Homology modeling
Dinesh Gupta
ICGEB, New Delhi
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Protein structure prediction
• Methods:
– Homology (comparative) modelling
– Threading
– Ab-initio
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Protein Homology modeling
• Homology modeling is an extrapolation of
protein structure for a target sequence
using the known 3D structure of similar
sequence as a template.
• Basis: proteins with similar sequences are
likely to assume same folding
• Certain proteins with as low as 25%
similarity have been observed to assume
same 3D structure
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The accuracy of modeling is proportional
to the similarity in primary sequences
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Steps…
• Given:
– A query sequence Q
– A database of known protein structures
• Find protein P such that P has high
sequence similarity to Q
• Return P’s structure as an approximation
to Q’s structure
• Energy minimization
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Sofware for homology molecular
modelling
• Freeware: available for all OS
– Downloadable
• Modeller (Sali, 1998)
• DeepView (SwissPDB viewer)
• WHATIF (Krieger et al. 2003)
– Web based:
• SWISS MODEL server (www.expasy.org/swissmod/SWISSMODEL.html)
• CPH model server
(http://www.cbs.dtu.dk/services/CPHmodels)
• SDSC1 server (http://cl.sdsc.edu/hm.html)
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Protein structure prediction
• Methods:
– Homology (comparative) modelling
– Threading
– Ab-initio
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Threading
• Structure prediction that picks up where
homology modelling leaves off.
• Recognize folds in proteins having no
similarity to known proteins structures
• Very approximate models
• Check by forcing a sequence of structure
into known folds checking the packing of
aa residues, including sides chains, in
each fold.
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2 kinds of threading
• Three dimensional threading
– Distance Based Method (DBM)
• Two dimensional threading
– Prediction Based Methods (PBM)
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Threading software
• EVA: http://cubic.bioc.columbia.edu/eva/
• SAMt99:
http://www.cse.ucsc.edu/research/compbio
/HMM-apps/T99-model-library-search.html
• 3DPSSM:
http://www.sbg.bio.ic.ac.uk/3dpssm
• FUGUE: http://tardis.nibio.go.jp/fugue/
• Metaservers:
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Protein structure prediction
• Methods:
– Homology (comparative) modelling
– Threading
– Ab-initio
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Ab initio structure prediction
• Still experimental
• ROSETTA (David Baker)
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Energy minimization (Molecular
Mechanics, MM)
• Energy minimization is an important part
of both empirical and predicted structures
• MM could be used to calculate large scale
conformational changes over long periods
of time, but currently computationally
infeasible.
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How does MM work?
• Three aspects:
– Functions that describe the forces acting on the
atoms
– Numerical integration methods, to calculate the
motion of the atoms due to the forces acting on them
– Long time propagation of the equations of motion
• Computational demands are intense
– Accuracy (small errors propagate!)
– Stability
– Lots of techniques for approximation (e.g. rigid
bodies) and handling artifacts (resonance).
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The Force Fields
• How do atoms stretch, vibrate, rotate, etc.?
• Must represent the constraints on atomic motion
(e.g. van der Waals, electrostatic, bonds, etc.)
• Must also represent solvation effects etc.
• Quantum solutions exist, but are too complex to
calculate for such large systems
• Empirical (approximate) energy functions must
be used. No single best function exists.
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Real energetics
• Steric (conformational) energy. Additive
combination of
– Bonded: stretching, bending, stretching and bending
– Non-bonded: Van der Waals, electrostatic and
“torsional”
• Minimum energy conformation minimizes these
energies
• Rosetta energy function is an empirical attempt
to capture most of this energy function without
having to calculate it fully.
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Bond length
• Spring-like term for energy based on
distance
Estr = ½ks,ij(rij -ro)2
where ks,ij is the stretching force constant
for the bond between i and j, rij is the
length, and ro is the equilibrium bond
length
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Bond bend
• Same basic idea for bending
Ebend = ½kb,ij(ij –o)2
where where kb,ij is the bending force constant,
ij is the instantaneous
bond angle, and o is
the equilibrium
bond angle
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Stretch-bend
• When a bond is bent, the two associated bond
lengths increase, with interaction term:
Estr-bend =½ksb,ijk(rij-ro)(ik - o)
where ksb,ijk is the stretch-bend force constant for
the bond between
atoms i and j with the
bend between atoms
i, j, and k.
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Van der Waals
• A non-bonded interaction capturing the
preferred distance between atoms
where A and B are constants depending
on the atoms. For two
hydrogen atoms,
A=70.4kCÅ6 and
B=6286kCÅ12
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Electrostatics
• If bonds in the molecule are polar, some atoms
will have partial electrostatic charges, which
attract if opposite and repel otherwise.
where Qi and Qj are the partial
atomic charges for i and j
separated by distance rij ,
 is the dielectric constant
of the solute, and k is a units
constant (k=2086 kcal/mol)
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Torsional energy
• Torsion is the energy needed to rotate about
bonds. Only relevant to single bonds, since
others are too stiff to rotate at all
Etor = ½ktor,1 (1 - cos ) + ½ktor,2 (1 - 2cos )
+ ½ktor,3 (1 - 3cos )
where  is the dihedral angle
around the bond, and ktor,1, ktor,2
and ktor,3 are constants for one-,
two- and three-fold barriers.
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energy of 3-fold torsional
barrier in ethane
Energy minimization
• Given some energy function and initial
conditions, we want to find the minimum
energy conformation.
• Optimization problem, various methods:
– Steepest descent
– Conjugate gradient descent
– Newton-Raphson
• Various programs: Charmm, Amber are
two most widely used (and packaged)
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Time steps
Need time steps of roughly 1/10 the period of the smallest time
scale of interest, or about a femtosecond (10-15s). A million
computational steps per nanosecond of simulation...
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Issues in Molecular Mechanics
• Solvation models: water & salt are very
important to molecular behaviour. Must model
as many water atoms as protein atoms.
• Initial conditions: velocity & position
• Equilibration: simulated heating and cooling
• Chaos: sensitivity to initial conditions, and
statistical characterization of states
• Computational issues (e.g. parallelization)
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Molecular Dynamics
• Molecules, especially proteins, are not static.
– Dynamics can be important to function
• Trajectories, not just minimum energy state.
– MM ignores kinetic energy, does only potential energy
– MD takes same force model, but calculates F=ma and
calculates velocities of all atoms (as well as positions)
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Docking
• Computation to assess binding affinity
• Looks for conformational and electrostatic "fit"
between proteins and other molecules e.g.
inhibitors
• Optimization again: what position and
orientation of the two molecules minimizes
energy?
• Large computations, since there are many
possible positions to check, and the energy for
each position may involve many atoms
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Virtual Screening
• Docking small ligands to proteins is a way to find
potential drugs. Industrially important
• A small region of interest (pharmacophore) can
be identified, reducing computation
• Empirical scoring functions are not universal
• Various search methods:
– Rigid provides score for whole ligand (accurate)
– Flexible breaks ligands into pieces and docks them
individually
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Docking example
Benzamidine binding to beta-Trypsin 3ptb,
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Macromolecular docking
• Docking of proteins to proteins or to DNA
• Important to understanding
macromolecular recognition, genetic
regulation, etc.
• Conceptually similar to small molecule
docking, but practically much more difficult
– Score function can't realistically compute
energies
– Use either shape complementarities alone or
some kind of mean field approximation
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Docking Resources
• AutoDock
http://www.scripps.edu/pub/olsonweb/doc/autodock/
• FlexX http://www.biosolveit.de/FlexX/ and
commercially at http://www.tripos.com
• Dock
http://www.cmpharm.ucsf.edu/kuntz/dock.html
• 3D-Dock http://www.bmm.icnet.uk/docking/
which uses an unusual “Fourier correlation”
method and is aimed at protein-protein
interactions
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Lab Exercise-1
Install:
• MDL chime
• RasMol
• SwissPDBviewer
• Cn3D
Explore few protein/DNA structures
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Lab exercise-2
• Download sequence file for S. cerevisiae endoplasmic
reticulum mannosidase
• Generate a homology model using SWISS-model server
http://www.expasy.ch/swissmod/
• Download the template structure from www.rcsb.org
• Compare the model and template structures
• Repeat the exercise for other protein sequences of your
choice
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