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ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support.
Fu, Li; Shi, Shaohua; Yi, Jiacai; Wang, Ningning; He, Yuanhang; Wu, Zhenxing; Peng, Jinfu; Deng, Youchao; Wang, Wenxuan; Wu, Chengkun; Lyu, Aiping; Zeng, Xiangxiang; Zhao, Wentao; Hou, Tingjun; Cao, Dongsheng.
Afiliación
  • Fu L; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
  • Shi S; School of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong SAR, 999077, P.R. China.
  • Yi J; School of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.
  • Wang N; Xiangya Hospital of Central South University, Changsha, Hunan 410008, P.R. China.
  • He Y; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
  • Wu Z; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China.
  • Peng J; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
  • Deng Y; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
  • Wang W; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
  • Wu C; School of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.
  • Lyu A; School of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong SAR, 999077, P.R. China.
  • Zeng X; Department of Computer Science, Hunan University, Changsha, Hunan 410082, P.R. China.
  • Zhao W; School of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, P.R. China.
  • Hou T; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China.
  • Cao D; Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, P.R. China.
Nucleic Acids Res ; 52(W1): W422-W431, 2024 Jul 05.
Article en En | MEDLINE | ID: mdl-38572755
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Internet / Descubrimiento de Drogas Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Internet / Descubrimiento de Drogas Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article