Double water exclusion: how graph theory refines the long-standing biological O-ring hypothesis

Speaker:	Dr. Jinyan LI
		School of Computer Engineering
		Nanyang Technological University
		Singapore

Title:		"Double water exclusion: how graph theory refines
		 the long-standing biological O-ring hypothesis"

Date:		Monday, 8 March 2010

Time:		4:00pm - 5:00pm

Venue:		Lecture Theater F (near lifts 25/26) HKUST

Abstract:

The O-ring theory is an influential and long-standing biological
hypothesis characterizing the binding hot spots in protein interactions.
It states that a hot spot is made up of a small fraction of the residues
in a protein binding interface, but it contributes most to the binding
free energy. It also says that a hot spot is always surrounded by a ring
of energetically less important residues that forms an O-shape to occlude
bulk water molecules from the hot spot. As the organizational topology of
the ring-inside, energetically more important hot residues is uncertain
and not specified by this theory, we proposed a new hypothesis called
"double water exclusion" to refine this biological principle. In this
talk, I will present how this biological problem is translated into a
computational one, how graph theories and statistics are used to tackle
the problem, and what are my next steps. Some open questions will be also
addressed. For example, is the water exclusion degree related to the
evolution of protein binding behavior?

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Biography:

Jinyan Li received his PhD degree in computer science from the University
of Melbourne in 2001. He is an associate professor in the School of
Computer Engineering, Nanyang Technological University, Singapore. His
research is focused on protein structural bioinformatics, statistically
important discriminative patterns, interaction subgraphs, and
classification methods. Jinyan has published over 100 research articles.
One of his most interesting work was a cancer diagnosis technique for
childhood leukemia disease through the discovery of emerging patterns from
the gene expression data, and currently he is very interested in
infectious disease studies and water bioinformatics in collaboration with
a biological group from the Massachusetts Institute of Technology by
exploring graph theories and biological water exclusion principles. One of
his data mining articles is widely cited over 450 times, and another paper
on bioinformatics is cited over 1000 times, according to google scholar.