TY - JOUR
T1 - Bitterness prediction in-silico
T2 - A step towards better drugs
AU - Bahia, Malkeet Singh
AU - Nissim, Ido
AU - Niv, Masha Y.
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2018/2/5
Y1 - 2018/2/5
N2 - 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.
AB - 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.
KW - Bitterness
KW - GPCRs
KW - Pediatric drugs
KW - Prediction
KW - Promiscuity
KW - Tas2Rs
KW - Taste receptors
KW - in-silico
UR - http://www.scopus.com/inward/record.url?scp=85016422746&partnerID=8YFLogxK
U2 - 10.1016/j.ijpharm.2017.03.076
DO - 10.1016/j.ijpharm.2017.03.076
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C2 - 28363856
AN - SCOPUS:85016422746
SN - 0378-5173
VL - 536
SP - 526
EP - 529
JO - International Journal of Pharmaceutics
JF - International Journal of Pharmaceutics
IS - 2
ER -