Generating Flavor Molecules Using Scientific Machine Learning.

ABSTRACT: Flavor is an essential component in the development of numerous products in the market. The increasing consumption of processed and fast food and healthy packaged food has upraised the investment in new flavoring agents and consequently in molecules with flavoring properties. In this context, this work brings up a scientific machine learning (SciML) approach to address this product engineering need. SciML in computational chemistry has opened paths in the compound's property prediction without requiring synthesis. This work proposes a novel framework of deep generative models within this context to design new flavor molecules. Through the analysis and study of the molecules obtained from the generative model training, it was possible to conclude that even though the generative model design

SUBMITTER: Queiroz LP 

PROVIDER: S-EPMC10061502 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature