Template choice principles

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Template choice
for comparative modeling


The most important step of comparative modelling is a carefully done multiple sequence alignment of the target sequence with a protein of known structure. However, you can't expect a useful model either, if you use an unsuitable template, and for many templates more than one coordinate file is available.

All homologues can contribute template information to your project!


 


 


 


 

Searching for templates

How to find a template
  • Keyword searches are possible, but unrealiable: there is no guarantee that the researchers who have deposited the structure have used the keyword you are thinking of, or that it is correctly spelled.
  • Sequence searches: BLAST and PSI-BLAST are the tools of first choice to find homologues structures. Try a BLAST search in the PDB subsection of the protein database first. If this is unsuccessful, do a PSI-BLAST search in "nr" and look for homologs that are flagged with the "known structure" icon.
  • Use CATH or SCOP. These hierarchical classifications of the entire PDB will contain domains that may serve as templates, if you know your protein's folding architecture. Sometimes protein families have diverged in sequence so far that alignments fail. A structural superposition of structures from a family may pinpoint key conserved residues that must be represented in the sequence alignment you use for your modelling procedure.


 


 

Evaluating Templates

Evaluation is based on an accurate alignment between target and template sequence.


 

Alignment

Hard and easy results
  • Since structural similarity correlates with sequence similarity, use the structure with the highest degree of % sequence identity (not alignment score) as a template. Easy modeling tasks are those where no indels have to be considered. Structural modeling of indels is always unreliable. Hard modeling tasks have significant indels or uncertain alignments over the length of the target. In selected cases you may consider using a template of high sequence identity to model the global fold, and then to import coordinates for a loop of the same length as your target from a more distantly related template. Whether such a loop will have the same conformation as your target protein depends on whether the loop length has been conserved from a shared ancestor, or whether it has changed, and then converged to your target sequence. If you have a phylogenetic tree available, you may be able to figure this out. Nevertheless, that template at least provides an example of a low-energy loop configuration of the correct length in the global context of the target protein.


 

Suitability

Assessing suitability

The model must be relevant to your protein's function! If you have a choice:

  • Choose orthologs fulfilling the Reciprocal Best Match' criterium over paralogues that may be functionally diverged;
  • Choose protein-ligand complexes over unliganded structures;
  • Choose structures in a functional state (bound inhibitor? heterooligomer? phosphorylated? proteolytic processing?) over free, unmodified structures;
  • Choose native sequences over mutated sequences (incl. His-tag, SeMet, non-physiological post-translational modifications);
  • Chose coordinate sets in which the regions of interest are well ordered over regions that are locally disordered and have high B-factors, or regions that are highly divergent in NMR model sets;
  • Choose structures where crystal packing contacts are distant from regions of interest over those where crystal packing may introduce conformational artefacts.
Assessing quality

Use the highest-quality structure available:

  • Use the structure with the best resolution (low values: 2.0 Å is better than 2.5 Å).
  • Treat NMR structures like crystal structures with a resolution (at best) worse than 2.5 Å
  • Well refined structures have R-values better than 10% of their nominal resolution (e.g. 2Å: R< 0.2).
  • R-free, and R-merge are additional quality metrics ... but are difficult to assess for the non-expert. Here too: lower is better.