TY - JOUR
T1 - PTID
T2 - An integrated web resource and computational tool for agrochemical discovery
AU - Gong, Jiayu
AU - Liu, Xiaofeng
AU - Cao, Xianwen
AU - Diao, Yanyan
AU - Gao, Daqi
AU - Li, Honglin
AU - Qian, Xuhong
PY - 2013/1/15
Y1 - 2013/1/15
N2 - Although in silico drug discovery approaches are crucial for the development of pharmaceuticals, their potential advantages in agrochemical industry have not been realized. The challenge for computer-aided methods in agrochemical arena is a lack of sufficient information for both pesticides and their targets. Therefore, it is important to establish such knowledge repertoire that contains comprehensive pesticides' profiles, which include physicochemical properties, environmental fates, toxicities and mode of actions. Here, we present an integrated platform called Pesticide-Target interaction database (PTID), which comprises a total of 1347 pesticides with rich annotation of ecotoxicological and toxicological data as well as 13 738 interactions of pesticide-target and 4245 protein terms via text mining. Additionally, through the integration of ChemMapper, an in-house computational approach to polypharmacology, PTID can be used as a computational platform to identify pesticides targets and design novel agrochemical products.
AB - Although in silico drug discovery approaches are crucial for the development of pharmaceuticals, their potential advantages in agrochemical industry have not been realized. The challenge for computer-aided methods in agrochemical arena is a lack of sufficient information for both pesticides and their targets. Therefore, it is important to establish such knowledge repertoire that contains comprehensive pesticides' profiles, which include physicochemical properties, environmental fates, toxicities and mode of actions. Here, we present an integrated platform called Pesticide-Target interaction database (PTID), which comprises a total of 1347 pesticides with rich annotation of ecotoxicological and toxicological data as well as 13 738 interactions of pesticide-target and 4245 protein terms via text mining. Additionally, through the integration of ChemMapper, an in-house computational approach to polypharmacology, PTID can be used as a computational platform to identify pesticides targets and design novel agrochemical products.
UR - https://www.scopus.com/pages/publications/84872539526
U2 - 10.1093/bioinformatics/bts651
DO - 10.1093/bioinformatics/bts651
M3 - 文章
C2 - 23162083
AN - SCOPUS:84872539526
SN - 1367-4803
VL - 29
SP - 292
EP - 294
JO - Bioinformatics
JF - Bioinformatics
IS - 2
ER -