The Rough Guide to Evolutionary Landscapes

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The Rough Guide to Evolutionary Landscapes Ben
Blackburne
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Examining Molecular Evolution

• Help us to understand how proteins work
• Proteins have been designed by evolution
• Protein folding and design
• Drug resistance, cancer, pesticide resistance...
• Help us to understand origins of life
• Need to see the bigger picture

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Examining Molecular Evolution

• How has the course of evolution affected the
  nature of proteins?
• What do existing sequences tell us about how they
  evolved?
• What are the limits of evolution?
• Evolutionary techniques used to explore other
  complex problems

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What is a Protein?

• Polymer of amino acids
• 20 monomer types
• Large number of possible proteins
• Protein 100 amino acids long -gt 20100 possible
  sequences
• Estimate of number of particles in the universe
  1088

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What is a Protein?

• Folds to a single native structure
• Levinthal paradox
• Protein 150 amino acids long -gt 10300
  conformations
• Global free energy minimum(Anfinsen)
• Performs a task determined by sequence and
  structure

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What is an Evolutionary Landscape?

• Wright (1933)
• Each sequence is connected to those a single
  point mutation away
• Evolution must cross a set of connected, viable
  intermediates
• adaptive
• moving to greater fitness
• neutral
• drifting randomly between sequences of equal
  fitness
• Ignores recombination

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The aim of this work

• Problem is intractably complicated
• Produce a lower resolution picture of proteins
• From this determine characteristics of
  evolutionary landscapes
• A tool for examining unanswered questions in
  protein science

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Modeling Proteins

• Hydrophobicity - driving force for folding
• Ligand binding
• Native Structure

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Lattice Models

• Restricted to lattice
• Shifted-HP model
• H-H interaction-2
• H-P/P-P interaction1

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Lattices

• Previous work has used the square lattice
• Two-dimensional
• 4 coordinate
• Currently we employ the diamond lattice
• Three-dimensional
• 4 coordinate
• This talk will focus on the diamond lattice

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Calculations

• Find every possible walk on the lattice for
  length n
• From each walk we can compute a contact map
• Each sequence can have an energy computed for
  each contact map
• Contact maps important for consideration of
  landscapes and designability

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Structure Space
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Sequence Space
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Families

• Find all pairs of viable sequences connected by
  single point mutations
• Link these pairs up to form families of viable
  sequences
• These families are our evolutionary landscapes

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Family Size and Chain Length
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Smoothness and Ruggedness
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86 Member Family
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Superfunnels

• Sequences can be ordered around their prototype
  sequence, with the greatest number of mutations
• Stability decreases with mutational distance
• Forms a funnel structure

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151-Member Family
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Examining Designability

• Definition of designability of a structure
• How many sequences possess this structure as
  their native state?
• Proteins structures are generally highly
  designable, but why?
• Are all foldable protein structures designable?
• Is high designability a product of evolution?

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What Makes a Designable Structure?

• Can we estimate designability by examining other
  characteristics of a structure?
• We examine contact maps with respect to
  designability
• Choose starting maps for structures of different
  designability
• Count number of contact maps for each Hamming
  distance from a starting map

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Examining Designability
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Conclusions

• Developed a model that allows us to examine
  questions about protein structure, function and
  evolution
• Examined the nature of evolutionary landscapes
• Increasing length -gtbigger, less rugged landscapes

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Conclusions

• There is a structure to landscapes
• Hub nodes
• Superfunnels
• Could be exploited in directed evolution
  experiments?
• Examined the causes of designability
• If verified in real proteins, may allow the
  design of structures by finding isolated contact
  maps

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Acknowledgments

• Jonathan Hirst
• Everyone in Computational Chemistry at Nottingham