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Bitterness prediction in-silico: A step towards better drugs | Biochemistry, Food Science and Nutrition

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Head of Institute: Prof. Ido Braslavsky

Administrative manager: Rakefet Kalev

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Bitterness prediction in-silico: A step towards better drugs

Citation:

Bahia, M. S. ; Nissim, I. ; Niv, M. Y. . Bitterness Prediction In-Silico: A Step Towards Better Drugs. International Journal of Pharmaceutics 2018, 536, 526 - 529.

Abstract:

Bitter taste is innately aversive and thought to protect against consuming poisons. Bitter taste receptors (Tas2Rs) are G-protein coupled receptors, expressed both orally and extra-orally and proposed as novel targets for several indications, including asthma. Many clinical drugs elicit bitter taste, suggesting the possibility of drugs re-purposing. On the other hand, the bitter taste of medicine presents a major compliance problem for pediatric drugs. Thus, efficient tools for predicting, measuring and masking bitterness of active pharmaceutical ingredients (APIs) are required by the pharmaceutical industry. Here we highlight the BitterDB database of bitter compounds and survey the main computational approaches to prediction of bitter taste based on compound's chemical structure. Current in silico bitterness prediction methods provide encouraging results, can be constantly improved using growing experimental data, and present a reliable and efficient addition to the APIs development toolbox.

Notes:

Formulating Better Medicines for Children – European Paediatric Formulation Initiative (EuPFI) 2016

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