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Data‐Driven Identification of Hydrogen Sulfide Scavengers
Author(s) -
Yang Chuntao,
Wang Yingying,
Marutani Eizo,
Ida Tomoaki,
Ni Xiang,
Xu Shi,
Chen Wei,
Zhang Hui,
Akaike Takaaki,
Ichinose Fumito,
Xian Ming
Publication year - 2019
Publication title -
angewandte chemie
Language(s) - English
Resource type - Journals
eISSN - 1521-3757
pISSN - 0044-8249
DOI - 10.1002/ange.201905580
Subject(s) - chemistry , hydrogen sulfide , combinatorial chemistry , azide , in vivo , molecule , sulfonyl , sulfide , computational biology , biochemistry , organic chemistry , biology , sulfur , microbiology and biotechnology , alkyl
Hydrogen sulfide (H 2 S) is an important signaling molecule whose up‐ and down‐regulation have specific biological consequences. Although significant advances in H 2 S up‐regulation, by the development of H 2 S donors, have been achieved in recent years, precise H 2 S down‐regulation is still challenging. The lack of potent/specific inhibitors for H 2 S‐producing enzymes contributes to this problem. We expect the development of H 2 S scavengers is an alternative approach to address this problem. Since chemical sensors and scavengers of H 2 S share the same criteria, we constructed a H 2 S sensor database, which summarizes key parameters of reported sensors. Data‐driven analysis led to the selection of 30 potential compounds. Further evaluation of these compounds identified a group of promising scavengers, based on the sulfonyl azide template. The efficiency of these scavengers in in vitro and in vivo experiments was demonstrated.