Subject: CCL:SUMM:Homology Modelling question

From: "Shoba.Ranganathan" <[email-masked]>
Date: Tue, 11 Jun 1996 10:01:04 +0000

I would to thank all CCLers who responded to my request.

Here's the summary for the "homology modelling" question (some
answers are from bionet.xtallography while repeats and signatures were
suppressed): 
> 
> I require references for the limits of homology 
> modelling, as well as the percentage of sequence 
> identity (in case I am unable to locate the reference). 
>
----------------------------------------------------------------------
From: [email-masked]

Here is my favourite for this question:

Sanders C and Schneider R. (1991) Database of Homology-Derived Protein
Structures and the Structural Meaning of Sequence Alignment. Porteins:
Struct., Funct., and Gen. 9, 56-68.

Best regards,
Herbert Treutlein
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: [email-masked]

  You might want to consider using the term "comparative modelling",
  as opposed
to "homology modelling".  The reason for this is that the minimum
sequence identity that is "required" for useful 3-D prediction and
modelling can be as low as zero percent (or some other statistically
insignificant similarity). Thus it is, in fact, possible to model the
structure of a protein based on the structure of an unrelated (or very
distantly related) protein.
  Check out the high quality structure prediction, which used a
combination of several state-of-the-art techniques, in:

->TI: THE PROTEIN FOLD OF THE VON-WILLEBRAND-FACTOR TYPE-A DOMAIN IS
      PREDICTED TO BE SIMILAR TO THE OPEN TWISTED BETA-SHEET FLANKED
      BY ALPHA-HELICES FOUND IN HUMAN RAS-P21
  AU: EDWARDS_YJK, PERKINS_SJ
  JN: FEBS LETTERS, 1995, Vol.358, No.3, pp.283-286

  -- Simon M. Brocklehurst

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: Aravind Mittur <[email-masked]>

Chris Sander and Gert Vriend have written some very good reviews and
articles on homology modeling over the last couple of years. You
should perhaps read the Sanderss' group home page at
http://www.embl-heidelberg.de.

The cut-off depends on a number of factors, including functional
validity. I can also recall an excellent review by Eisenhaber and
others in Critical Reviews in Biochemistry and Molecular Biology early
last year.

Aravind M.

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: [email-masked] (Oakley H. Crawford)

See S. Mosimann, R. Meleshko, and M. N. G. James, Proteins 23, No. 3,
p. 301 (1995), and other papers in that issue of Proteins.

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: [email-masked]

Our company, Molecular Applications Group (MAG), supports and markets
a homology modeling package based on the work of our founder, Michael
Levitt ["SegMod", J. Mol. Biol. 226, 507-533 (1992)].  It is a highly
automated procedure, yet remarkably accurate.  Our primary product,
Look, acts as a graphical front-end to SegMod, permitting the user to
focus on the most important part of the homology modeling process--the
sequence alignment between your unknown and the reference
structure--rather than the mechanics of building the homology model.

For more information, please visit the following page on our Web site:
        <http://www.mag.com/products/look/segmod.html>
In particular, please see MAG's validation study of SegMod:
        <http://www.mag.com/products/look/segmod-validation.html> in
which, for example, a homology model with an RMS error of 2.79 A for
Calpha atoms was produced from a single template structure with only
27% sequence identity.

Please contact me if you have further questions or would like to
receive more information.

Wally E. Reiher
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: Arne Elofsson <[email-masked]>

According to Andrej Sali (and my memory)
>50% identity, 90-95% of internal sidechain correclty predicted, rmsd
       >2 A
40-50% sequecnce identity 80% internal sidechain correclty predicted,
       rmsd 2.5 A
30-40% loops predicted wrongly, 75 % of internal sidechain not
       correctly predicted.

arne

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: [email-masked]

Jonathan Greer and colleagues have just written a chapter for Reviews
in Computational Chemistry. He can be contacted at:

[email-masked]

Yvonne Martin
(I do not have a reply from Jonathan Greer till date - Shoba)

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: [email-masked] (Dave Schuller)

I assume you mean for SUCCESSFUL homology modeling?  You can model
anything you want; whether it is useful or meaningful is another
question.

I could point out a couple attempts that failed (in my view) with
18-20% identity.  Some of the reasons for the failure:  1) despite the
overall identity numbers, there was no homology at all for one of the
regions modelled. 1b) This fact was obscured by incorrect sequence
alignments. 2) The modelling attempts may have been influenced by an
incomplete and incorrect crystal structure of a third homologous
protein.

Banci, Carloni & Savellini (1994) Biochemistry 33, 12356-12366.

Smith, Du & Loew (1995)  Nuclear Magnetic Resonanc of Paramagnetic
Macromolecules, Kluwer Academic publishers, the Netherlands, pp.
75-93.

naturally, the authors would probably prefer to dwell on the positive
aspects, such as correct placement of some or all of the active site
residues, and not on the fact that some residues were mis-placed by
tens of Angstroms.

Dave Schuller

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
From: [email-masked] (C.S.RAMAN)

Homology modelling has been done with as little as 30% sequence
identity to a known structural protein.  Generally, one finds reports
where there was ~40-50% sequence identity and 70% similarity via
conservative replacements.

-raman

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
===========================================================
Dr. Shoba RANGANATHAN                     
Computational Mol Biology & Drug Design Group
Div. of Biochemistry & Mol. Biology 
John Curtin School of Medical Research                 
Australian National University          Tel: +616-279-8301                           
Canberra ACT 0200                       Fax: +616-249-0415
Australia.              email:[email-masked]
===========(http://biocomp.anu.edu.au/~sra/)==============