Mechanistic role of plant-based bitter principles and bitterness prediction for natural product studies I: Database and methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22310%2F19%3A43919270" target="_blank" >RIV/60461373:22310/19:43919270 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.degruyter.com/view/j/psr.2019.4.issue-7/psr-2018-0117/psr-2018-0117.xml" target="_blank" >https://www.degruyter.com/view/j/psr.2019.4.issue-7/psr-2018-0117/psr-2018-0117.xml</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1515/psr-2018-0117" target="_blank" >10.1515/psr-2018-0117</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Mechanistic role of plant-based bitter principles and bitterness prediction for natural product studies I: Database and methods

Popis výsledku v původním jazyce

This chapter discusses the rationale behind the bitter sensation elicited by chemical compounds, focusing on natural products. Emphasis has been placed on a brief presentation of BitterDB (the database of bitter compounds), along with available methods for the prediction of bitterness in compounds. The fundamental basis for explaining bitterness has been provided, based on the structural features of human bitter taste receptors and have been used to shed light on the mechanistic role of a few out of the 25 known human taste receptors to provide the foundation for understanding how bitter compounds interact with their receptors. Some case studies of ligand-based prediction models based on 2D fingerprints and 3D pharmacophores, along with machine learning methods have been provided. The chapter closes with an attempt to establish the relationship between bitterness and toxicity.

Název v anglickém jazyce

Mechanistic role of plant-based bitter principles and bitterness prediction for natural product studies I: Database and methods

Popis výsledku anglicky

This chapter discusses the rationale behind the bitter sensation elicited by chemical compounds, focusing on natural products. Emphasis has been placed on a brief presentation of BitterDB (the database of bitter compounds), along with available methods for the prediction of bitterness in compounds. The fundamental basis for explaining bitterness has been provided, based on the structural features of human bitter taste receptors and have been used to shed light on the mechanistic role of a few out of the 25 known human taste receptors to provide the foundation for understanding how bitter compounds interact with their receptors. Some case studies of ligand-based prediction models based on 2D fingerprints and 3D pharmacophores, along with machine learning methods have been provided. The chapter closes with an attempt to establish the relationship between bitterness and toxicity.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10611 - Plant sciences, botany

Projekt

<a href="/cs/project/EF16_027%2F0008351" target="_blank" >EF16_027/0008351: ChemJets UCT Prague</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Physical Sciences Reviews

ISSN

2365-6581

e-ISSN

2365-659X

Svazek periodika

4

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

11

Strana od-do

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Kód UT WoS článku

000472606200003

EID výsledku v databázi Scopus

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