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PHAR 735 Drug Design 2nd Handout 2006

Examples of Isosteric Replacements in the Development of Cimetidine (Tagamet®) Structures and H2-Receptor Histamine Antagonist Activities of Burimamide, Metiamide, Cimetidine, and Isosteres.

X

Z

HNR

HN N

CH3

HN

H2-Receptor activities

In vitro In vivo

Structure Atriuma Acid secretionb

Compound R X Z KB x 10-6 M ID50 (µmol/kg)

Burimamide (thiourea) H CH2 S 7.8 6.1

Thiaburimamide H S S 3.2 5

Oxaburimamide H O S 28 N.D. Metiamide (thiourea) Me S S 0.92 1.6

Urea isostere Me S O 22 27

Guanidine isostere Me S NH 16 12

Nitroguanidine isostere Me S N-NO2 1.4 2.1

Cimetidine (cyanoguanidine) Me S N-CN 0.79 1.4

Guanylurea derivative Me S N-CONH2 7.1 7.7

a Activities determined against histamine stimulation of guinea-pig right atrium in vitro. KB is the dissociation constant.

b Activity as an antagonist of histamine stimulated gastric acid secretion in anesthetized rats. N.D. = Not determined

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PHAR 735 - QSAR (Quantitative Structure-Activity Relationships) Summary

I. Goals of QSAR A. Predict biological activity in untested compounds. B. Define the structural features required for a good fit between the drug molecule and

receptor.

II. What is QSAR? It is the use of mathematical models to predict activity or define the drug binding site. The modern field of computational chemistry is a more advanced version of QSAR that relies heavily on computer technology.

III. General Classes of Descriptors

A. Physicochemical 1. Partition Coefficient or Lipophilicity (Log P) 2. Steric (Van der Waal radii, molar refraction = MR) 3. Electronic (Hammett, Taft)

B. Quantum Mechanics Probable position and energies of the electrons in the atoms that compose the molecule.

C. Topological Indices Molecular Connectivity indices (describes the specific bond connectivities within a molecule)

IV. QSAR Models The mathematical models used in QSAR can be quite complex, involving numerous parameters. Examples of these include linear, parabolic, and bilinear models. Chapter 2 (by Professor Block), pp. 17-27 covers QSAR in more detail for those interested.

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Log P

Log P is a measure of the lipophilicity of a molecule and also is known as the octanol/water partition coefficient. Octanol is a representative of a lipophilic environment. The Log P value for a drug molecule is an important parameter that correlates to drug absorption and to distribution in the body.

Conc. of drug in Octanol P = Conc. of drug in Water

Conc. of drug in Octanol Log P = log Conc. of drug in Water

The USP definition for a water insoluble compound is solubility less than 3.3% (1 g/mL = 100%). A logP value of +0.5 is equivalent to 3.3% solubility. Therefore, compounds with a log P value greater than +0.5 are insoluble, while log P values < +0.5 are water soluble. For example, consider a drug that has a concentration in octanol of 10 g/mL and a concentration in water of 0.01 g/mL. The ratio of concentrations is 1000. The logarithm of 1000 is 3, so log P = 3. This drug would be water insoluble. In the early years of medicinal chemistry, log P values were obtained by measuring the concentrations of a drug in the octanol and water layers after equilibrating the drug in the two separate phases. Today, most log P values are calculated. A relative simple model for calculating log P values is shown below.

Log Pcalc = Σπ (fragments) This equation represents that the partition coefficient can be calculated as a sum of the hydrophobic substituent constant (π) for each organic functional group in the molecule. The examples on the next page illustrate how the table of hydrophilic/lipophilic vaues (π values) can be used to provide an estimate of the log P value. Note: This is a very simplified approach to determine water solubility. This model often overestimates the log P values. More sophisticated models with highly refined π values actually provide calculated log P (ClogP) values in good agreement with measured values (MlogP). Another item to note is that these calculations do not take into consideration ionization of the drug molecule at different pH’s (salt forms). The concepts of acid-base chemistry and different functional groups associated with acidity and basicity will be covered in pharmaceutics.

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HYDROPHILIC-LIPOPHILIC VALUES (π VALUES) FOR ORGANIC FRAGMENTS Fragments π Values

C (aliphatic) +0.5 C (alkene) +0.33 Phenyl +2.0 Cl (halogen) +0.5 N (amine) -1.0 O (hydroxyl, ether) -1.0 NO2 (aliphatic nitro) -0.85 NO2 (aromatic nitro) -0.28 O=C-O (ester, carboxylic acid) -0.7 O=C-N (amide) -0.7 Intramolecular hydrogen bond (IMHB) +0.65

Note: These calculations are for the neutral molecules only. The pH of the aqueous solution will greatly influence the solubility of acidic/basic compounds. Table adapted from “Review of Organic Functional Groups. Introduction to Medicinal Organic Chemistry”, Lemke, T.L.; Fourth Edition, 2003, Lippincott Williams & Wilkens, p. 127. Examples: Calculations of water solubility for several drugs. Water solubility requires logP < +0.5.

O CH2

CH2

O

CH2

NH2N

CH3

CH3CH2

Procaine

Phenyl +2.0 6 – C @ +0.5 +3.0 2 – N @ -1.0 -2.0 O=C-O -0.7

Total +2.3 Prediction Insoluble

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O

H3C

HO

NH2

OH

Normetanephrine

Phenyl +2.0 3 – C @ +0.5 +1.5 N (amine) -1.0 3 – O @ -1.0 (2 hydroxyls + 1 ether)

-3.0

Total -0.5 Prediction Soluble

N

O2N

O

O

2 x Phenyl +4.0 9 – C @ +0.5 +4.5 N (amine) -1.0 O=C-O -0.7 NO2 (aromatic) -0.28

Total +6.52 Prediction Insoluble

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O

OH

Salicylic acid

OH

O

OH

O

H

Salicylic acid with an intramolecularhydrogen bond (IMHB)

Calc. LogP w/o IMHB Calc. LogP with IMHB Phenyl +2.0 Phenyl +2.0 O-H -1.0 O-H -1.0 O=C-O -0.7 O=C-O -0.7 IMHB +0.65

Total +0.3 Total +0.95 Prediction Soluble Prediction Insoluble As can be seen, including the intramolecular hydrogen bond in the calculation more accurately predicts the true solubility of salicylic acid (0.2% = water insoluble).

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Computer-Assisted Drug Design (CADD) (Ch. 28 for more in-depth coverage of this topic)

The general approaches used with SAR and QSAR studies can be incorporated into the design of potential drug molecules using the power of computers – Computer Assisted Drug Design. Isosteric and bioisosteric replacements can be done on a computer prior to any new compounds being synthesized and tested. Computational approaches help to narrow down the number of compounds that actually have to be tested in assays and possibly can reduce the numbers of compounds that enter into animal trials. Goal: “Design” a molecule to fit into the receptor or enzyme Assumptions:

1. Know the shape of the molecule and/or

2. Know the shape of the receptor (knowing the explicit structure of the receptor or enzyme target is also associated with a related type of drug design – Structure-Based Drug Design).

Modeling the molecule – (Molecular Modeling)

1. Chemical structure drawing programs (ball-and-stick models in the early years of drug design.) (A useful website that can illustrate the 2-D and 3-D structures of all current drug molecules is: http://redpoll.pharmacy.ualberta.ca/drugbank/)

2. X-ray crystallography (of the small molecule – not truly “modeling”, but it does provide important structural information) Assumes the conformation in the crystal is the shape seen by the receptor.

3. Quantum Mechanics a. Most accurate b. Computer intensive

4. Molecular Mechanics

a. Assumes a mechanical model for a bond between atoms. (assume the bond twists, rotates, bends, etc.) b. Parameter values for atoms and bonds adjusted until the results make sense in the “real world”. c. Numerous programs available for PCs – readily accessible.

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Structure-Based Drug Design Structure-Based Drug Design is also known as Structure-Guided Drug Design. In cases where the high resolution structure of a target is known (X-ray crystal structure or NMR-based structure), another approach can be used - Structure-Based Drug Design (this is a particular type of CADD – the structure of the target is the key factor) The high-resolution structure of the target receptor or enzyme is used as a template to match the shape and charge of potential ligands – molecules that will bind at the receptor. This approach can

often lead to improved drug candidates that do not necessarily look like previous compounds. Although this approach could be used without any lead compound in hand, it is usually used in the optimization of a lead compound. This approach requires greater computational power than lower level molecular modeling approaches, but still can be done on a PC, although larger workstations are typically employed. The HIV protease inhibitor nelfinavir (Viracept®) was developed used structure-based drug design. The crystal structure of HIV protease was used in this process. A few websites that describe structure-based drug design are: http://www.cgl.ucsf.edu/Research/collaboratory/sbdd.html http://csbcc1.csbcc.dartmouth.edu/sbdd.html http://www.accelrys.com/services/contract/structdd.html

NH

OH

N

S O

CH3

HN

OCH3

HO

CH3

CH3

H

H

Nelfinavir (Viracept®)

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Crystal Structure of HIV Protease This image shows the general overall structure for the dimer of HIV protease with the substrate binding pocket in the center of the molecule. The specific amino acid residues lining this binding pocket were examined for their interactions with potential inhibitors and one result was the antiviral drug nelfinavir. (image from http://oregonstate.edu/instruction/bb450/stryer/ch09/Slide33.jpg)

NH

OH

N

S O

CH3

HN

OCH3

HO

CH3

CH3

H

H

Nelfinavir (Viracept®)

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Importance of Stereochemistry in Drug Design/Drug Action

Many drug molecules contain one or more chiral centers, which meansthat there can be more than one stereoisomer of these drugs. In most cases,a single enantiomer or diastereomer will be the major active compound. Formost drugs, it is believed that the "inactive" isomer is harmless, so often thereis little reason to develop the single enantiomer as a drug. However, stereochemistry often can affect drug metabolism as well as drug action, so the pharmacokinetics of the individual isomers often differs. In modern drugdesign, the single active enantiomer is often prepared early in the process sothat only the single enantiomer product is developed as a drug.

Definitions:Eutomer - The stereoisomer with higher receptor affinity or activity.Distomer - The stereoisomer with lower receptor affinity or activity.

Racemic mixture/racemate - A mixture with equal quantities of R- and S-enantiomers.

OHHN

CH3

CH3

CH3

HO

HO

*

OHHN

CH3

CH3

CH3

HO

HO

R

Albuterol(racemic mixture)

Levalbuterol(Single active R-isomer)

H3C

N H

N

H3C

N

H

N

The term "stereoisomer" also is applied to compounds with differentstereochemistry about a double bond.

Triprolidine - (E - isomer)"trans"

Triprolidine - (Z - isomer)"cis"

Triprolidine is used as the single E - isomer. It is 1000x as potent as theZ - isomer as an antihistamine.

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Stereochemistry in Drug Design/Drug Action

H3CN

H3C

OO

CH3

Dextropropoxyphene = analgesic

H3CN

H3C

OO

CH3

Levopropoxyphene =antitussive

O N

CH3

Cl

CH3

H

Clemastine - Used as a single R, R-stereoisomer.The R,R + S,S pair and the R,S + S,R pair are enantiomeric pairs.The R,R + S,R; R,R + S,R; S,S + R,S; and S,S + S,R combinations would be considered diastereomeric pairs.Enantiomers are stereoisomers with equal and opposite optical rotations. Diastereomers are stereoisomers, but not exact mirror images of each other (optical rotations don't have to be equal and opposite).

O N

CH3

Cl

CH3

H

O N

CH3

Cl

CH3

H

S, R - isomerR, S - isomer

O N

CH3

Cl

CH3

H

If a molecule has two different chiral centers, there will be four possiblestereoisomers.

R, R - isomer S, S - isomer

Enantiomers with different biological activities.

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Summary of main points in “Principles of Drug Design” “Drug Design” has three phases – Discovery, Optimization, and Development Medicinal chemists play an important role in the discovery and optimization phases.

1) Determine biological target and devise assay for the disease state of interest 2) Obtain potential lead compounds (natural products, synthetic compound libraries,

combinatorial libraries, virtual screening) 3) Optimization of lead compounds (main role for medicinal chemists)

Lock and key model; “induced-fit” model; bonding interactions Lipinski’s Rule of Five Identification of the pharmacophore

SAR Studies Homologation and chain branching Ring transformation Isosteric and bioisosteric replacements QSAR Studies log P, steric factors, electronic factors C log P estimation Computer Assisted Drug Design (CADD) Molecular Modeling Structure Based Drug Design Stereochemistry in Drug Design

General guidelines a) Understand the general process of drug design including the identification of lead

compounds (what are the sources and what types of assays might be used) and know the general biochemical classes of drug targets (e.g. receptors, enzymes, etc.)

b) Know the following terms and concepts: “lock and key” model; “induced fit” model; Lipinski’s rule of 5; pharmacophore; SAR; QSAR; log P and C log P; homologation; isostere; bioisostere; enantiomer; diastereomer; eutomer; distomer.

c) Be able to identify potential bonding interactions for a given drug molecule (H-bonds, ionic bonds, hydrophobic interactions, etc.)

d) Know at least one example for isosteric replacements in each functional group class. e) Be able to calculate log P values given a table of hydrophobic substituent constants (π

values). f) Understand the distinction between the more general computer aided drug design (CADD)

and the more specific Structure-Based Drug Design.