molecular modeling n primer design

8/8/2019 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


secStep 4: 72o C for 1.5

min

Step 5: Go to step 2

for 35 times


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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molecular modeling n primer design

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