Systems Level Understanding Of Macromolecular Interactions. Any Suggestions??

Question

[Pals]

Hi all,

I have special interest on macromolecular modeling and drug design. These days I have been dealing with protein-ligand interactions. However, I have planned to find some projects that involve large scale study on protein-protein interaction, most preferably protein-RNA (poly nucleotide) interaction as this is quite challenging as well as interesting area. On the other hand, research on systems biology and highthroughput bioinformatics seem to be speeding up. I have therefore thought to base my research (on macromolecular interactions) on systems level with what I have learned from structural bioinformatics. I would like to get a general overview of how the study on Protein-RNA interactions can be incorporated into systems biology. As this sort of study involves post-translational modifications, how complicated would be the biological networks? If we won't be able to make reliable networks, how about proceeding towards making prediction programs? As I do not have strong programming background, how can I make a start? What kind of algorithms will be needed? I would be glad to get suggestions.

Thanking you in Advance!!

[Michael]

I think the scope of the question is ok for biostar but it needs soe clarification: what do you mean by 'systems level research' that is not clear to me. Further, would you mind making more straight forward question? I'd advise to try to pinpoint something concrete, especially rephrase the last sentence. Despite your two '??' I do not see a question yet.

[Pals]

Thank you for the comment. I am interested in Systems biology but I have comparatively very less knowledge on Systems biology but enough background on structural bioinformatics. And I wanted to get some suggestions how I could proceed.

[Fred Fleche]

To start with Systems Biology my reading suggestion is the following with a lot of resources inside : http://www.amazon.com/Introduction-Systems-Biology-Sangdun-Choi/dp/1588297063

Answer 1

[Chris Evelo]

This question relates to a lot of things indeed.

Macromolecular interactions are studied a lot and our understanding of how gene products work together is the basis of what we know about biological functionality as it is for instance present in regulatory or signaling pathways. And when it is about using this best known well structured knowledge about macromolecular interactions you will probably want to use pathway tools. There are a lot of questions on Biostar about these.

But you are right that the experimental finding of a protein-protein or a protein-nucleotide sequence by itself offers interesting information. Many databases exist for that type of information, for instance [?]IntAct[?] for protein protein interactions and [?]Jaspar[?] for protein nucleotide motif interactions. But there are really many many more, including some specific for protein RNA interactions. You will often want experimentally validated interactions but prediction is useful to know what needs to be validated.

You can try to combine interaction data from different sources. You will often want to start by taking a well known core, an existing pathway for instance, and extend from that using other data sources about validated or predicted interactions and to combine that with experimental data (for instance about co-expression or epigenetic regulation or just locations where proteins are found.). A good tool to do that is [?]Cytoscape[?]. And if you want to do network analysis often you will definitely want to learn how to use that.

Your specific structural biology background is of course very important to improve the predictions and you will want to evaluate the increased power of your predictions using approaches like I mentioned in the previous paragraph.

In fact these predictions are going to be a lot more important in an era where genetic variations can be easily measured. Because using structural biology you cannot only predict macromolecular interactions you can also evaluate how genetic changes would affect the macromolecules and thus the interactions. That really will be the core field where bioinformatics (or if you want integrative systems biology) has to develop over the next 10 years or so. Estimate how genetic variations affect transcription factor binding motifs, or protein binding domains... The questions go on and on. And a lot of it will need to be experimentally validated.

You might also want to check out [?]this page[?] with a recent webcast and a interesting overview on a Nature poster provided by Agilent.

I hope this helps a bit. Because you could easily write a book about it.

[Pals]

Thanks a lot for such a detailed and simplified information.