Gevorg Grigoryan, PhD PROTEINS AS MATRICES. Background: Cells Nano-Machines Cells are tiny...
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Transcript of Gevorg Grigoryan, PhD PROTEINS AS MATRICES. Background: Cells Nano-Machines Cells are tiny...
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Gevorg Grigoryan, PhD
PROTEINS AS MATRICES
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Background: Cells Nano-Machines Cells are tiny machines:
sense environment, respond, make decisions move, search for food (example) synthesize chemicals make copies of themselves
Cellular macromolecules: e.g. proteins workhorses of the cell responsible for many of these tasks
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Background: Proteins
Primary structure: chains of amino acids 20 amino acids:
aka “residues” different in side-chain polar/hydrophobic acidic/basic large/small
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Background: Protein Structure Amino-acid sequence defines the full
molecular structure of the protein and ultimately its function:
…AKWLMENI… function
folding
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Background: Protein Structure Secondary structure:
common local structural motifs
-helices -sheets
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Background: Protein Structure Tertiary and Quaternary structure:
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Nowadays, much more data… Protein Data Bank (PDB):
www.pdb.org – available to anyone for free as of Jan 25, 2011 at 4 PM there are 70,813
Structures
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Protein Structural Universe
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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
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Representation: Distance Maps A good representation of structure is
key:
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Search
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Search Method
Mapping of Distances for the Characterization of Topology (MaDCaT)
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Search Method
Mapping of Distances for the Characterization of Topology (MaDCaT)
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Search Method
Mapping of Distances for the Characterization of Topology (MaDCaT)
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Search Method: branch and bound Mapping of Distances for the
Characterization of Topology (MaDCaT)
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Search Method: branch and bound Mapping of Distances for the
Characterization of Topology (MaDCaT)
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Search Method: branch and bound Mapping of Distances for the
Characterization of Topology (MaDCaT)
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Search Method: branch and bound Mapping of Distances for the
Characterization of Topology (MaDCaT)
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Search Method: Result
Mapping of Distances for the Characterization of Topology (MaDCaT)
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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