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…

THE EFFECT OF DIFFERENT TERROIRS ON AROMA COMPOUNDS OF ‘KALECIK KARASI’ WINES

Kalecik Karası is a domestic grape variety of Turkey, originating from Kalecik district, 80 km from Ankara. Although there is no definite evidence, it is known that it was used in wine production by many civilizations that lived in the Anatolian region, especially the Hittites. Compared to other black wine grapes, it stands out with its low tannin content, rich fruity aroma and complex structure. In good vintages, red fruits such as strawberries, cherries and raspberries stand out in the aroma profile. Although its structure is elegant, it has the potential to age and develop similar to the ‘Pinot Noir’ wine of the Burgundy region. This offers a complex aroma structure including red flowers, earth and ripe fruits.

2018 updates on the agronomic performances of fungus resistant wine grapes in Trentino (Italy)

On the market there are several wine grapes which are tolerant to the main fungal diseases. These varieties, commonly defined “resistant”, were developed in the grapevine breeding programs carried out mainly in Germany, France, Hungary and Italy. Some of these cultivars have been included in the national catalogues of wine grape varieties and have sometimes been allowed for specific kinds of wine. The VEVIR project, aimed at the enological evaluation of resistant vines, involves 33 cultivars achieved at the State Institute for Viticulture Freiburg in Germany, the Research Institute of Viticulture and Enology Pecs in Hungary and the Fondazione Edmund Mach S. Michele all’Adige (FEM) in Italy.

Il sistema vigneto del Lago di Bolsena: caratterizzazione della produzione di Cannaiola di Marta

Il comprensorio del Lago di Bolsena (VT) è un territorio ad elevata vocazione vitivinicola in cui il paesaggio della vite storicamente persiste e caratterizza la fisionomia dei luoghi. Qui gli agroecosistemi viticoli possiedono una valenza ecologico-ambientale, storico-culturale ed economica di rilievo.

Towards the understanding of wine distillation in the production of brandy de Jerez. Chemical and sensory characterization of two distillation methods: continuous and batch distillation

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (1) and varies each year of harvest depending on the weather conditions (2).

Sustainability as system innovation: sustainability as system innovation: a returnable system for glass wine bottles

Introduction increasing sustainability is essential and a societal challenge, requiring fundamental changes in behaviour and attitudes. This applies to both producers and consumers. For the wine industry in particular, such a change is a major challenge. An eip-agri research project is evaluating the introduction of a returnable glass system in the german wine industry as a key solution for increasing sustainability. Given the need for change associated with a returnable system, the project is theoretically grounded in systems innovation, as this approach provides solutions for complex, transformative change.