Skip to main content



Networking in Protein Interaction Helps Disease Curing

http://lpm.hms.harvard.edu/palaver/sites/default/files/DrHiroshiTanaka.pdf

http://www.accessscience.com/content.aspx?id=YB051650

I recently read about how networks can be applied in biological fields, rather than in social contexts (such as friendship networks which we’ve already talked a lot about). I would like to talk about how networks can help in discovering new medicine and curing disease. This is actually related to the material of graph theory very early of the class.

The certain network I want to discuss about is called the protein interaction network (PIN). As we talked about in class, the basics of graphs are nodes and edges. In the PIN, nodes are proteins, and two nodes are linked by an edge if these two proteins interact with each other. The reason why we are interested in protein networks is that certain interaction between proteins can affect fitness of cells and cause diseases. And by studying PIN, we would be able to develop drugs acting on certain proteins changing their biophysical activities to cure the diseases.

The protein interaction data from yeast two-hybrid and other technologies showed that “98% are connected into a single network,” which means a giant component actually exists in the protein network. However, some proteins are heavily interconnected, while some are lightly interconnected. Based on how many other proteins one protein is connected to, we categorize these interactive proteins into three classes: First, high degree proteins are proteins that have many open and available nodes to interact with proteins. Second, intermediate proteins have an average amount of available nodes for protein interaction. And lastly, there is low degree protein, which means there are limited or a certain number of open nodes for interaction.

With this network, we are now able to answer why cancers are lethal to human bodies. Cancer targeted proteins are usually high degree proteins with extensive and massive networks that can make complicated interactions with other proteins. This high level of disorder in the many available nodes can, by chance, potentially lead to unfavorable interactions. These unfavorable protein interactions in the body can turn a healthy protein to a malignant protein by a cellular mechanism, and eventually lead to cancers.

By studying the connectivity between proteins, people decide on which protein the drug should actually deal with. And one piece of important information people can gain from the protein interaction network model is how severe the side effects of the drugs would be. Upon close examination of the pharmaceutical drugs that patients intake, we see that they are mostly low degree proteins. This indicates that the drug are designed to interact with a select few proteins and create small and formatted network. In other words, drugs acted on low degree proteins are more likely to cause less side effects.

In conclusion, using graphs and networks are actually very useful in biological study. Studying the connectivity of proteins in protein interaction network is actually of great use to disease curing and medicine development.

 

Smileyface

Comments

Leave a Reply

Blogging Calendar

September 2012
M T W T F S S
 12
3456789
10111213141516
17181920212223
24252627282930

Archives