terclim by ICS banner
IVES 9 IVES Conference Series 9 Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Artificial intelligence (AI)-based protein modeling for the interpretation of grapevine genetic variants

Abstract

Genetic variants known to produce single residue missense mutations have been associated with phenotypic traits of commercial interest in grapevine. This is the case of the K284N substitution in VviDXS1 associated with muscat aroma, or the R197L in VviAGL11 causing stenospermocarpic seedless grapes. The impact of such mutations on protein structure, stability, dynamics, interactions, or functional mechanism can be studied by computational methods, including our pyDock scoring, previously developed. For this, knowledge on the 3D structure of the protein and its complexes with other proteins and biomolecules is required, but such knowledge is not available for virtually none of the proteins and complexes in grapevine. Fortunately, the possibility of modeling proteins and complex structures with Artificial Intelligence (AI)-based methods like AlphaFold2 and AlphaFold2-Multimer will facilitate the application of this approach to proteins and complexes without available structure. Moreover, we are developing new methods based on AI to combine AlphaFold models, molecular dynamics (MD), pyDock energy scoring, and CCharPPI descriptors to predict the impact of protein mutations at the molecular level. As a case study, we have modelled the impact of the R197L seedlessness-associated substitution in VviAGL11. This protein is a homo-dimeric transcription factor that interacts with VviMADS4 dimeric protein to form a functional hetero-tetramer. Structural modeling of this complex provides insights into the functional mechanism of this protein and the role of the mentioned mutation. This protein modeling approach could be extended for grapevine mutation analysis at the genomic level.

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Poster

Authors

Luis Ángel Rodríguez-Lumbreras1, Víctor Monteagudo1, Pablo Carbonell-Bejerano1, Fabian Glaser2, Juan Fernández-Recio1*

1 Instituto de Ciencias de la Vid y del Vino (ICVV), CSIC-UR-Gobierno de La Rioja, Spain
2 Technion Institute of Technology, Israel

Contact the author*

Keywords

AI-based modeling, Seedless grapes, Protein-protein interactions, Mutation impact analysis, Protein structure

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

Observation and modeling of climate at fine scales in wine-producing areas

Global change in climate affect regional climates and hold implications for viticulture worldwide. Despite numerous studies on the impact of projected global warming on different regions

Relationship between chemical parameters of tannins and in-mouth attributes of grape phenolic fractions

Establish relationships between taste and mouthfeel properties of grapes and tannin-related chemical parameters. Tempranillo Tinto and Garnacha Tinta grapes were harvested from distinct blocks in different dates; each sample collection date was separated by one week. Grapes were destemmed and macerated in 15% of ethanol for one week. The polyphenolic fraction (PF) of samples was submitted to solid phase extraction on C18 cartridges and recovered with ethanol. PFs were reconstituted in wine model and their taste and mouthfeel properties were characterised by rate-K-attributes methodology. In parallel, concentration (TC) and activity (TAc) of tannins as well as the concentration of tannins linked to anthocyanins (T-A) were determined using HPLC-UV–VIS.

Redwine project: increasing microalgae biomass feedstock by valorising wine gaseous and liquid residues

Global warming due to greenhouse gases (GHG) has become a serious worldwide concern.

Mapping aromatic profiles of Chardonnay and Sangiovese wines in grafting combination with new rootstocks

Rootstocks play a key role in the adaptation of grapevine to environmental conditions, affecting phenology, vigour, yield and grape quality.

Leaf vine content in nutrients and trace elements in La Mancha (Spain) soils: influence of the rootstock

The use of rootstock of American origin has been the classic method of fighting against Phylloxera for more than 100 years. For this reason, it is interesting to establish if different rootstock modifies nutrient composition as well as trace elements content that could be important for determining the traceability of the vine products. A survey of four classic rootstocks (110-Richter, SO4, FERCAL and 1103-Paulsen) and four new ones (M1, M2, M3 and M4) provided by Agromillora Iberia. S.L.U., all of them grafted with the Tempranillo variety, has been carried out during 2019. The eight rootstocks were planted in pots of 500 cc, on three soils with very different characteristics from Castilla-La Mancha (Spain). In the month of July, the leaves were collected and dried in a forced air oven for seven days at 40ºC. Then, the samples were prepared for the analysis determination, carried out by X-Ray fluorescence spectrometry. The results obtained showed that in the case of content in mineral elements in leaf, separated by soil type, we can report the importance of few elements such as Si, Fe, Pb and, especially, Sr. The rootstock does not influence the composition of the vine leaf for the studied elements that are the most important in determining the geochemical footprint of the soil. The influence of the soil can be discriminated according to some elements such as Fe, Pb, Si and, especially, Sr.