Download Protein Structure Prediction not a trivial matter

Protein Structure Prediction
not a trivial matter
Strict relation between protein function and
structure
Gap between known sequences and
known tertiary structures is constantly
increasing
There is a need for automatic methods
General methodology able to solve the
problem has not yet been devised
BMC Bioinformatics 2005, 6(Suppl 4):S3
Protein Structure Prediction
not a trivial matter
Protein structure prediction is a very
difficult task
Why?
Protein Structure Prediction
not a trivial matter
Complex interactions exist between intramolecular atoms and between the protein
and the surrounding environment.
Number of interactions to track increases
exponentially with molecule size
The number of possible structures that
proteins may possess is extremely large
Protein Structure Prediction
not a trivial matter
The physical basis of protein structural
stability is not fully understood
The primary sequence may not fully
specify the tertiary structure (chaperones
have the ability to induce proteins to fold in
specific ways)
Protein Structure Prediction
not a trivial matter
Direct simulation of protein folding via
methods such as molecular dynamics is
not generally reliable for both practical and
theoretical reasons
Distributed computing projects are tackling
such simulation difficulties
Protein Structure Prediction
not a trivial matter
Distributed computing projects:
– Folding@home (Stanford University's
Chemistry Department )
– Predictor@home (Scripps Research Institute )
– Human Proteome Folding Project (part of
World Community Grid run by IBM)
Protein Structure Prediction
not a trivial matter
Goal of protein structure prediction is to
determine the 3D structure of proteins
from their amino acid sequence
Some approaches:
– Comparative Protein Modeling: uses
previously solved structures as starting points
Protein Structure Prediction
not a trivial matter
Comparative Protein Modeling: 2 methods
– homology modeling
– protein threading
Protein threading:
– scans the amino acid sequence of an unknown
structure against a database of solved structures
– a scoring function is used to assess the compatibility
of the unknown sequence (target sequence) to the
known structure (template)
Protein Structure Prediction
not a trivial matter
Homology Modeling
– Facilitated by the fact that 3D structure of
proteins from the same family is more
conserved than their primary sequences
– Example: human hemoglobin and
leghemoglobin (hemoglobin in legumes)
If proteins are similar at the sequence
level then structural similarity can usually
be assumed
Protein Structure Prediction
not a trivial matter
Predicting structure from scratch
– De novo structure prediction (or ab initio
structure prediction)
– Requires vast computational resources
– Uses stochastic methods to search possible
solutions
– Finding the structure with the lowest free
energy is the key element of this approach
Protein Structure Prediction
not a trivial matter
Distributed computing
– Folding@home
– Predictor@home
– Human Proteome Folding Project
Employs the unused CPU cycles of
personal computers worldwide to analyze
scientific data
Protein Structure Prediction
not a trivial matter
Computational simulations of model
proteins
– most proteins are too large for current
technology to simulate folding on an atom by
atom basis
– lattice proteins: highly simplified computer
models of proteins, amino acid sequence
behaves like a single functional unit (a bead)