Therapeutic Agents against Amyotrophic Lateral Sclerosis
by Toluwase Hezekiah Fatoki, Stanley Chukwuejim, Chibuike C. Udenigwe and Rotimi E. Aluko
Int. J. Mol. Sci. 2023, 24(6), 5828; https://doi.org/10.3390/ijms24065828 - 18 Mar 2023
Cited by 2 | Viewed by 2788
Abstract
Amyotrophic lateral sclerosis (ALS) is regarded as a fatal neurodegenerative disease that is featured by progressive damage of the upper and lower motor neurons. To date, over 45 genes have been found to be connected with ALS pathology. The aim of this work [...] Read more.
Amyotrophic lateral sclerosis (ALS) is regarded as a fatal neurodegenerative disease that is featured by progressive damage of the upper and lower motor neurons. To date, over 45 genes have been found to be connected with ALS pathology. The aim of this work was to computationally identify unique sets of protein hydrolysate peptides that could serve as therapeutic agents against ALS. Computational methods which include target prediction, protein-protein interaction, and peptide-protein molecular docking were used. The results showed that the network of critical ALS-associated genes consists of ATG16L2, SCFD1, VAC15, VEGFA, KEAP1, KIF5A, FIG4, TUBA4A, SIGMAR1, SETX, ANXA11, HNRNPL, NEK1, C9orf72, VCP, RPSA, ATP5B, and SOD1 together with predicted kinases such as AKT1, CDK4, DNAPK, MAPK14, and ERK2 in addition to transcription factors such as MYC, RELA, ZMIZ1, EGR1, TRIM28, and FOXA2. The identified molecular targets of the peptides that support multi-metabolic components in ALS pathogenesis include cyclooxygenase-2, angiotensin I-converting enzyme, dipeptidyl peptidase IV, X-linked inhibitor of apoptosis protein 3, and endothelin receptor ET-A. Overall, the results showed that AGL, APL, AVK, IIW, PVI, and VAY peptides are promising candidates for further study. Future work would be needed to validate the therapeutic properties of these hydrolysate peptides by in vitro and in vivo approaches. Full article
(This article belongs to the Special Issue Computer-Aided Screening and Action Mechanism of Bioactive Peptides)
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12 pages, 2351 KiB  
Article
Screening and Molecular Mechanisms of Novel ACE-Inhibitory Peptides from Gracilariopsis lemaneiformis
by Yongchang Su, Shicheng Chen, Jiashen Shen, Zhiwei Yi, Shuji Liu, Shuilin Cai, Nan Pan, Kun Qiao, Xiaoting Chen, Bei Chen, Min Xu, Suping Yang and Zhiyu Liu
Int. J. Mol. Sci. 2022, 23(23), 14850; https://doi.org/10.3390/ijms232314850 - 27 Nov 2022
Cited by 4 | Viewed by 1706
Abstract
Candidate peptides with novel angiotensin-I-converting enzyme (ACE) inhibitor activity were obtained from hydrolysates of Gracilariopsis lemaneiformis by virtual screening method. Our results showed that G. lemaneiformis peptides (GLP) could significantly lower blood pressure in spontaneously hypertensive rats (SHR). At least 101 peptide sequences [...] Read more.
Candidate peptides with novel angiotensin-I-converting enzyme (ACE) inhibitor activity were obtained from hydrolysates of Gracilariopsis lemaneiformis by virtual screening method. Our results showed that G. lemaneiformis peptides (GLP) could significantly lower blood pressure in spontaneously hypertensive rats (SHR). At least 101 peptide sequences of GLP were identified by LC-MS/MS analysis and subjected to virtual screening. A total of 20 peptides with the highest docking score were selected and chemically synthesized in order to verify their ACE-inhibitory activities. Among them, SFYYGK, RLVPVPY, and YIGNNPAKG showed good effects with IC50 values of 6.45 ± 0.22, 9.18 ± 0.42, and 11.23 ± 0.23 µmoL/L, respectively. Molecular docking studies revealed that three peptides interacted with the active center of ACE by hydrogen bonding, hydrophobic interactions, and electrostatic forces. These peptides could form stable complexes with ACE. Furthermore, SFYYGK, RLVPVPY, and YIGNNPAKG significantly reduced systolic blood pressure (SBP) in SHR. YIGNNPAKG exhibited the highest antihypertensive effect, with the largest decrease in SBP (approximately 23 mmHg). In conclusion, SFYYGK, RLVPVPY, and YIGNNPAKG can function as potent therapeutic candidates for hypertension treatment. Full article
(This article belongs to the Special Issue Computer-Aided Screening and Action Mechanism of Bioactive Peptides)
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13 pages, 34682 KiB  
Article
In Silico Discovery of Anticancer Peptides from Sanghuang
by Minghao Liu, Jiachen Lv, Liyuan Chen, Wannan Li and Weiwei Han
Int. J. Mol. Sci. 2022, 23(22), 13682; https://doi.org/10.3390/ijms232213682 - 8 Nov 2022
Cited by 2 | Viewed by 2175
Abstract
Anticancer peptide (ACP) is a short peptide with less than 50 amino acids that has been discovered in a variety of foods. It has been demonstrated that traditional Chinese medicine or food can help treat cancer in some cases, which suggests that ACP [...] Read more.
Anticancer peptide (ACP) is a short peptide with less than 50 amino acids that has been discovered in a variety of foods. It has been demonstrated that traditional Chinese medicine or food can help treat cancer in some cases, which suggests that ACP may be one of the therapeutic ingredients. Studies on the anti-cancer properties of Sanghuangporus sanghuang have concentrated on polysaccharides, flavonoids, triterpenoids, etc. The function of peptides has not received much attention. The purpose of this study is to use computer mining techniques to search for potential anticancer peptides from 62 proteins of Sanghuang. We used mACPpred to perform sequence scans after theoretical trypsin hydrolysis and discovered nine fragments with an anticancer probability of over 0.60. The study used AlphaFold 2 to perform structural modeling of the first three ACPs discovered, which had blast results from the Cancer PPD database. Using reverse docking technology, we found the target proteins and interacting residues of two ACPs with an unknown mechanism. Reverse docking results predicted the binding modes of the ACPs and their target protein. In addition, we determined the active part of ACPs by quantum chemical calculation. Our study provides a framework for the future discovery of functional peptides from foods. The ACPs discovered have the potential to be used as drugs in oncology clinical treatment after further research. Full article
(This article belongs to the Special Issue Computer-Aided Screening and Action Mechanism of Bioactive Peptides)
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15 pages, 4776 KiB  
Article
Computer-Aided Screening and Revealing Action Mechanism of Food-Derived Tripeptides Intervention in Acute Colitis
by Huifang Ge, Ting Zhang, Yuanhu Tang, Yan Zhang, Yue Yu, Fangbing Men, Jingbo Liu and Yiding Yu
Int. J. Mol. Sci. 2022, 23(21), 13471; https://doi.org/10.3390/ijms232113471 - 3 Nov 2022
Cited by 2 | Viewed by 1571
Abstract
Food-derived tripeptides can relieve colitis symptoms; however, their alleviation mode has not been systematically evaluated as an alternative nutritional compound. This study aimed to reveal the potential mechanism of 8000 food-derived tripeptides against acute colitis using a computer-aided screening strategy. Forty-one potential hub [...] Read more.
Food-derived tripeptides can relieve colitis symptoms; however, their alleviation mode has not been systematically evaluated as an alternative nutritional compound. This study aimed to reveal the potential mechanism of 8000 food-derived tripeptides against acute colitis using a computer-aided screening strategy. Forty-one potential hub targets related to colitis with a Fit score > 4.0 were screened to construct the protein-protein and protein-tripeptide network based on the PharmMapper database and STRING software (Ver. 11.5). In addition, 30 significant KEGG signaling pathways with p-values < 0.001 that the 41 hub targets mainly participated in were identified using DAVID software (Ver. 6.8), including inflammatory, immunomodulatory, and cell proliferation and differentiation-related signaling pathways, particularly in the Ras- and PI3K-Akt signaling pathways. Furthermore, molecular docking was performed using the Autodock against majorly targeted proteins (AKT1, EGFR, and MMP9) with the selected 52 tripeptides. The interaction model between tripeptides and targets was mainly hydrogen-bonding and hydrophobic interactions, and most of the binding energy of the tripeptide target was less than −7.13 kcal/mol. This work can provide valuable insight for exploring food-derived tripeptide mechanisms and therapeutic indications. Full article
(This article belongs to the Special Issue Computer-Aided Screening and Action Mechanism of Bioactive Peptides)
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