A unique Machine-Learning and Molecular Modelling pipeline focusing on the interactome of the Taste Receptors has been released in a new publication from the InSyBio team in collaboration with a team of exceptional researchers from Dalle Molle Institute for Artificial Intelligence (Switzerland), and Politecnico di Torino (Italy) in the framework of VIRTUOUS Project, an EU Horizon 2020 program.
In this study, a Machine-Learning (ML) methodology was developed for predicting binary Protein-Protein Interactions (PPIs) and ranking them based on their computationally predicted affinity. The ML models developed were then applied for resolving the Taste Receptor interactome and detecting the most important interactions of Taste Receptors from the multitude of potential ones. The detected interactions were further characterized through Molecular Dynamics analysis, verifying novel interactions of TAS2R41, such as the TAS2R41-CHMP4A. The classification and regression models applied were based on InSyBio’s multi-objective evolutionary optimization algorithm that is implemented in InSyBio Suite, showcasing the wide range of applications of InSyBio’s biomarker discovery and predictive analytics algorithms and pipelines.
This pipeline aims to facilitate taste perception research for nutrition and pharmaceutical companies and laboratories by filtering and characterizing the most significant Taste Receptor interactions for further studies. The paper was published in the NPJ Science of Food journal of the Springer Nature publishing company (https://rdcu.be/euiWe).
Image: Flowchart of the proposed ML and Molecular Dynamics analysis pipeline applied for the Taste Receptor Interactome.
Labros Digonis, CEO of InSyBio, commented on the importance of the tool:
“We are proud for this unique application of our machine learning and network analytics technology. Resolving the molecular mechanisms of taste is essential for engineering new food products and studying the health implications and downstream effects of different food products. This was an excellent collaborative result of our R&D working together with universities and research institutes in Italy, Greece and Switzerland. Congratulations to the pioneer team!”
About Virtuous: The EU-funded VIRTUOUS project (Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) – https://virtuoush2020.com/) is dedicated to the development of a virtual tongue made by an integrated computational framework that can screen food for natural components by binding taste receptors. This international consortium includes eight academic and industry participants from four European countries. Using a variety of computational and experimental data, partners plan to create an algorithm for the prediction of the organoleptic profile of the food based on its chemical composition. The potential application of this platform as a taste predictor is in the food industry, modern precision agriculture, and as a link to neuroscience for taste determination.
About InSyBio: InSyBio is an international pioneer bioinformatics revolutionizing the medical field, clinical trials and food/nutrition industries through targeted biomarker discovery and highly-accurate predictive analytics.
InSyBio solutions provide the R&D departments of Pharma, Research Institutes and Food/Nutrition companies, with the means both analytically and computationally, to meet their challenging research and innovation goals (such as robust biomarker discovery and accurate predictive models). This is done through a sophisticated, software-as-a-service, machine learning platform which comprehensively integrates multi-omics data reducing the number of samples and additional validation experiments needed. Since 2013, InSyBio has worked with hundreds of academics, large and small companies, hospitals and research centers allowing them to succeed in their biomarker discovery tasks with an increase of at least 10% in predictive accuracy and decrease of at least 80% in overall time and cost.
Visit www.insybio.com to see how InSyBio can help you reach your R&D goals in the era of Precision Medicine and Nutrition.