The document discusses drug design as the process of creating new medications by understanding biological targets, detailing two main methods: traditional trial-and-error and rational drug design. It highlights key factors affecting drug properties such as ionization, solubility, and stereoisomerism, and introduces computational chemistry techniques, including structure-based and ligand-based drug design. It also emphasizes the role of computer-aided drug design (CADD) in developing therapeutics and provides examples of drugs discovered through these methods.

1. Computational
Chemistry
1
Mehedi Islam
Lecturer
Department of Pharmacy
State University of Bangladesh

2. Drug Design
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Drug design is the inventive process of finding new medications
based on the knowledge of a biological target.
In general, drug design involves the design of organic (less commonly
inorganic) molecules that are complementary in shape and charge to
the biomolecular target with which they interact and therefore will
bind to it.
Drug design involves:
a) modification of lead compound (from natural/synthetic
source),
b) invention of new drug (using computational chemistry)

3. Two ways of Drug Design….
Traditional methods, (known as forward pharmacology): Relies
on trial-and-error testing of chemical substances on cultured cells or
animals, and matching the apparent effects to treatments.
Rational drug design, (or reverse pharmacology): This process of
drug design begins with a postulate that modulation of a specific
biological target, where ligand may have therapeutic value.
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4. Properties to be considered during drug design….
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5. Ionization (Acid / Base properties)
Ionization refers to the protonation or deprotonation, resulting in
charged molecules
The acidity or basicity of a compound plays a major role in
controlling:
 Absorption and transport to site of action
• Solubility, bioavailability, absorption and cell
penetration, plasma binding, volume of distribution
 Binding of a compound at its site of action
• un-ionised form involved in hydrogen bonding
• ionised form influences strength of salt bridges or H-
bonds
 Elimination of compound
• Biliary and renal excretion
• CYP P450 metabolism
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6. Look at the sulphonamides (antibacterial)
 These compounds are only active in their ionised forms
 Despite only minor differences in half-life and lipo-solubility,
there is a huge difference in activity
 This is due to their respective pKa values:
 For sulfadiazine, at pH 7.4 it is ~80% ionised
 For sulfanilamide, at pH 7.4 it is only 0.03% ionised
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9. Example:% ionisationfor aspirin
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12. Water Solubility
The solubility of a drug in water directly affects the route of
administration, distribution, and elimination (ADME).
 The two most important key factors that influence the water
solubility are:
• Hydrogen bonding: more H-bonds → solubility
• Ionisation: dissociable ions → solubility
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13. Partition coefficient deals with:
• lipophilic vs. hydrophilic character of drug
• determines the water solubility of drug
substances
• affects drug distribution
• confers target-drug binding interactions
Partition coefficient (Hydrophylicity and Lipophylicity)
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14. Predicting Water Solubility
1. Empirical Approach
2. Analytical Approach
Empirical Approach
Lemke developed an empiric approach to predict the water solubility of
molecules based on the carbon-solubilizing potential of several functional
groups.
In this approach, if the solubilizing potential of the functional groups are
more
than the total number of carbon atoms present, then the molecule is
considered to be water soluble. Otherwise, it is considered to be water
insoluble.
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15. Water solubilising potential of organic functional groups of mono- and
poly- functional molecules
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16. The Empirical Approach –a working example
 We get a total “solubilising potential” of 9 carbons using this
theory.
Since the molecule contains 22 carbons, it suggests that the
molecule is insoluble in water. However, if we make the
hydrochloride salt, then the compound becomes water soluble.
Lemke estimates that a charge (either anionic or cationic)
contributes a “solubilising potential” of between 20 and 30 carbons
Anileridine
(Narcotic analgesic)
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17. ⮩ The alternative approach for predicting water solubility utilises the
“logP” of molecules.
⮩ Essentially, logP is a measure of lipophilicity (hydrophobic)
properties
of a molecule.
⮩ It is determined by measuring the “partition co-efficient” between
water and octanol for a given molecule (i.e., the solubility of the
compound in octanol versus the solubility of the compound in water).
• LogP is calculated by adding the contributionsfrom each
functional group in the molecule
• A hydrophobic substituent constant π has been assigned to most
organic functional groups, such that LogP = ∑ π (fragments)
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The alternative approach

18. • The USP definition for a water insoluble compound is solubility less
than 3.3% (1g/mL = 100%). A logP value of +0.5 is equivalent to
3.3% solubility. Therefore, compound with a logP value greater than
+0.5 are insoluble, while logP <+0.5 are water soluble.
• Therefore, anileridine, with a logP greater than + 0.5 is considered
insoluble
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19. Stereoisomerism and Biological Activity
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The biological activity of a drug molecule is not only dependent on its
physicochemical characteristics but also the spatial arrangement
of the functional groups in the molecule.
Stereoisomers are compounds having the same number and kinds of
atoms, the same configuration (arrangement) of bonds, but altogether
different 3D-structures i.e., they specifically differ in the 3D
arrangements of atoms in space.

20. Example (i) shows that the S-(+) naproxen sodium (left) with activity
as an antipyretic, analgesic and anti-inflammatory drug. In contrast,
the R-(–) naproxen sodium (right) is inactive.
(i)
Example (i)
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21. Easson-Stedman Theory
Easson-Stedman hypothesis also known as the three-point attachment
theory, a theory which proposes that three groups or moieties in a drug
molecule must simultaneously interact with three complimentary sites
on the receptor molecule. This theory is based on the knowledge that three
points are required for the desired bonding and that different enantiomers
often have markedly different biological effects.
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22. According to this theory, the R (–) – Epinephrine has greater biological
activity than S (+) – Epinephrine or Epinine.
Because, the R-isomer can bind to all the three sites: (i) catechol binding site
‘A’ (ii) hydroxy binding site ‘B’ and (iii) anionic binding site ‘C’ (illustrated
below); whereas, the S-isomer and the deoxy isomer exclusively bind to two
of the sites, thus exhibiting identical biological activity which is lower than that
of R- isomer.
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23. A vital, useful and latest strategy involves converting a conformationally
flexible molecule into a conformationally rigid molecule, so as to
establish and find the optimized conformation that is required for
binding to the drug receptor.
This scientific and logical approach helps -
 in incorporating selectivity for receptors
 in minimizing and eliminating undesired side effects
 in learning more with regard to spatial relationships of
functional moieties for receptors.
Conformationally Flexible to Conformationally Rigid Molecule
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24. Computational chemistry is a branch of chemistry that uses computer
simulation to assist in solving chemical problems.
⮩ It uses methods of theoretical chemistry, incorporated into
efficient computer programs, to calculate the structures and
properties
of molecules and solids.
⮩ Computational results normally complement the information
obtained by chemical experiments, in some cases predict the
unobserved chemical phenomena.
⮩ It is widely used in the design of new drugs and materials.
Again, Computer Aided Drug Design (CADD) utilizes computer to aid
in the creation, modification, analysis, and optimiztion of the drug
design.
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26. Structure-based drug design
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Structure-based drug design (or direct drug design) relies on
knowledge of the 3D-structure of the biological target obtained
through methods such as x-ray crystallography or NMR spectroscopy.
 Using the structure of the biological target, candidate drugs are
predicted to bind with high affinity and selectivity.
 Here, computational procedures may be used to suggest new
drug candidates.

27. Structure-based drug design can be divided roughly into three main
categories:
1. The first method is identification of new ligands for a given receptor
by searching large databases of 3D structures of small molecules. Then
molecular docking is performed to identify the appropriate one.
2. A second category is de novo design of new ligands. In this method,
ligand molecules are built up by assembling small pieces in a stepwise
manner. These pieces can be either individual atoms or molecular
fragments. The key advantage of such a method is that novel structures,
not contained in any database, can be suggested.
3. A third method is the optimization of known ligands by evaluating the
proposed analogs within the binding cavity.
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Structure-based drug design

28. Molecular Docking
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* The aim of molecular docking is to evaluate the feasible binding
of a ligand with a target whose 3D structure is known.
* Docking methods rapidly and accurately dock large numbers of
small molecules into the binding site of a receptor, allowing for a
rank ordering in terms of strength of interaction with a particular
receptor.
* Some of the docking programs are GOLD (Genetic Optimization for
Ligand Docking), AUTODOCK, LUDI, HEX etc.

29. Tasks of docking
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There are three basic tasks that any docking procedure must
accomplish:
(1) Characterizing the binding site;
(2) Positioning of the ligand into the binding site (orientation); and
(3) Evaluating the strength of interaction for a specific ligand-
receptor complex.
In order to screen large databases, automated docking is required.

30. How DOCK works…….
Some ligands
(potential
inhibitors)
1.) Identify which fit together
the best
Areceptor (target molecule)
2.) Find the best
orientation and
conformation
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31. If we know exactly where and how a known ligand binds...
 We can see which parts are important for binding
 We can suggest changes to improve affinity
 Avoid changes that will ‘clash’ with the protein
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How DOCK works…….

32. Identification of
the ligand’s
binding
geometry (pose)
in the binding
site (Binding
Mode)
Prediction of the
binding affinity
(Scoring
Function)
Molecular Docking
Rational Design of Drugs
Importance of Molecular Docking
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33. TYPES OF DOCKING
Rigid Docking (Lock and Key): In rigid docking, the internal geometry of
both the receptor and ligand are treated as rigid.
Flexible Docking (Induced fit): The effect of the rotations of the molecules
(usually smaller one) is calculated. In every rotation, the energy is calculated;
later the most optimum orientation is selected.
Docking can be between….
Protein - Ligand
Protein – Protein
Protein – Nucleotide
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34. LIGAND-PROTEIN DOCKING
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35. LIGAND-PROTEIN DOCKING
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36. 1. Electrostatic forces - Electrostatic forces are due to the
charges residing in the matter.
2. Electrodynamics forces - The most widely known is probably the
van der Waals interaction.
3. Steric forces – Steric forces generate due to the spatial
arrangement of the atoms. When atoms come close together, there is
a rise in the energy of the molecule.
4. Solvent-related forces – Molecular structures are influenced
because of the interaction with the solvent. The most common
interactions are Hydrogen bonding and hydrophobic interactions.
Types of interactions between ligands and biological
targets
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37. 1. Receptor selection and preparation
Building the Receptor
 The 3D structure of the receptor should be considered
which can be downloaded from PDB.
 The available structure should be processed.
 The receptor should be biologically active and stable.
Identification of the Active Site
 The active site within the receptor should be identified.
 The receptor may have many active sites but the one of the
interest should be selected.
Key Stages In Docking
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38. Key Stages In Docking
2. Ligand selection and preparation: Ligands can be obtained
from various databases like ZINC, PubChem or can be sketched
using tools like Chemsketch, ChemDraw.
3. Docking: The ligand is docked onto the receptor and the
interactions are checked. The scoring function generates score,
depending on which the best fit ligand is selected.

39. Different approaches based on structural availability
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40. De Novo Drug Design
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De novo means start afresh, from the beginning, from the scratch .
• It is a process in which the 3D structure of receptor is used to
design newer molecules.
• It involves structural determination of the lead and lead
modifications using molecular modeling tools.
De novo design approach involves the ligand optimization, which
can be done by analyzing protein active site properties that
could be probable area of contact by the ligand.

41. Types of De Novo Drug Design
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Manual
• Operator directs the study
• Allows input of designer’s ideas
• Useful for identification of a single lead compound
• Slow and limited to designer’s originality
Automated
• Program is automated
• No bias introduced by operator
• Produces novel structures
• Useful for generating a large number of possible lead compounds
• May generate impractical structures for synthesis
• Scoring structures for binding strengths is unreliable

42. 1. Determination of crystal structure by X-ray crystallography
2. Identification of the binding site
3. In silico designing of ligands to fit and bind to the binding site
4. Identification of binding interactions
5. Calculating the strength of binding
6. Synthesizing and test of the promising structures
7. Optimizing by structure-based drug design
Procedure of De Novo Drug Design
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43. Methods for de novo drug design
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44. LUDI: a new method for the de novo design of enzyme
inhibitors
Stage 1: identification of interaction sites
Stage 2: fitting molecular
fragments
Stage 3: fragment bridging
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45. LUDI
Stage 1: Identification of interaction sites
The atoms present in the binding site are analysed to identify – i) those that
can take part in hydrogen bonding interactions, and ii) those that can take
part in van der Waals interactions.
Stage 2: fitting molecular fragments
The LUDI program accesses a library of several hundred molecular
fragments. The molecules chosen are typically 5 - 30 atoms in size.
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46. Stage 3: fragment bridging
Fragments have been identified and fitted to the binding site, the final stage
is to link them up.
The program first identifies the molecular fragments that closest to each
other in the binding site, then identifies the closest hydrogen atoms.
These now define the link sites for the bridge. The program now tries out
various molecular bridges from a stored library to find out which one
fits best.
A suitable bridge has been found, a final molecule is created.
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47. CADD has already been used in the discovery of compounds that have passed
clinical trials and become novel therapeutics in the treatment of a variety of
diseases.
Some of the examples of approved drugs that owe their discovery in large
part to the tools of CADD:
 carbonic anhydrase inhibitor dorzolamide, approved in 1995
 the angiotensin-converting enzyme (ACE) inhibitor captopril, approved
in 1981 as an antihypertensive drug
 three therapeutics for the treatment of human immunodeficiency virus
(HIV): saquinavir (approved in 1995), ritonavir, and indinavir (both
approved in 1996)
 tirofiban, a fibrinogen antagonist approved in 1998
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Examples of CADDed drugs

48. Ligand-based drug design
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The ligand-based computer-aided drug discovery (LB-CADD, also
called indirect drug design) approach involves the analysis of
ligands known to interact with a target of interest.
* These methods use a set of reference structures collected
from compounds known to interact with the target of interest
and analyze their 2D or 3D structures.
* The overall goal is to represent these compounds in such a way that
the physicochemical properties, which are most important for their
desired interactions, are reserved, whereas unrelated information
(to the interactions) is discarded.

49. The two fundamental approaches of LB-CADD
are
(1) selection of compounds based on chemical
similarity to known actives using some
similarity measure or
(2) the construction of a QSAR model that
predicts biologic activity from chemical
structure.
The difference between the two approaches is
that the later weights the features of the
chemical structure according to their influence
on the biologic activity of interest, whereas the
former does not.
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50. Thank You
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