Gevorg Grigoryan, PhD PROTEINS AS MATRICES. Background: Cells  Nano-Machines  Cells are tiny machines:  sense environment, respond, make decisions.

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Presentation transcript:

Gevorg Grigoryan, PhD PROTEINS AS MATRICES

Background: Cells  Nano-Machines  Cells are tiny machines:  sense environment, respond, make decisions  move, search for food (example)example  synthesize chemicals  make copies of themselves  Cellular macromolecules:  e.g. proteins  workhorses of the cell  responsible for many of these tasks

Background: Proteins  Primary structure:  chains of amino acids  20 amino acids: aka “residues” different in side-chain polar/hydrophobic acidic/basic large/small

Background: Protein Structure  Amino-acid sequence defines the full molecular structure of the protein and ultimately its function: …AKWLMENI… function folding

Background: Protein Structure  Secondary structure:  common local structural motifs  -helices  -sheets

Background: Protein Structure  Tertiary and Quaternary structure:

Nowadays, much more data…  Protein Data Bank (PDB):  – available to anyone for free  as of Jan 25, 2011 at 4 PM there are 70,813 Structures

Protein Structural Universe

 Questions about the Universe of Protein Structure:  What is the universe? Where are the building blocks?  Are there functions specific to certain fragments?  Can we design new structure/functions from building blocks?  Need:  convenient representation of structure  efficient search and classification methods

Representation: Distance Maps  A good representation of structure is key:

Search

Search Method  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method: branch and bound  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method: branch and bound  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method: branch and bound  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method: branch and bound  Mapping of Distances for the Characterization of Topology (MaDCaT)

Search Method: Result  Mapping of Distances for the Characterization of Topology (MaDCaT)

Conclusions/Future  Distance maps are a feasible way of representing and classifying protein structure  Searches for tertiary structural elements, with multiple fragments are possible  Future questions:  given any structure, decompose it into common blocks  splice common fragments together to engineer new structure  at some point efficiency is an issue, need better search approaches