TY - JOUR
T1 - ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support
AU - Fu, Li
AU - Shi, Shaohua
AU - Yi, Jiacai
AU - Wang, Ningning
AU - He, Yuanhang
AU - Wu, Zhenxing
AU - Peng, Jinfu
AU - Deng, Youchao
AU - Wang, Wenxuan
AU - Wu, Chengkun
AU - Lyu, Aiping
AU - Zeng, Xiangxiang
AU - Zhao, Wentao
AU - Hou, Tingjun
AU - Cao, Dongsheng
N1 - National Key Research and Development Program of China [2021YFF1201400]; National Natural Science Foundation of China [22173118, 22220102001]; Hunan Provincial Science Fund for Distinguished Young Scholars [2021JJ10068]; Science and Technology Innovation Program of Hunan Province [2021RC4011]; Natural Science Foundation of Hunan Province [2022JJ80104]; 2020 Guangdong Provincial Science and Technology Innovation Strategy Special Fund [2020B1212030006, Guangdong-Hong Kong-Macau Joint Lab]. Funding for open access charge: HKBU Strategic Development Fund project [SDF19-0402-P02].
© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.
PY - 2024/7/5
Y1 - 2024/7/5
N2 - ADMETlab 3.0 is the second updated version of the web server that provides a comprehensive and efficient platform for evaluating ADMET-related parameters as well as physicochemical properties and medicinal chemistry characteristics involved in the drug discovery process. This new release addresses the limitations of the previous version and offers broader coverage, improved performance, API functionality, and decision support. For supporting data and endpoints, this version includes 119 features, an increase of 31 compared to the previous version. The updated number of entries is 1.5 times larger than the previous version with over 400 000 entries. ADMETlab 3.0 incorporates a multi-task DMPNN architecture coupled with molecular descriptors, a method that not only guaranteed calculation speed for each endpoint simultaneously, but also achieved a superior performance in terms of accuracy and robustness. In addition, an API has been introduced to meet the growing demand for programmatic access to large amounts of data in ADMETlab 3.0. Moreover, this version includes uncertainty estimates in the prediction results, aiding in the confident selection of candidate compounds for further studies and experiments. ADMETlab 3.0 is publicly for access without the need for registration at: https://admetlab3.scbdd.com.
AB - ADMETlab 3.0 is the second updated version of the web server that provides a comprehensive and efficient platform for evaluating ADMET-related parameters as well as physicochemical properties and medicinal chemistry characteristics involved in the drug discovery process. This new release addresses the limitations of the previous version and offers broader coverage, improved performance, API functionality, and decision support. For supporting data and endpoints, this version includes 119 features, an increase of 31 compared to the previous version. The updated number of entries is 1.5 times larger than the previous version with over 400 000 entries. ADMETlab 3.0 incorporates a multi-task DMPNN architecture coupled with molecular descriptors, a method that not only guaranteed calculation speed for each endpoint simultaneously, but also achieved a superior performance in terms of accuracy and robustness. In addition, an API has been introduced to meet the growing demand for programmatic access to large amounts of data in ADMETlab 3.0. Moreover, this version includes uncertainty estimates in the prediction results, aiding in the confident selection of candidate compounds for further studies and experiments. ADMETlab 3.0 is publicly for access without the need for registration at: https://admetlab3.scbdd.com.
UR - https://academic.oup.com/nar/article/52/W1/W422/7640525?login=true
UR - http://www.scopus.com/inward/record.url?scp=85198001837&partnerID=8YFLogxK
U2 - 10.1093/nar/gkae236
DO - 10.1093/nar/gkae236
M3 - Journal article
C2 - 38572755
SN - 0305-1048
VL - 52
SP - W422-W431
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - W1
ER -