Advanced structure prediction

14 important questions on Advanced structure prediction

What types can you have for template free modelling?

Constraint based (structural information)
Ab initio (knowledge based energies)
both go into fragment based model constructrion

What are template finding strategies (2 types)?

  • Homology detection
    • sequence search: BLAST
    • profile search: PSI-BLAST / HMMer
    • profile-profile search: FFAS03/COMPASS/ HHpred
  • Fold recognition
    • structure profile -sequence search: Fugue
    • Threading: THREADER, RAPTOR
    • meta-servers (+ insignificant scores)

Just as you looked at propensities to be buried or exposed, you can also create entire substitution tables for buried and exposed residues. What differences would you expect?

Eg salt bridges higly conserved when buried (one positive needs compensating charge)

And charged ones more conserved on outside
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Explain what Rosetta is, and to which category it belongs.

  • Ab initio prediction
  • “Knowledge based”“ab initio”protein structure prediction
  • Usage of existing databases of protein structures ( so ab initio not really suitable term)
  • use if no suitable template exists

How does Rosetta work?

  • PDB is used
  • a fragment library is constructed
  • so small protein fragments, small structure elements
  • all possible elements and transitions included
  • target sequence is also split up and tried to match with fragment
  • can give multiple options, so monte carlo is used
  • Fragments are assembled and multiple models are created, minimizing energy
  • --> decoys
  • from all decoys, you select the one that looks best like protein structure and matches what you know of the sequence the best

Explain ROSETTA fragment recognition.

See slide.

Explain ROSETTA fragment assembly.

Monte Carlo is used.

  • Now we have a many fragments, at each sequence position, with many possibilities to combine them:
  • We use Monte Carlo (MC) to search through different combinations.
  • Good combinations are those that give a low energy .Each MC run will give you a different model, since it is a stochastic algorithm.
    • done by looking at phi/psi angles
  • Such models are called decoys.

What is considered in the ROSETTA energy function?

Slide.

ROSETTA monte carlo: when are moves accepted?

  • If it lowers the energy function
  • If random number < Boltzman factor


(if move accepted then the model is accepted).

What is done for refinement in ROSETTA?

Small improvements of structure.
Now atomistic force field is used and only small changes allowed.

How are decoys scored?

  • Protein like features (detailed energy function)
  • Clusters of similar structures are more native like
    • cf. entropy

What do you want regarding decoy selection?

That the decoy that you select (best score) is closest to the real structure. Look at C-alfa RMSD.

So benchmarking: you want to see: lowest rosetta energy = lowest C-alfa RMSD. But it doensn't look like that!

How can the energy function be helped to function properly?

Give some information on which residues should be close together in space (contact map).

What is the idea of co-evolution?

If one residue substitutes into one, a paired one should as well. --> metagenomics. Changes at the same time can be observed here. Gives an idea of which residues are close in space --> contact map based on co-evolution. Increases rosetta score

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