Protein Concentrates on Tepary Bean (Phaseolus acutifolius Gray) as a Functional Ingredient: In silico Docking of Tepary Bean Lectin to Peroxisome Proliferator-Activated Receptor Gamma

López-Ibarra, Cristina; Ruiz-López, F.J.; Villarreal, Minerva Bautista; González, Juan Gabriel Báez; Romero, Beatriz Adriana Rodríguez; González-Martínez, Blanca Edelia; Lomelí, Manuel López-Cabanillas; Vázquez-Rodríguez, Jesús Alberto

doi:10.3389/fnut.2021.661463

Cited by 3 publications

(4 citation statements)

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“…Although phaseolin is not directly related to drought stress in the seeds of common bean, the abundance of P. acutifolius decreased in both treatments. Is well knowed that phaseolin fraction is the major seed storage protein in cotyledon of Tepary bean [ 21 ]. However, the regulatory mechanisms responsible for the synthesis, accumulation and degradation of phaseolin in the common bean seed are not yet sufficiently known [ 32 – 34 ].…”

Section: Discussionmentioning

confidence: 99%

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Proteomic profile of tepary bean seed storage proteins in germination with low water potential

Padilla-Chacón,

Campos-Patiño,

Peña-Valdivia

et al. 2024

Proteome Sci

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Background Tepary bean (Phaseolus acutifolius A. Gray) is one of the five species domesticated from the genus Phaseolus with genetic resistance to biotic and abiotic stress. To understand the mechanisms underlying drought responses in seed storage proteins germinated on water and polyethylene glycol (PEG-6000) at -0.49 MPa, we used a proteomics approach to identify potential molecular target proteins associated with the low water potential stress response. Methods Storage proteins from cotyledons of Tepary bean seeds germinated at 24, 48 and 72 h on water and PEG-6000 at -0.49 MPa were analyzed by one-dimensional electrophoresis (DE) with 2-DE analysis and shotgun mass spectrometry. Using computational database searching and bioinformatics analyses, we performed Gene Ontology (GO) and protein interactome (functional protein association network) String analyses. Results Comparative analysis showed that the effect of PEG-6000 on root growth was parallel to that on germination. Based on the SDS‒PAGE protein banding patterns and 2-DE analysis, ten differentially abundant seed storage proteins showed changes in storage proteins, principally in the phaseolin and lectin fractions. We found many proteins that are recognized as drought stress-responsive proteins, and several of them are predicted to be intrinsically related to abiotic stress. The shotgun analysis searched against UniProt’s legume database, and Gene Ontology (GO) analysis indicated that most of the seed proteins were cytosolic, with catalytic activity and associated with carbohydrate metabolism. The protein‒protein interaction networks from functional enrichment analysis showed that phytohemagglutinin interacts with proteins associated with the degradation of storage proteins in the cotyledons of common bean during germination. Conclusion These findings suggest that Tepary bean seed proteins provide valuable information with the potential to be used in genetic improvement and are part of the drought stress response, making our approach a potentially useful strategy for discovering novel drought-responsive proteins in other plant models.

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Section: Discussionmentioning

confidence: 99%

“…The phaseolin fraction usually represents the largest proportion of proteins in grain and legumes (36–46%), with those inside the beans being the most abundant. Furthermore, lectins are 120 KDa tetramers (subunits approximately 31 KDa) and represent 5–12% of the total protein in the genus Phaseolus [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Proteomic profile of tepary bean seed storage proteins in germination with low water potential

Padilla-Chacón,

Campos-Patiño,

Peña-Valdivia

et al. 2024

Proteome Sci

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“…The antiadipogenic effect via PPARγ is possible due to the interaction of this receptor in adipose tissue, and, additionally, it has been reported that peptides that exert bioactivity are usually hydrophobic in nature [ 16 ]. These PPARγ BAPs are mainly studied in whey protein, spirulina ( Spirulina platensis ), and legumes such as soy ( Glycine max ) and tepary bean ( Phaseolus acutifolius ) [ 15 , 17 , 18 ], but cereal proteins such as rice ( Oryza sativa ), mainly prolamin and glutelin fractions, present activity against ACE and DPPIV enzymes, and present antioxidant activity [ 19 , 20 , 21 ], and their potential bioactivity against specific receptors related to obesity, such as PPARγ, remains unknown.…”

Section: Introductionmentioning

confidence: 99%

In Silico Identification of Peptides with PPARγ Antagonism in Protein Hydrolysate from Rice (Oryza sativa)

et al. 2023

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At least half the population in industrialized countries suffers from obesity due to excessive accumulation of adipose tissue. Recently, rice (Oryza sativa) proteins have been considered valuable sources of bioactive peptides with antiadipogenic potential. In this study, the digestibility and bioaccessibility in vitro of a novel protein concentrate (NPC) from rice were determined through INFOGEST protocols. Furthermore, the presence of prolamin and glutelin was evaluated via SDS-PAGE, and their potential digestibility and the bioactivity of ligands against peroxisome proliferator-activated receptor gamma (PPARγ) were explored by BIOPEP UWM and HPEPDOCK. For the top candidates, molecular simulations were conducted using Autodock Vina to evaluate their binding affinity against the antiadipogenic region of PPARγ and their pharmacokinetics and drug-likeness using SwissADME. Simulating gastrointestinal digestion showed a recovery of 43.07% and 35.92% bioaccessibility. The protein banding patterns showed the presence of prolamin (57 kDa) and glutelin (12 kDa) as the predominant proteins in the NPC. The in silico hydrolysis predicts the presence of three and two peptide ligands in glutelin and prolamin fraction, respectively, with high affinity for PPARγ (≤160). Finally, the docking studies suggest that the prolamin-derived peptides QSPVF and QPY (−6.38 & −5.61 kcal/mol, respectively) have expected affinity and pharmacokinetic properties to act as potential PPARγ antagonists. Hence, according to our results, bioactive peptides resulting from NPC rice consumption might have an antiadipogenic effect via PPARγ interactions, but further experimentation and validation in suitable biological model systems are necessary to gain more insight and to provide evidence to support our in silico findings.

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“…The grains of tepary bean are rich in proteins, sucrose, lipids, and mineral elements such as N, P, K, Mg, Ca, Cu, Fe, Mn, S, and Zn [6][7][8]. Between 34 and 40 Kilodaltons of lectin protein present in tepary bean have been associated with beneficial health effects such as anticancer and antidiabetic properties [9]. Further, the crop is resistant to various insect pests (e.g., bean weevil, leafhopper, thrips) and diseases (i.e., common bacterial blight, anthracnose, fusarium wilt, angular leaf spot, ashy stem blight) [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Genotype-by-Environment Interaction in Tepary Bean (Phaseolus acutifolius A. Gray) for Seed Yield

et al. 2022

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Genotype-by-environment (GEI) analysis guides the recommendation of best-performing crop genotypes and production environments. The objective of this study was to determine the extent of GEI on seed yield in tepary bean for genotype recommendation and cultivation in drought-prone environments. Forty-five genetically diverse tepary bean genotypes were evaluated under non-stressed and drought-stressed conditions for two seasons using a 9 × 5 alpha lattice design with three replications in four testing environments. Data were collected on seed yield (SY) and days to physiological maturity (DTM) and computed using a combined analysis of variance, the additive main effect and multiplicative interaction (AMMI), the best linear unbiased predictors (BLUPs), the yield stability index (YSI), the weighted average of absolute scores (WAASB) index, the multi-trait stability index (MTSI), and a superiority measure. AMMI analysis revealed a significant (p < 0.001) GEI, accounting for 13.82% of the total variation. Genotype performance was variable across the test environments, allowing the selection of best-suited candidates for the target production environment. The environment accounted for a substantial yield variation of 52.62%. The first and second interaction principal component axes accounted for 94.8 and 4.7% of the total variation in the AMMI-2 model, respectively, of surmountable variation due to GEI. The AMMI 2 model family was sufficient to guide the selection of high-yielding and stable genotypes. Based on best linear unbiased predictors (BLUPs), yield stability index (YSI), superiority measure (Pi), and broad adaptation, the following tepary bean genotypes were identified as high-yielding and suited for drought-prone environments: G40138, G40148, G40140, G40135, and G40158. The selected tepary bean genotypes are recommended for cultivation and breeding in Malawi or other related agroecologies.

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Protein Concentrates on Tepary Bean (Phaseolus acutifolius Gray) as a Functional Ingredient: In silico Docking of Tepary Bean Lectin to Peroxisome Proliferator-Activated Receptor Gamma

Cited by 3 publications

References 56 publications

Proteomic profile of tepary bean seed storage proteins in germination with low water potential

Proteomic profile of tepary bean seed storage proteins in germination with low water potential

In Silico Identification of Peptides with PPARγ Antagonism in Protein Hydrolysate from Rice (Oryza sativa)

Genotype-by-Environment Interaction in Tepary Bean (Phaseolus acutifolius A. Gray) for Seed Yield

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