Yissum - Research Development Company of the Hebrew University

Computerized Prediction of Taste Recognition (Bitter and Sweet)

Posted by Yissum - Research Development Company of the Hebrew UniversityResponsive · Innovative Products and Technologies · Israel

Summary of the technology


Computer-aided taste modulators identification
Project ID : 23-2016-4357

Yissum - Research Development Company of the Hebrew University
Yissum - Research Development Company of the Hebrew University

Description of the technology


Food & Nutrition, Computer-aided drug discovery


Bitter, Sweet, Machine Learning, Chemical features

Current development stage

TRL7System prototype demonstration


  • Basic taste qualities like sweet, bitter, sour, salty and umami serve specific functions in identifying food components found in the diet of humans and animals, and are recognized by bitter taste receptors in the oral cavity.
  • It is desirable to identify potential bitter taste of food and pharmaceutical compounds
  • Bitter taste receptors are expressed in extra-oral tissues and are considered as novel therapeutic targets, mainly for asthma.

Our Innovation

A novel and generic computer-aided technique for molecular taste recognition, prediction and compounds classifier to facilitate studying the chemical features associated with bitterness and sweetness ExistingBitterDB is a free and searchable database that includes over 680 compounds that were reported to taste bitter to human.

BitterDB predicts taste from chemical structure with ~80% accuracy (BitterPredict) and a novel (unpublished) predictor for intensely bitter compounds

  • Researchers proved a weak relation between bitterness and toxic. Bbitterness is more common in therapeutic drugs than in highly toxic compounds.


  • A machine learning classifier, BitterPredict predicts whether a compound is bitter or not, based on its chemical structure. The bitterness prediction is based on ligands that fit to a 3D model of receptor or are similar to a particular bitter ligand.
  • Adaptive Boosting based on decision trees machine-learning algorithm applied to the molecules that were represented. Distribution of oral LD50 values of bitter had the same trend as non-bitter.
  • Structure-based and ligand-based prediction of agonists for particular human bitter taste receptors were successfully validated.
  • A structure-based and ligand-based computational approaches to predict novel sweeteners and sweetness enhancers.
  • Sensory tests confirmation.

Fig. 1: Bitter and non-bitter chemical space

  • A newer classifier predicts whether compound is intenselybitter or not.

Sweetness enhancement:


  • Bitterness and intense prediction of unknown compounds.
  • Ligands prediction for bitter receptors from different species and rational design of bitterness modulators.
  • New sweeteners and sweetness enhancers with 15-35% less calories for the same sweetness.

Project manager

Ilya Pittel

Project researchers

Masha Niv
HUJI, Faculty of Agricultural, Food and Environmental Quality Sciences
Biochemistry, Food Science and Nutrition

Related keywords

  • Information Processing, Information System, Workflow Management
  • IT and Telematics Applications
  • Multimedia
  • Materials Technology
  • Chemistry
  • Technologies for the food industry
  • Food quality and safety
  • Micro- and Nanotechnology related to agrofood
  • Agrofood Industry
  • Computers
  • Computer Graphics Related
  • Specialised Turnkey Systems
  • Scanning Related
  • Peripherals
  • Computer Services
  • Computer Software Market
  • Other Computer Related
  • Food and Beverages
  • Chemicals and Materials
  • Food & Nutrition
  • Functional Foods & Ingredients

About Yissum - Research Development Company of the Hebrew University

Technology Transfer Office from Israel

Yissum Research Development Company of the Hebrew University of Jerusalem Ltd. Founded in 1964 to protect and commercialize the Hebrew University’s intellectual property. Ranked among the top technology transfer companies, Yissum has registered over 8,900 patents covering 2,500 inventions; has licensed out 800 technologies and has spun-off 90 companies. Products that are based on Hebrew University technologies and were commercialized by Yissum generate today over $2 Billion in annual sales.

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