IntApop: a web service for predicting apoptotic protein interactions in humans

Nan Zhou, Jinchun Zhang, Ling Feng, Bangmin Lu, Zijie Wang, Rong Sun, Chuanfang Wu, Jinku Bao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Apoptosis, a type of cell death, is necessary for maintaining tissue homeostasis and removing malignant cells. Interrupted apoptosis process contributes to carcinogenesis, developmental defects, autoimmune diseases and neurological disorders. Due to the complexity of the process, the molecular dynamics and relative interactions of individual proteins responsible for the activation or inhibition of apoptosis should be researched systematically. In this study, we integrate known protein interactions from databases DIP, IntAct, MINT, HPRD and BioGRID by Naïve Bayes classifier. The receiver operation characteristic (ROC) curve with the area under the ROC curve (AUC) of 0.797 indicates it has a good performance in prediction. Then, we predict the global human apoptotic protein interactions network. Within it, we not only identify the already known interactions of caspases (caspase-8/-10, caspase-9, caspase-3/-6/-7) and Bcl-2 family, but also reveal that Bid can interact with casein kinases (CSK21/22/2B, KC1A, KC1E); both of B2LA1 and B2CL2 can interact with Bid, Bax and Bak; caspase-8 interacts with autophagic proteins (MLP3B, MLP3A and LRRk2). Consequently, we make an initial step to develop the web service IntApop that provides an appropriate platform for apoptosis researchers, systems biologists and translational clinician scientists to predict apoptotic protein interactions in human. In addition, the interaction network can be visualized online, making it a widely applicable systems biology tool for apoptosis and cancer researchers.

Original languageEnglish
Pages (from-to)238-244
Number of pages7
Issue number3
Publication statusPublished - 2013
Externally publishedYes


  • apoptosis
  • Naïve Bayes classifier
  • protein interactions
  • prediction


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