This document summarizes different computational methods for protein structure prediction, including homology modeling, fold recognition, threading, and ab initio modeling. Homology modeling relies on identifying proteins with similar sequences and known structures. Fold recognition and threading can be used when there are no homologs, to identify proteins with the same overall fold but different sequences. Ab initio modeling uses physics-based modeling and protein fragments to predict structure from sequence alone, and has challenges due to the vast number of possible conformations.

1. Fold recognition and
ab initio protein
modeling
Michael Dolan
6/26/18 Source: Aza Toth

2. What if there is no homolog?

3. Computational methods for protein
structure prediction
• Homology (or “comparative”) modeling
used for proteins which have their homologous protein structures deposited in
the Protein Data Bank (PDB)
used to model those proteins which have the same fold as proteins of known
structures, but do not have homologous proteins with known structure
• Fold recognition / threading
• ab initio modeling
Uses the laws of physics along with protein fragments to construct a model using
the laws of physics (energy function)

4. Protein fold recognition
• Can be applied when homology modeling
methods provide no reliable prediction
• attempt to identify a model fold for a given
target sequence among the known folds even
if no sequence similarity can be detected

5. Protein Fold Recognition
Basic premise
• Similar sequence implies similar structure but
not all similar structures have similar
sequence
– structure is evolutionary more conserved than
sequence
– number of unique structural folds in nature is
fairly small

6. Structures conserve more than just
sequence….

7. SCOP: Structural Classification of Proteins

8. Similar structures can be found among
proteins with no sequence similarity
Chap. 11 Protein Structures: Published by Eleanore Bruce

9. 3.6 Å
5% ID
NK-lysin (1nkl) Bacteriocin (1e68)
Less protein folds compare to
sequence diversity

10. Protein Fold Recognition / Threading
Which of the known folds is likely to be
similar to the (unknown) fold of a new
protein when only its amino-acid sequence
is known?

11. Predicting Secondary Structure
From Primary Structure
TEAVDAATAEKVFKQYANDNGVDGEWTYDDATKTFTVTEK
TEAVDAWTVEKAFKTFANDNGVDGAWTVEKAFKTFTVTEK
Replace both sequences with an engineered peptide
Source: Minor and Kim. 1996. Nature 380:730-734
a -helix b-strand

12. Protein Threading
• Threading method defines the "fitness" of the
query from the structural environment of the
template structure.
• Sequences are fitted directly onto the backbone
coordinates of known protein structures
• Matching of sequences to backbone coordinates
is performed in 3D space, incorporating specific
pair interactions explicitly

13. Ab initio / de novo methods
• Build protein 3D structures from sequence
alone
– based on physical
principles
https://doi.org/10.1371/journal.pone.0032637

14. Protein intramolecular interactions
https://www.fastbleep.com/biology-notes/40/1175

15. Let’s pause and think about this
problem…
• For a protein of 200 residues and considering
only 3 backbone angles (F,Y, and W)…
…there are 3200 possibilities.
• There are estimated to be 1082 atoms in
universe.

16. Rosetta

17. Fragment-based, ab initio modeling
• Sections of a sequence are subjected to secondary structure prediction
• Assembled in 3D space, looking for lowest energy configurations

18. Fragment-based folding using Rosetta

19. ab initio modeling
Challenges:
– scoring function
– fast method for sampling conformations
Advantages:
– Can work for novel folds
– helps to understand the folding process
Disadvantages:
– applicable to short sequences only; monomers
– time consuming
– misleading results?

20. Hands on Exercises
Robetta: A web server for ab initio modeling
Rosetta: Command line suite of programs for ab
initio modeling
(see assoc tutorial)

21. Robetta: full-chain protein structure
prediction server
http://robetta.bakerlab.org

22. Rosetta analysis