Pharmacophore Modeling and Database Searching

Pharmacophore
Modeling and Database
Searching
Process
• Collect set of high-affinity ligands for target
(from literature)
• Analyze conformations of each (start from
least flexible)
• Superpose pharmacophore elements to
identify bioactive conformation
• Examine lower affinity ligands to identify
disallowed volume
Why > 1 Conformation?
Conformational Analysis
• Requires:
• a method to calculate (relative) energies
• an algorithm to explore conformational space
H 3C
CH 3 CH 3
CH 3
Energy
CH 3
CH 3
Computing Energies
Energies can be calculated at several levels of theory
• Ab Initio – PC Spartan
• Most theoretically rigorous
• Energies calculated from electronic structure
• Requires no experimental parameters
• Semi-Empirical – PC Spartan
• Simplifying assumptions made
• Experimental parameters compensate
• Molecular Mechanics – MOE and PC Spartan
• Electrons essentially ignored
• Many experimental parameters required
Molecular Mechanics
• Energy broken down into terms
• Bond stretching
• Angle bending
• Torsional potential
• Non-bonded interactions
• Van derWaals, electrostatic, dipolar interactions
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Force Fields
• The combination of mathematical formulae
and parameters used to represent the energy
of a chemical system
• Different forcefields are optimized for different
problems:
• MMFF94: optimized for small organic compounds
- wide structural variety
• AMBER94: optimized for proteins - often missing
parameters for other organics
• PEFSAC95: optimized for carbohydrates
Bond Stretching
• Approximated with a harmonic potential
• V = k s
( r - r 0
) 2
• Two parameters per pair of atom types
harmonic potential
Energy
}
Interatomic distance
Morse potential
huge errors at relatively large
interatomic distances
Torsional Potential
s=1
Typical of sp 3 -sp 3 bond
n=3
Typical of sp 2 -sp 2 bond
s=-1
n=2
0 60 120 180 240 300 360
• Eω = V n
(1 + s cos nω)
(Two--fold term added to compensate for non-equivalent minima)
Three parameters needed for each combination of atom types
Van derWaals
• Usually expressed as a Lennard-Jones potential
(6-12 shown):
12 6
⎡⎛σ
⎞ ⎛σ
⎞ ⎤
V VDW
= 4ε
⎢⎜
⎟ − ⎜ ⎟ ⎥
σ r 0
⎢⎣
⎝ r ⎠ ⎝ r ⎠ ⎥⎦
repulsive attractive
Energy
Interatomic distance
V VDW
r 0 = 2 -1/6 s
12
6
⎡⎛
r
⎤
0 ⎞ ⎛ r0
⎞
= ε ⎢⎜
⎟ − 2⎜
⎟ ⎥
⎢⎣
⎝ r ⎠ ⎝ r ⎠ ⎥⎦
Ionic Interactions
• Generally approximated using partial point
charges
q 1
r
q 2
q1q
=
Dr
V
2
Effective dielectric constant
Conformational Search
Algorithms
• Torsion angle driving
• Monte Carlo
• Artificial Intelligence
• Molecular Dynamics
• Simulated Annealing
• Poling
• Etc.
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Monte Carlo
• Uses a random kick of coordinates followed by
minimization to find new minima
• More effective on highly flexible molecules
• Not exhaustive -> heuristics used to define end point:
• if each of the lowest energy conformations has been found
~10 times, the search has probably found all the interesting
ones
• if duplicate conformations are found ~20 times in a row, the
interesting conformations have probably all been found
• (actual numbers to use depend on the flexibility of the
system and your interest in a nearly exhaustive search!)
• In MOE there are two methods that include this
• Compute -> Conformations -> Stochastic Search
• Compute -> Conformations -> Hybrid Monte Carlo
Exercise
• Build a structure for morphine and perform a
stochastic conformational search
• Use Window->Potential Control to activate the MMFF94
force field
• Use default conditions (your choice on output database
name) to run the search
• Analyze your results
• How many conformations?
• What energy range?
• How different are they (might try Edit->Interactive
Superpose)
Process
• Collect set of high-affinity ligands for target
(from literature)
• Analyze conformations of each (start from
least flexible)
• Superpose pharmacophore elements to
identify bioactive conformation
• Examine lower affinity ligands to identify
disallowed volume
Pharmacophore Element
Representations
• While a pharmacophore is defined based on ligand
structure, activity occurs due to an interaction with a
receptor
• Pharmacophore elements can be represented as:
• Ligand Points
• Site Points
Morphine Pharmacophore
Elements
• Choose a conformation of morphine from
your search as the ‘bioactive’ conformation
• What are the distances between potential
pharmacophore elements?
HO
O
N
Refining a Pharmacophore
• Most pharmacophore modeling cases do not
include a molecule as inflexible as morphine
• These cases require consideration of several
structures to identify a most likely bioactive
conformation for each
• Compute->Flexible Alignment can be used to
find superimpositions of several structures
based on types of pharmacophore element
HO
Morphine
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Exercise – Flexible Alignment
• Use flexible alignment to superimpose one of the
flexible structures below on your selected
conformation of morphine (fix morphine atoms using
Edit->Fix)
• Compute->Flexible Alignment can be used to find
superimpositions of several structures based on
types of pharmacophore element
H 2N CH C
CH 2
O
H
N
CH
H
O
C
H
N
CH
H
X=methionine or leucine
O
C
H
N
CH
CH 2
O
C
X
O
N
N
OCH 3
Sufentanil
S
Using a Pharmacophore
• Distances between pharmacophore elements
can be used as input to 3D database
searches
• Public 3D database searching available
through the National Cancer Institute (link on
course home page)
• Pharmacophore elements can be drawn
• Distance ranges can be specified
• Additional constraints (MW range, properties) can
be used to reduce number of potential hits
OH
Why Distance Ranges?
Accessible Conformations
1. 3D databases contain a limited set of
representative conformations, not every
accessible conformation
2. Queries defined by ligand points are overly
restrictive
OH
OH
N
OH
N
N
OH
Dopamine D2 agonist
that defines the 3D
pharmacophore
N
Ligand Point Restriction
Exercise
• Go to the NCI database
• Define a query using the morphine
pharmacophore (and any other limitations
you like)
• What do you find?
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Related Reading
• The Organic Chemistry of Drug Design and
Drug Action
• Chapter 2.2A
• Problems 2.4: 3
• Textbook of Drug Design and Discovery
• Chapter 4
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