Prediction of Potential Drug Targets From Ion Channels

Creative Bioarray is committed to providing clients with ion channel drug target prediction services by using a variety of experimental and computational tools. We provide existing and customized drug target discovery strategies to meet clients' specific research needs and accelerate the drug development process.

Background

The discovery and accurate positioning of drug targets is the key to the success of new drug development. Among known drug targets, ion channel proteins are a popular class of targets. The flow of ions through ion channels provides the basis for membrane excitability, signal transduction, and neurotransmission, so ion channel proteins play an irreplaceable role in the functions of the nervous system, cardiovascular and so on.

For target discovery, traditional biological methods not only require high scientific research costs but also are time-consuming. The method based on machine learning can process some big data conveniently and quickly, and applying it to the field of life science can quickly and efficiently analyze the biological significance of these data, which is of great help for mining potential drug targets.

Fig. 1 Drug target prediction performance based on leave-one-out cross validation. (Chen, 2010)

Prediction of Potential Drug Targets from Ion Channel Proteins

Our research team has made a lot of efforts in the study of drug targets. Currently, we have developed multiple experimental and computational tools to help our clients identify new drug targets.

• Prediction of potential drug targets from ion channels using classical support vector machine (SVM) method with a combination of three types of protein features, primary sequence, secondary structure, and subcellular localization.
  • Step 1. Prediction of ion channel target proteins based on genome-wide target protein signatures.
  • Step 2. Prediction of targets based on known ion channel target protein characteristics.
• Prediction of ion channel targets based on the analysis of sequence homology and domains of known drug targets.
• Prediction of ion channel targets based on side effect similarity.
• Prediction of drug targets based on protein domains.
• Prediction of drug targets based on ensemble learning.
  • Step 1. Investigate a variety of protein-encoding features that can transform protein sequences with distinct lengths into sequences with the same lengths.
  • Step 2. Screen feature subsets that distinguish between targets and non-targets through numerical experiments, and use ensemble learning to integrate the features to obtain prediction models.

Our Advantages

• Comprehensive drug development services
• High accuracy prediction
• Experienced researchers and cutting-edge technologies

Creative Bioarray has established long-term cooperation with many pharmaceutical companies and research institutes around the world in drug development and accumulated rich experience in the prediction of potential drug targets from ion channel proteins. Our dedicated drug target analysis team will customize the best strategy for you and quickly meet your specific needs at a competitive price. If you are interested in our scientific services, please contact us for more details.

Reference

1. Chen, X.; Yan, G. Y. NRWRH for drug target prediction[C]//The International Conference on Computational Systems Biology. 2010.