molecular modeling n primer design
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Bioinformatics is the field of science inwhich biology, computer science, andinformation technology merge into a singlediscipline. The ultimate goal of the field isto enable the discovery of new biologicalinsights and to create a global perspectivefrom which unifying principles in biologycan be discerned.
Molecular Modeling is one of theimportant area of Bioinformatics
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Computational programs generate molecular
data
geometries (bond lengths, bond angles, torsion
angles),energies (heat of formation, activation energy,
etc.),
electronic properties (moments, charges,
ionization potential,electron affinity),spectroscopic properties (vibrational modes,
chemical shifts)
bulk properties (volumes, surface areas,
diffusion, viscosity, etc.).
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Molecular modeling encompasses
theoretical methods and computational
techniques used to model or mimic the
behavior of different molecules.
The most common feature of molecular
modeling techniques is the atomistic level
description of the molecular systems
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The starting point for many studies is generally atwo dimensional drawing of a compound of interest.These diagrams can range from notebook or "back-of-the-envelope" sketches to electronically stored
connection tables in which one defines the types ofatoms in the molecule, their hybridization and howthey are bonded to each other.
Carbon dioxide, for example, would be defined asone SP2 oxygen atom (atom number 1) bonded to anSP carbon atom (atom number 2) with a doublebond which in turn, is bonded to a second SP2
oxygen atom with a double bond.
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atom # Atom Name Atom Type Bound to atoms
1 O 5 2
2 C 2 1, 3
3 O 5 2
Connection tables are easily stored and
searched electronically. However, they must betransformed into three dimensional
representations of chemical structure to study
chemical properties.
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The "mechanical" molecular model was developed out of
a need to describe molecular structures and properties in as
practical a manner as possible.
Molecular mechanics is a mathematical formalism which
attempts to reproduce molecular geometries, energies and
other features by adjusting bond lengths, bond angles and
torsion angles to equilibrium values that are dependent onthe hybridization of an atom and its bonding scheme.
Molecular Mechanics Background
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Epot is the total steric energy which is defined as the difference in energy between
a real molecule and an ideal molecule.
Ebnd, the energy resulting from deforming a bond length from its natural value, is
calculated using Hooke's equation for the deformation of a spring (E = 1/2 Kb(b -bo)
2 where Kb is the force constant for the bond, bo is the equilibrium bond length
and b is the current bond length).
Eang, the energy resulting from deforming a bond angle from its natural value, is
also calculated from Hooke's Law.
Etoris the energy which results from deforming the torsion or dihedral angle.
Eoop is the out-of-plane bending component of the steric energy.
Enb is the energy arising from non-bonded interactions
Eel is the energy arising from coulombic forces.
Energy Calculation
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An excellent approach to searching regions of conformational space,
it is not an exhaustive search. The active conformation of a molecule
can be missed as the dynamics simulation skips over the hills and
valleys of the potential energy surface. Since the active conformation
at a receptor may not always be the minimum energy structure(defined as the structure with the 3D geometry that places the
molecule at the lowest point on the potential energy hypersurface), it is
important to examine all potentially accessible conformations.
For small molecules with a limited number of freely rotating bonds,this can be easily accomplished by driving each torsion angle stepwise
over a 360 degree range.
As an example, a graph of the conformationally dependent energy
(shown along the Y-axis) of the molecule Butane.
molecular dynamics
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The number of conformations for a molecule (defined as the "non-identical
arrangements of the atoms in a molecule obtainable by rotation about one or
more single bonds
Number of conformers = (360/angle increment)(# rotatable bonds)
Butane Conformers
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Optimize molecular geometry and
calculate physical and electronic
properties.
An equally important aspect of
CAMD/CADD is the ability to display
these properties in a manner which
increases the chemist's ability to
interpret experimental findings andcorrelate these finding with structural
features.
Molecular surfaces play an important
role in these studies.
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Molecular ModelingStrategies
DirectDrugDesign
Indirect Drug
Design
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In the direct approach, the three-dimensional
features of the known receptor site are
determined from X-ray crystallography to design
a lead molecule. In direct design, the receptor site
geometry is known; the problem is to find a
molecule that satisfies some geometric
constraints and is also a good chemical match.
After finding good candidates according to these
criteria, a docking step with energy minimization
can be used to predict binding strength.
Direct drug design
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The indirect drug design approach
involves comparative analysis of
structural features of known active and
inactive molecules that are
complementary with a hypothetical
receptor site. If the site geometry is not
known, as is often the case, the designer
must base the design on other ligand
molecules that bind well to the site.
Indirect Drug Design
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SBDD is an iterative process, in whichmacromolecular crystallography has been thepredominate technique used to elucidate the three-dimensional structure of drug targets
Both nucleic acids and proteins are potential drugtargets, but the majority of such targets are proteins.
Proteins undergo considerable conformationalchange upon ligand binding, it is important to designdrugs based on the crystallographic structures ofprotein-ligand complexes, not the un ligandedstructure.
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I. Two case studies for sequence to structuremapping:
Small changes in protein sequence cause dramatic
difference in drug binding:COX inhibitors
Large changes in protein sequence still maintainsimilar structure: G protein coupled receptors
II. Protein Structure Prediction
III. Ligand Docking to Protein Structures
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Primary Sequence
MNGTEGPNFY VPFSNKTGVV RSPFEAPQYY LAEPWQFSML AAYMFLLIML GFPINFLTLY
VTVQHKKLRT PLNYILLNLA VADLFMVFGG FTTTLYTSLH GYFVFGPTGC NLEGFFATLG
GEIALWSLVV LAIERYVVVC KPMSNFRFGE NHAIMGVAFT WVMALACAAP PLVGWSRYIP
EGMQCSCGID YYTPHEETNN ESFVIYMFVV HFIIPLIVIF FCYGQLVFTV KEAAAQQQES
3D Structure
Folding
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First (if structure is known) or second (after structureprediction) step in a drug design project: find a leadstructure (=small molecule which binds to a giventarget)
docking problem - predicting the energetically mostfavorable complex between a protein and a putativedrug molecule
For a given protein structure, one can apply docking
algorithms to virtually search through the space
2 questions:1. what does the protein-ligand complex look like
2. what is the affinity with respect to other candidates?
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Find a set of compounds to start with- e.g. from inspecting known ligands for a protein (e.g.
substrate in an enzyme)
compounds from a screening experiment of a combinatoriallibrary (in which there is usually a molecular fragment that is
common between all molecules of the library, the core, andthe fragments attached to the core are R-groups)
compounds from a filtering experiment using other software
from varying other lead structures or known ligands
virtual screening using a fast docking algorithm (typicallyfrom a million molecules)
de novo design using fragments of compounds=> get several hundred to thousands of ligands to start with
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Rigid-body docking algorithms Protein and ligand are held fixed in conformational
space which reduces the problem to the search for therelative orientation fo the two molecules with lowest
energy.
All rigid-body docking methods have in common thatsuperposition of point sets is a fundamental sub-problem that has to be solved efficiently:
Superposition of point sets: minimize the RMSD
Flexible ligand docking algorithms most ligands have large conformational spaces with
several low energy states
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Ligand database Target Protein
Molecular docking
Ligand docked into proteins active site
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DOCKworks in 5 steps:
Step 1Step 1 Start with coordinates of target receptor
Step 2 Generate molecular surface for receptor
Step 3
Fill active site of receptor with spheres potential locations for ligand atoms
Step 4 Match sphere centers to ligand atoms
determines possible orientations for the ligand
Step 5 Find the top scoring orientation
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AutoDock
designed to dock flexible ligands into receptor
binding sites
Has a range of powerful optimization algorithms
RosettaDOCK
models physical forces
Creates a large number of decoys degeneracy after clustering is final criterion in
selection of decoys to output
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RANDOM START POSITIONRANDOM START POSITION
Creation of a decoy begins with a random orientation
of each partner and a translation of one partner along
the line of protein centers to create a glancing contactbetween the proteins
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LOWLOW--RESOLUTION MONTE CARLO SEARCHRESOLUTION MONTE CARLO SEARCH
Low-resolution representation: N,CE,C, O for the
backbone and a centroid for the side-chain One partner is translated and rotated around the
surface of the other through 500 Monte Carlo moveattempts
The score terms: A reward for contacting residues, apenalty for overlapping residues, an alignment score,residue environment and residue-residue interactions
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HIGHHIGH--RESOLUTION REFINEMENTRESOLUTION REFINEMENT
Explicit side-chains are added to the protein
backbones using a rotamer packing algorithm, thus
changing the energy surface An explicit minimization finds the nearest local
minimum accessible via rigid body translation and
rotation
Start and Finish positions are compared by the
Metropolis criterion
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Before each cycle, the
position of one protein is
perturbed by random
translations and by random
rotations
To simultaneously optimize
the side-chain
conformations and the rigid
body position, the side-chain packing and the
minimization operations are
repeated 50 times
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COMPUTATIONAL EFFICIENCY
1. The packing algorithm usually varies the
conformation of one residue at a time; rotamer
optimization is performed once every eight cycles
2. Periodically filter to detect and reject inferior decoys
without further refinement
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Download and install Arguslab in
windows
Load a PDB file, practice Arguslab tools
Follow the tutorial at
http://www.arguslab.com/tutorials/tutori
al_docking_1.htm
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Molecular Docking using Argus lab:
Ex : Benzamidine inhibitor docked into Beta Trypsin
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Create a binding site from bound ligand
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Setting docking
parameters
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Analyzing docking results
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Polypeptide builder.
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The computational molecular docking problem is
far from being solved.
There are two major bottle-necks:
1. The algorithms handle limited flexibility2. Need selective and efficient scoring functions
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Molecular Modeling Applications
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Molecular Modeling Applications
I. Molecular structures may be generated by a variety of
software. The 3D structures of molecules may be created by
several common building functions like make-bond, break- bond, fuse rings, delete-atom, add-atom-hydrogens, invest
chiral center, etc. Computer modeling allows chemists to build
dynamic models of compounds which in turn allows them tovisualize molecular geometry and demonstrate chemical
principles
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II. The most important area of the molecular modeling
concept is visualization of molecular structures and
interactions. The molecules are visualized in three
dimensions by various representations like connected
sticks, ball and stick models, space filling
representations and surface displays.
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IV. The 3D structures of many ligands (drug molecules)
that interact with the receptors may be known but the
structures of most receptors are not known. The interaction
of macromolecular receptors and of small drug molecules
is an essential step in many biological processes.
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Invented in 1982 (Cetus Corp)
Discovery of Taqpolymerase in 1985
Kary Mullis: Nobel Prize 1993Widely used method with wide application
Many variations of commercial kits
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Method for exponential amplification of DNA orRNA sequences
Basic requirements template DNA or RNA
2 oligonucleotide primers complementary to differentregions of the template
heat stable DNA polymerase
4 nucleotides and appropriate buffer
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Cycling ProgramStep 1: 94o C for 30
sec
Step 2: 94o C for 15
sec
Step 3: 55o C for 30
secStep 4: 72o C for 1.5
min
Step 5: Go to step 2
for 35 times
Step 6: 72o C for 10
minStep 7: 4o C forever
Step 8: END
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James D. Watson & Francis Crick, 1953, discovered thestructure of DNA
Alexander Todd et al, 1950s, made the first internucleotide bond
(cycle time: days)
H.G. Khoranaet al, 1960s, made the first oligonucleotide
phosphodiester (cycle time: hours)
R. Letsinger et al, 1965, synthesis on solid support led to the first
DNA synthesizer ever
Many researchers, 1970s, phosphotriester method
M. Matteuci & M. Caruthers, 1980s developed DNA synthesis on
inorganic support
S. Beaucage & M. Caruthers, 1981s, developed phosphoramiditechemistry
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Specificity
Specific for the intended
target sequence (avoid
nonspecific hybridization)
Stability
Form stable duplex with
template under PCR
conditions
Compatibility
Primers used as a pair shall
work under the same PCR
condition
Uniqueness
Length
Annealing Temperature
Primer Pair Matching
Internal Structure
Base Composition
Internal Stability
Characteristics of primers: Thoughts on primer design:
Melting Temperature
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A melting temperature (Tm) in the range
of ~52C to 65C
Absence of dimerization capability
Absence of significant hairpin formation
(>3 bp)
Lack of secondary priming sites
Low specific binding at the 3' end (ie.lower GC content to avoid mispriming)
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Primer length
GC%
Annealing
3 complementary between primers
G&C runs at the 3 end
Palindrome sequences
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Primer length has effects on uniqueness and
melting/annealing temperature. Roughly speaking, the longer
the primer, the more chance that its unique; the longer the
primer, the higher melting/annealing temperature.
Generally speaking, the length of primer has to be at least 15
bases to ensure uniqueness. Usually, we pick primers of 17-28
bases long. This range varies based on if you can find unique
primers with appropriate annealing temperature within this
range.
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Melting Temperature, Tm the temperature at which
half the DNA strands are single stranded and halfare
double-stranded.. Tm is characteristics of the DNA
composition; Higher G+C content DNA has a higher Tm
due to more H bonds.
Calculation
Shorter than 13: Tm= (wA+xT) * 2 + (yG+zC) * 4
Longer than 13: Tm= 64.9 +41*(yG+zC-16.4)/(wA+xT+yG+zC)
(Formulae are from http://www.basic.northwestern.edu/biotools/oligocalc.html)
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I
f primers ca
na
nnea
l to themselves, ora
nnea
l to ea
ch other ra
ther tha
nanneal to the template, the PCR efficiency will be decreased dramatically.
They shall be avoided.
owever, sometimes these r str ct res are harmless when the annealing
temperat re does not allow them to take form. For example, some dimers
or hairpins form at rC while d ring PCR cycle, the lowest temperat re
only drops to rC.
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Primers with stable 5 termini and unstable 3
termini give the best performance: reduces false
priming on unknown targets
Low 3 stability prevents formation of duplexes
that may initiate DNA synthesis: 5 end must also
pair in order to form a stable duplex
Optimal terminal (G ~ 8.5kcal/mol; excessivelow (G reduces priming efficiency
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1. Uniqueness: ensure correct priming site;
2. Length: 17-28 bases.This range varies;
3. Base composition: average (G+C) content around 50-60%; avoid long(A+T) and (G+C) rich region if possible;
4. Optimize base pairing: its critical that the stability at 5 end be high
and the stability at 3 end be relatively low to minimize false priming.
5. Melting Tm between 55-80 rC are preferred;
6. Assure that primers at a set have annealing Tm within 2 3 rC of
each other.
7. Minimize internal secondary structure: hairpins and dimmers shall be
avoided.
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Primer design is an artartwhen done by human beings, and a
far better done by machinesfar better done by machines.
Some primer design programs we use:
- Oligo: Life Science Software, standalone application
- GCG: Accelrys, ICBR maintains the server.
- Primer3: MIT, standalone / web application
http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi
- BioTools: BioTools, Inc. ICBR distributes the license.
- Others: GeneFisher, Primer!, Web Primer, NBI oligo program, etc.
Melting temperature calculation software:
- BioMath: http://www.promega.com/biomath/calc11.htm
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