decribe about rational drug design and methods

1. Praveen kumar.s
M.Pharm 2nd semester
Department of phramacology
PSG college of pharmacy.

2. The explosive development of computer technology to
calculate the molecular properties have increasingly made it
possible to use computer techniques to aid the drug
discovery process. the use of computer techniques in this
context is often called computer aided drug design(CADD),a
more appropriate name is computer aided ligand design
(CALD).
If the 3D structure of the target enzyme or receptor is
avaliable from X-ray crystallography ,preferentally with
cocrystallized ligand so that the binding site and binding
mode of the ligand is known ,it is feasible to study the
biomacromolecule –ligand in a direct way by interactive
computer graphics techniques and computational chemistry.

3. In this way a detailed knowledge of the interaction s
between the ligand and the enzyme/ receptor may be
obtained .
New candidate ligands may be docked into binding
site in order to study if the new structure can interact with
receptor in an optimal way. this procedure is known as
structure based ligand design.
If a set of active ligand molecule is known for the
macromolecule target but little or no structural information
exists for target,ligand based computational method can be
employed.

4.  In the absence of an experimentally determined 3D
structure for the receptor ,ligand design may be
performed by the use of a pharmacophore model
based on the analysis and comparison of molecular
properties and receptor binding data for known
receptor ligands.

5.  Nineteenth century organic chemists developing organic dyes introduced
the concept of chromophore for those parts of a molecule which are
responsible for its colour.
 In analogy ,paul ehrlich in the early 1900s ,introduced the term
pharmacophore to describe those parts of molecule which are responsible
for its biological activity.
 The idea behind these concepts come from the common observattion that
variation of some parts of the molecular structure of acompound trastically
influence the activity of a target receptor ,variations of other parts only
cause minor activity changes.
 A pharmacophore element Is traditionally is defined as an atom or group of
an atoms commmon for active compounds with respect to the receptor .and
essentrial for the acrtivity of compounds.
 Thus ,a 3D PHARMACOPHORE consists of a specific 3D arrangements of
pharmacophore elements .
 The pharmacophore concept has been used for long time in medicinal
chemistry in a topological sense (2D),however the use of computer
techniques has enormously facilitated topographical (3D)use of the concept.

6.  The basic principles of the development of a 3D-
pharmacophore model are illustrated in figure.
 On basis of conformational analysis of a set of active
molecule with pharmacophore elements A,B,C, a
conformations of each molecule is selected for which the
pharmacophore elements of the molecules overlap in space.
 The selected conformations are the putative bioactive
conformations of the molecules and the overlapping
pharmacophore elements and Spatial positions make up the
3D-pharmacophore.

8.  Step 1:
A set of high-affinity ligands for the target receptor is
collected and pharmacophore elements are selected. The
molecules in the set should have as diverse structural
frameworks as possible . the selected compounds should have
as few torsional degrees of freedom as possible. The receptor
binding data for the selected compounds. Obtained by
radioligand Binding assay,it should be high quality and
preferably from the same laboratory.

9.  Step 2:
An exhaustive conformational analysis is performed for each com
pound in the set in order to identify low-energy conformations for
each active molecule.
 Step 3:
Molecular superimposition techniques are used to identify low-
energy conformations of each molecule in the set, conformations for
which the selected pharmacophore elements superimpose.The aim
of this step is to identify the bioactive conformation of each
molecule and a common 3D-pharmaco phore for all high-affinity
compounds.
 Step4:
When a common 3D-pharmacophore for all high-affinity compounds
have been identified, inactive or low-affinity compounds which fit the
3D-pharmacophore in a low-energy conformation may be used to
explore the dimensions of the receptor cavity and to identify
receptor-excluded and receptor-essential volumes.

10.  The selection of pharmacophore elements is generally based
on experimental observations about parts (atoms,functional
groups)of a set of active molecules which are common for
these molecule and essential for the activity.
 Pharmacophore elements used in the development of 3D-
pharmacophore models are most often atoms or functional
groups which may interact with receptor binding sites via
hydrogen bonds,electrostatic forces or van der waals forces.
 Thus,heteroatoms such as oxygen and nitrogens and polar
functional groups such as carboxylic acids,amides and hydroxyl
groups are commonly found in pharmacophore elements.
 Drug molecule s frequently include aromatic ring systems.such
ring systems strongly interact with,for instance, aromatic side-
chains of the receptor or hydrophobic region they are very
often essential for the activity and therefore selected as
pharmacophore elements .

11.  If we consider a hydroxyl group as a pharmacophore
element,the important properties of this
functionalgroup in connection with its binding to the
receptor are its hydrogen bond donating and
accepting properties.

12.  A) does not specify any particular properties of the
hydroxyl group and pharmacophore element merely
requires that hydroxyl group is present at a particular
location in 3D –space in all active compounds.
 In b)&c) represent hydrogen bond accepting and
donating properties.the use of the oxygen or the
hydrogen atom asa ligand point implies that the
corresponding atoms should superimpose in space in
all active compounds.
 In d)&e)is a great advance in 3D-pharmacophore
development.the dashed line between the site point
and the ligand functional group represents a hydrogen
bond interaction with receptor site and the site point
itself represents interacting part of the receptor.

13. (a) The amino acid arginine with site points describing
possible optimal hydrogen bonding interactions,(b) arginine
bound to the LAO transport protein.

14.  In a)shows the amino acid arginine including site
points constructed.these site points describe possible
(optimal) hydrogen bond interaction s between
arginine and a receptor.the experimental structure of
the complex between arginine and the amino acid
transport protein LAO (lysine, arginine, ornithine-
binding protein)in b).

15.  As an alternative to (and extension of) the
representations of pharmacophores elements by ligand
points or site points, as described above, molecules may
be analyzed in terms of ensembles of explicit molecular
properties as hydrogen bond donors and acceptors,
hydrophobic areas, charged groups etc.
 A computer-program which analyzes molecules in this
way is CATALYST. Predefined properties are hydrogen-
bond acceptor, hydrogenbond donor, hydrophobic
(aliphatic or aromatic), negative or positive charge,
negatively or positively ionizable, and ring aromatic.
 In order to allow for variations in the geometry of the
interaction between a molecule and its receptor, distance
variation as well as angle variation is taken into account
in this approach.

16.  CATALYST may be employed to generate a pharmacophore in a manual
or in an automatic mode.
 In the manual mode, a compound with a high biological activity in a
proposed bioactive conformation is used and the user manually assign
properties (pharmacophore elements) to the molecule.
 In order to generate a pharmacophore model by using CATALYST in an
automatic model , a set of compounds with measured biological
activities is required. In the order of 20 compounds with activities
covering 4–6 orders of magnitude is recommended for this approach.
 For each molecule, a set of conformations representing the available
conformational space of the molecule is generated by the software.
 During the subsequent generation of the pharmacophore model, all
conformations and relevant properties of the functional groups are being
considered.
 The automatic procedure includes a QSAR calculation
 The software returns the ten best models in terms of fit of the
compounds to the model and the ability of the model to account for the
biological activities of the compounds.

17. Thermodynamic considerations:
 The great majority of drug molecules are flexible, which means
that they through rotations about bonds and/or inversions about
atomic centers may adopt a large number of conformations,
giving the molecule a correspondingly large number of different
3Dshapes.
 In the pharmacophore concept, this means that a ligand in
general may exhibit a large number of possible spatial
relationships between its pharmacophore elements.
 The pharmacophore hypothesis implies that for an active
molecule, one of these conformations is optimally
complementary to the receptor binding site and that the ligand,
when bound to the receptor is characterized by a specific
molecular conformation.

20.  The bioactive conformation is not necessarily the lowest energy conformation
of themolecule in solution, in the crystal or in the gas phase.
 Thus, experimental data on structures and conformational equilibria alone are
of limited use in attempts to identify the bioactive conformation.
 A computational approach is required and the entire conformational space
must be investigated.
 There are two groups of methods which may be used for the calculation of
conformational properties of molecules: (i) quantum chemical methods; and
(ii)molecular mechanics or force field methods.
 In the quantum chemical methods (anapproximation of) the Schrödinger
equation is solved, treating the molecule as a collection of positively charged
nuclei and negatively charged electrons moving under the influence of
Coulombic potentials.
 A hierarchy of quantum chemical methods at different levels of approximation
are being used in computational chemistry.
 In the ab initio methods, all electrons are included in the calculations,
whereas in the semi-empirical methods only the outer (valence) electrons are
explicitly included in the calculations and many terms are not calculated but
fitted to experimental data.

21.  Molecular mechanics is a method for the calculation of
molecular structures,conformational energies and other
molecular properties using concepts from classical
mechanics.
 A molecule is considered as a collection of atoms held
together by classical forces.
 These forces are described by potential energy functions of
structural features like bond lengths, bond angles, torsional
(dihedral) angles, etc.
 The energy (E) of the molecule is calculated as a sum of
terms as in equation,

23.  A 3D-pharmacophore model is characterized by a particular 3D-
arrangement of
pharmacophore elements.
 Active (high affinity) ligands are able to assume a low-energy
conformation in which the pharmacophore elements are positioned at
closely similar relative positions in space as those of the 3D-
pharmacophore model.
 During the development of a pharmacophore model, molecular super-
imposition techniques are used to investigate similarities and
differences between the accessible conformations of different
molecules with respect to the spatial positions of their pharmacophore
elements.
 When a 3D-pharmacophore model has been developed, molecular
superimpositions are used to investigate if new molecules fit the model.
 The most commonly used molecular superimposition method is the rigid-
body least squares superimposition of pharmacophore elements
represented as ligand points or site points.
 The root mean square deviation (rms) between selected points in the
test molecule and the corresponding points in the reference molecule is
minimized by displacing and rotating the test molecule as a rigid body.
 The rms value of the resulting least-squares fit is given by equation

26.  An example of this effect of the solvent, compound (4.13) binds to
the enzyme thermolysin with a Ki-value of 9.1 nM. X-ray
crystallography of the ligand-enzyme complex shows that the NH
group indicated by an arrow interacts with a carbonyl oxygen of
the enzyme binding site via a hydrogen bond.
 compound (4.14) binds equally well to the enzyme (Ki=10.6nM) in
spite of the fact that the CH2 group in (4.14),
 Replacing the NH group in (4.13), cannot form a hydrogen bond to
the enzyme.
 Computer simulations of the ligand-protein equilibrium show that
(4.14) interacts less well with the enzyme than (4.13) by 10 kJ
mol−1 (∆∆Ginter in equation 4.3, Section 4.5.1).
 However, (4.14) is less well stabilized by the solvent than (4.13) by
11 kJ mol−1 (∆∆Gsolv).
 The net effect is that ∆∆G is close to zero and that (4.13) and (4.14)
have essentially the same affinities for the enzyme.

30.  Drug discovery and development (technology
in transition) HP RANG.
 Text book of drug design and discovery 3rd
edition povl krogsaard-LarsenTommy
liljefors and ulf Madsen.

31. Thank you