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

Nan Zhou¹, Jinchun Zhang, Ling Feng

¹School of Life Sciences & Key Laboratory of Bio-resources, Ministry of Education, Sichuan University, Chengdu 610064, China.

|October 15, 2013

Abstract:

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.

Insights

This study maps the human apoptotic protein interaction network, identifying novel interactions and providing a web tool for researchers. Understanding these interactions is crucial for tissue homeostasis and disease research.

Area of Science:

Molecular Biology
Systems Biology
Bioinformatics

Background:

Apoptosis, or programmed cell death, is vital for tissue homeostasis and eliminating malignant cells.
Dysregulation of apoptosis is implicated in cancer, developmental disorders, autoimmune diseases, and neurological conditions.
Systematic research into the molecular dynamics and protein interactions governing apoptosis is essential.

Purpose of the Study:

To integrate known protein interaction data and predict the global human apoptotic protein interaction network.
To identify novel interactions between apoptotic proteins and related pathways.
To develop a web-based platform for predicting and visualizing apoptotic protein interactions.

Main Methods:

Integration of protein interaction data from DIP, IntAct, MINT, HPRD, and BioGRID databases.
Application of a Naïve Bayes classifier for predicting protein interactions, validated using ROC curves (AUC = 0.797).
Construction and analysis of the global human apoptotic protein interaction network.

Main Results:

Confirmed known interactions involving caspases and the Bcl-2 family.
Discovered novel interactions: Bid with casein kinases (CSK21/22/2B, KC1A, KC1E); B2LA1 and B2CL2 with Bid, Bax, and Bak; caspase-8 with autophagic proteins (MLP3B, MLP3A, LRRk2).
Developed the IntApop web service for predicting and visualizing apoptotic protein interactions.

Conclusions:

The study provides a comprehensive map of human apoptotic protein interactions, revealing novel functional relationships.
The IntApop web service offers a valuable resource for researchers in apoptosis, systems biology, and translational medicine.
This work advances our understanding of apoptosis and its role in diseases like cancer, providing a foundation for future research and therapeutic strategies.

Read full analysis

Keywords:

Apoptosis Naïve Bayes classifier Prediction Protein interactions

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