ISSNIP

Enterprise Grid Enabled Web Portal for Protein Structure Prediction

Investigators
Staff:

Raj Buyya, M. Palaniswmami;
Post Doctoral Research Fellow: Jayavardhana Gubbi, Chao Jin.

Student:
Collaborations

Michael Parker, SVIMR, Australia.

Description
Introduction: Proteins are of primary importance in normal functioning of a living organism. Understanding the way protein functions is arguably the most important aim of molecular biology.
Significance: There has been a consensus in the molecular biology community that the function of the protein depends on its three dimensional structure. Hence solving the three dimensional structure of a protein becomes a very important issue. The knowledge of the protein structure helps us in understanding the way they are involved in interaction with other molecules. This leads us to understand the way abnormal proteins (which are the cause for disease) function. The abnormal function is due to the change in the three dimensional structure of the protein. Efficient design of drugs (which is also a protein) is possible only by understanding the structure of abnormal proteins. Apart from efficient drug design, proteins help us in understanding the evolutionary relationships between proteins.
Applications: This research is based on using enterprise grid model which will help us to make the protein structure prediction algorithms developed by our group to be accessible universally.
Challenges: The development of computational methods in designing new drugs has improved the entire process in terms of quality of new drugs as well as time taken to generate new drugs. This is essentially due to structure based drug design which depends on the knowledge of three dimensional structure of diseased protein and the drug. Due to large improvement in computational methods for protein structure prediction, the time taken for rational drug design has dropped considerably.
Publication
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