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An integrated web-based platform for molecular descriptor and fingerprint computation. ChemDes provides more than 3,679 molecular descriptors that are divided into 61 logical blocks. In addition, it provides 59 types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints.

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2 user reviews

2 user reviews

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changfulu

A good platform that can be used to calculate different types of molecular descriptors and fingerprints. So far it is the most comprehensive tool.

Zhijiang Yao's avatar image Zhijiang Yao's country flag

Zhijiang Yao

It's a useful web server.

ChemDes forum

No open topic.

ChemDes classification

ChemDes specifications

Software type:
Toolkit
Restrictions to use:
None
License:
CC Attribution-NonCommercial-ShareAlike
Version:
15.11.11
Requirements:
Modern internet browser supporting HTML5 and JavaScript
Interface:
Web user interface
Programming languages:
Java, Javascript, Python
Computer skills:
Basic
Stability:
Stable

Publications

  • (Dong et al., 2015) ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation. Journal of Cheminformatics.
    PMID: 26664458

ChemDes support

Maintainer

Credits

Institution(s)

School of Pharmaceutical Sciences, Central South University, Changsha, Hunan People's Republic of China; Department of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, Houston, USA; Xiangya Hospital, Central South University, Changsha, Hunan People's Republic of China; College of Chemistry and Chemical Engineering, Central South University, Changsha, People's Republic of China; Institute of Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR People's Republic of China

Funding source(s)

This work is financially supported by grants from the Project of Innovationdriven Plan in Central South University, the National Natural Science Founda tion of China (Grants No. 81402853), and the Postdoctoral Science Foundation of Central South University, the Chinese Postdoctoral Science Foundation (2014T70794, 2014M562142).

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