homology modeling and threading modeling

1. Prepared By – Archita Srivastava
M.Phram (Student)
Department Of Pharmacology
United Institue Of Pharmacy.
COMPUTATIONAL PREDICTICTION
OF PRROTEIN STRUCTURE:
THREADING & HOMOLOGY
MODELING METHOD

2. INTRODUCTION
 proteins fold into unique three-dimensional structures that
are closely related to their biological functions.
 Malfunctions of proteins are often the cause of fatal
diseases, thus understanding the structures of proteins and
their related functions in various biological mechanisms are
important subjects of studies because of the close
relationship between the structure and the function of a
protein, determining the three-dimensional native state
structure of a protein is very important.
 X-ray crystallography and NMR spectroscopy have served
as major experimental tools for the protein structure
determination .

3.  Protein structure prediction methods can be
classified into three types depending on the
homologous structures available from the existing
structural data base, and the degree of the
structural information incorporate.
Homology
modeling
Threading method
Ab– initio structure
prediction

4. HOMOLOGY MODELING
METHOD
 It is also known as, comparative modeling of
protein refers to construct "target” protein from its
amino acid sequence and an experimental three-
dimensional structure of a related homologous
protein.
 When a target protein of unknown structure has
structural homolog in the structure data base, the
structure of the target protein can be modeled by
using the homologous structure as a template

5.  For this, first the target protein sequence needs to be
aligned against the template protein sequence whose
structure is already experimentally determined.
 Homology modeling has been so far the most
successful method for protein structure prediction

6.  Limited to structure of template.
 Cannot study conformational changes
Limitation

7. Threading modeling and fold
recognition
 predicts the structural fold of unknown protein
sequences by fitting the sequence into a structural
database and selecting the best fitting fold.
 we can identify structurally similar proteins even
without detectable sequence similarity.
profile based
method
pairwise
energy based
method

8. Pairwise energy based
method (threading)
profile based method (fold
recognition)
 Searched for a
structural fold database
to find the best
matching structural fold
using energy based
criteria.
 Using dynamic
programming and
heuristic approaches.
 Calculate energy for
raw model.
 Lowest energy fold that
correspond to the
structurally a group of
 A profile is constructed for
related protein structures.
 Generated by
superimposition of the
structures to expose
corresponding residues.
 Secondary structure
type,polarity,hydrophobicit
y.
 The protein fold to be
predicted does not exist in
the fold library,method will