2. ProInt Finder to Search Protein Interactions Shwe S. Lin Mentor: Matteo Pellegrini, UCLA

3. Outlines  Project overview  Purpose  Background  My part  Algorithms  Tool used  Examples  Acknowledgments  References

4. Project Overview  To develop a protein-protein interaction database and an interactive web-based interface to search for protein interactions from the database

5. Purpose of the Project  To study protein-protein interactions Example: p53-MDM2 interactions  To predict protein functions which may be inferred from analyzing protein interactions Example: protein A interacts with 5 cell cycle proteins and we therefore infer that it is a cell cycle protein

6. Importance of Studying Protein Interactions Example:  Essential for cell communications which result in activation or inactivation of biological responses Protein MDM2 inactivates p53’s function as a tumor suppressor EPO interacts with the EPO receptor to trigger growth of erythrocytes

7. Traditional Methods for Studying Protein Functions Sequence alignment techniques Protein’s 3-D structure

8. Limitations of Traditional Methods  Yield functional information only on experimentally characterized homologous proteins  Detect protein’s biochemical function only; not biological process

9. Approach to Address Limitations  Develop protein interaction databases Example: DIP, MINT, BIND etc.  Implement methods for function prediction Example: guilt-by-association

10. My Part  Develop web application (ProInt Finder) to utilize the database for studying protein interactions Django: Python Web framework Database: Automated collections of data by text mining of web

11. Algorithm (Input)  Accept query: gene name or gene id of interest Example - Gene name: p53 Gene ID: 7157

12. Algorithm (Search)  Search for gene_ids from the database gene table actors acted by

13. Algorithm (Output)  Return: gene_1_id interacts with gene_2_id  Result: List of protein pairs that are experimentally identified to interact with each other pro_ A >> activates pro_B pro_E phosphorylates >> pro_A >> acetylates pro_C pro_H binds to >> >> methylates pro_D pro_I activates >> >> interacts with pro_E pro_K regulates >>

14. Tool Used: Django Python web framework to build Web applications Provides Model-View-Controller (MVC) approach to programming Database layer: Models or data models Controller layer: View or control logic View layer: Templates or user interface

15. Each model is a Python class Contains fields and behaviors of the stored data Each model maps to a single database table Database Layer: Models Gene A Model in Django Gene ID Gene Name Taxonomy ID from django.db import models class Gene(models.Model): gene_id = models.IntegerField (primary_key=True) long_name = models.TextField( ) symbol = models.TextField( ) tax_id = models.ForeignKey( Species ) class Meta: db_table = 'protInt_gene' ordering = ['symbol'] Fields/ class attributes

16. View Layer: Templates ProInt Finder A text file that contains variables and tags Variables: Get replaced with values when the template is evaluated Tags: Control the logic of the template Templates for each of the web pages for ProInt Finder index.html results.html search.html

17. Control Layer Takes user input from search.html template Defines how to process the data Returns results to results.html template search.html User input Controller (View) results.html Protein interactions

18. Home Page This is a link which leads to the search page. These are links to other protein interaction databases.

19. Search page

20. Result page User Input Description of the protein Query protein interacts with different protein Proteins interacts with query protein

21. More on Result

22. Web Links Click on the link

23. Acknowledgements  Dr. Matteo Pellegrini  Shawn Cokus  Joseph Kim and Cory Tobin  Dr. Sandra Sharp and Dr. Wendie Johnston  SoCalBSI  NIH, NSF, and LAOC

24. References http://www.djangoproject.com/

25. Questions?Questions?