Wednesday, October 18, 2017

FlavorDB: A resource for flavor molecules

Why do we eat what we eat?

Simple questions are often the most difficult to answer. When we started exploring this question, traditional recipes from many Western cuisines had been shown to be characterized by the ‘uniform food pairing’ phenomenon. Such homogeneous blending was consistent with the hypothesis suggested by Chef Heston Blumenthal. When we started investigating traditional Indian recipes for their blend, while I had a niggling thought about the generality of food pairing rule, true to my training as a physicist I was hoping to find a universal phenomenon reflecting the fundamental basis for culinary preferences of Homo sapiens.

What seemed like an innocuous question led to the serendipitous discovery of ‘contrasting food pairing’ in Indian cuisine through data-driven studies conducted from our lab. Like any good research, apart from answering one question, it opened up many more. These questions have led to divergent investigations: mathematical models for the evolution of recipes, molecular basis of ingredient flavors, emergence of the flavor of a recipe, algorithms for novel recipe generation, food-disease associations, the therapeutic potential of phytochemicals and strategies for leveraging food as medicine, among others.

In the Complex Systems Laboratory at IIIT-Delhi, we are investigating many of these questions that encompass overlapping domains including social history, computer science, mathematical modeling, chemoinformatics and medicine. Some of these queries relate to the perception of flavor, an emergent property of a complex biochemical system arising from the interaction of flavor molecules with gustatory and olfactory mechanisms. Answering these questions that invoke perception of taste and odor require a solid foundation of data of flavor molecules and associated features that are critical for the sensation of flavor.  

With this vision, we have created FlavorDB, a comprehensive database of flavor molecules:  It comprises of 25595 flavor molecules representing an array of tastes and odors. Among these 2254 molecules are associated with 936 natural ingredients belonging to 34 categories. The dynamic, user-friendly interface of the resource facilitates exploration of flavor molecules for divergent applications: finding molecules matching a desired flavor or structure; exploring molecules of an ingredient; discovering novel food pairings; finding the molecular essence of food ingredients; associating chemical features with a flavor and more. Such data-driven studies springing out of FlavorDB are expected to pave the way for an improved understanding of flavor mechanisms.

Publication: Neelansh Garg†, Apuroop Sethupathy†, Rudraksh Tuwani†, Rakhi NK†, Shubham Dokania†, Arvind Iyer†, Ayushi Gupta†, Shubhra Agrawal†, Navjot Singh†, Shubham Shukla†, Kriti Kathuria†, Rahul Badhwar, Rakesh Kanji, Anupam Jain, Avneet Kaur, Rashmi Nagpal, and Ganesh Bagler*, FlavorDB: A database of flavor molecules, Nucleic Acids Research, Accepted (2017).
 † Equal contribution
 * Corresponding Author 

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