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A structure-similarity-based software for the cardiovascular toxicity prediction of traditional chinese medicine.
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MedLine Citation:
PMID:  22359446     Owner:  NLM     Status:  In-Data-Review    
Although natural medicines are generally considered to be safer than synthetic medicines, some reports on toxicity of many herb drugs, for example Traditional Chinese Medicine (TCM), attract more and more common public attention recently. The reasons for these cardiovascular toxic effects are not always satisfactory. Not all these clinical symptoms can be observed regularly. Cardiovascular toxicity concern is one of the hindrances for TCM to enter international markets. Therefore, we create web-based software for people to evaluate TCM cardiovascular toxicity. The software, TCM Cardiovascular Toxicity Prediction (TCMCardioTox), is based on structure similarity search algorithm ( When a user enter a TCM name, the system interprets the name as a number of active component structures, and computes the structure similarities of the components against a number of known toxiphores. If one of the similarity is greater than a given similarity threshold, the TCM will be reported as an alert TCM for medical uses.
Feng Lu; Qiong Gu; Ruibo Wu; Jun Xu
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Publication Detail:
Type:  Journal Article     Date:  2012-01-20
Journal Detail:
Title:  Bioinformation     Volume:  8     ISSN:  0973-2063     ISO Abbreviation:  Bioinformation     Publication Date:  2012  
Date Detail:
Created Date:  2012-02-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101258255     Medline TA:  Bioinformation     Country:  Singapore    
Other Details:
Languages:  eng     Pagination:  110-3     Citation Subset:  -    
Research Center for Drug Discovery & Institute of Human Virology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China.
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Journal Information
Journal ID (nlm-ta): Bioinformation
Journal ID (publisher-id): Bioinformation
ISSN: 0973-2063
Publisher: Biomedical Informatics
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© 2012 Biomedical Informatics
Received Day: 22 Month: 12 Year: 2011
Accepted Day: 07 Month: 1 Year: 2012
collection publication date: Year: 2012
Electronic publication date: Day: 20 Month: 1 Year: 2012
Volume: 8 Issue: 2
First Page: 110 Last Page: 113
ID: 3282267
PubMed Id: 22359446
Publisher Id: 97320630008110

A Structure-Similarity-Based Software for the Cardiovascular Toxicity Prediction of Traditional Chinese Medicine
Feng Lu
Qiong Gu
Ruibo Wu
Jun Xu*
Research Center for Drug Discovery & Institute of Human Virology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China
*Jun Xu:


TCM are usually used in the form of an aqueous decoction. An herb soup has many chemical components which are not necessarily well understood. A single purified TCM compound isolated from a TCM can be either too toxic or without therapeutic efficacy [1]. The toxicities of a number of TCM have been reported in many reports [29]. However, it is impossible to experimentally measure toxicities for all TCM due to the costs. Developing in silico approach to estimate the cardiovascular toxicity of a TCM is an only practical solution for pushing a TCM to international markets.

Principle for the cardiovascular toxicity prediction of TCM

TCMCardioTox is a web based program implemented in and C# on a Microsoft server. The client program of TCMCardioTox is an Internet browser, such as, Internet Explorer (IE), with the installation of Java Run Environment. TCMCardioTox is actually a web-based knowledge-based system, which collects all the chemical structures that have been identified as human cardiovascular toxins. The main principle for the cardiovascular toxicity prediction is that if one of the chemical components in a TCM has the structural similarity against one of the known cardiovascular toxins in the database of TCMCardioTox system, the TCM will be alerted for cardiovascular toxicity.

TCMCardioTox consists of three components: (1) TCM cardiovascular adverse reactions reported in literatures; (2) TCM and corresponding known chemical structures; (3) chemical structure similarity algorithm. The chemical structure data and cardiovascular toxicity data are stored in a Microsoft Access Database. The chemical structure data are saved in the form of SD format.

When TCMCardioTox receives a TCM query, it will translate the TCM name into a set of chemical structures known as its compositions. These structures will be sent to a software module which checks them against a set of known cardiovascular toxins by substructure matching. At least one of the structures is matched; the TCM will be reported as potential a cardiovascular toxin. Otherwise, these structures will be sent to structural similarity algorithm to calculate structure similarities between the TCM chemical structures and the known cardiovascular toxic structures in the TCM CardioTox knowledge base. If one of the structure similarities is greater than a given threshold (such as, 80%), the TCM will be reported for cardiovascular toxicity. If a TCM is reported for cardiovascular toxicity, TCMCardioTox will reported the reasoning details in a spreadsheet, such as, the referenced structures, literatures, and experimental descriptions (if it is available) etc. However, if the spreadsheet is not displayed, it means that the TCM is not found being cardiovascular toxic.

Features Functions

The principle of predicting cardiovascular toxicity in TCMCardioTox is to figure out if a TCM contains compounds that are structurally similar to known cardiovascular toxic molecules or contains key toxic substructures. The more cardio-toxic molecules existing in a TCM, the TCM will be more potentially cardiovascular toxic.

When users retrieve a TCM in TCMCardioTox, similarity search will be done in a few seconds. The results depend on the similarity threshold. Usually, the threshold can be set to 85%. Higher similarity threshold will result in fewer hits (the number of cardiovascular toxicity hits means more risky). If a user wants to see more possible hits, he/she can lower the similarity threshold. The detailed principle is articulated in (Figure 1).

User Interface

TCM CardioTox is a web based system, which can be accessed through an internet browser at A query for TCMCardioTox can be a string for a TCM name, a compound structure drawing, or a SDF file for a number of chemical structures that are in a TCM herb as active components.

For example, Gambirplant stem is a TCM herb. TCMCardioTox predicts this herb that has cardiovascular toxicity for arrhythmia, hypotension and even carcinogenicity. Animal model experiments showed that this herb could cause arrhythmia. Some TCM cardiovascular adverse effects [29] testing results are listed in Table 1.


Current version of TCMCardioTox predicts cardiovascular toxicity based only structure similarity to toxins; this is a ligand based prediction. The advantage of this approach is simple and fast. The disadvantage is that it cannot explain the mechanism of actions.

The correct predictions rely on the coverage of the knowledge base in the system and the structure similarity algorithm. TCMCardioTox allows an administrative user to expand the knowledge base. But, the similarity algorithm is not changeable at this time. Currently, the structure similarity algorithm is based upon a simple structural fragment comparison using Tanimoto schem. In the future, three dimensional structure similarities can be implemented for alternative solutions.

In order to reach more precise prediction, the target structure based models are necessary. This requires the knowledge of mechanism of actions. The structure-based models demands for high performance computing, therefore, the new version of TCMCardioTox will need parallel computing technology, such as CUDA-based GPU technology.


FN1Citation:Lu et al, Bioinformation 8(2): 110-113 (2012)

This work was funded in part of the major scientific and technological special project by the Ministry of Science and Technology of China (2009DFA31530, 2010ZX09102-305), Guangdong Recruitment Program of Creative Research Groups, the Fundamental Research Funds for the Central Universities, the National Natural Science Foundation of China (No.81001372, 81173470). The editors are appreciated for their valuable comments and continuously encouragement.

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