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DRUG DESIGNING

IMPORTANCE OF SAR AND QSAR STUDIES

ContentsIntroduction.............................................................................................................................................................6

A Brief History......................................................................................................................................................6

Drug Discovery And its Importance......................................................................................................................6

Drug Design Scheme................................................................................................................................................8

Target Discovery...................................................................................................................................................8

Assay Development..............................................................................................................................................8

Screening and Hits to Leads.................................................................................................................................9

Lead Optimization................................................................................................................................................9

Development........................................................................................................................................................9

Clinical Trials.....................................................................................................................................................10

Phase 1...............................................................................................................................................................10

Phase 2...............................................................................................................................................................11

Phase 3...............................................................................................................................................................11

NDA...................................................................................................................................................................11

Phase 4...............................................................................................................................................................12

Approaches to Drug Design...................................................................................................................................12

Structure-Activity Relationships (SARS)...........................................................................................................12

Changing shape and size....................................................................................................................................13

Introduction of new substitution.........................................................................................................................13

Introduction of a group in an unsubstituted position...........................................................................................13

Introduction of a group by replacing an existing group......................................................................................14

Quantitative Structure-Activity Relationships (QSARS)........................................................................................14

Factors Influencing Drug-Activity......................................................................................................................14

Lypophilicity......................................................................................................................................................14

Partition Coefficient (P)...................................................................................................................................15

Lypophilic substituent constants (π)...............................................................................................................15

Electronic effects................................................................................................................................................16

The Hammet Constant....................................................................................................................................16

Steric Effects..........................................................................................................................................................16

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The Taft Steric Parameter...............................................................................................................................17

Molar refractivity (MR)...................................................................................................................................17

Other Parameters...............................................................................................................................................17

Hansch Analysis.................................................................................................................................................17

S.A.R STUDIES ON MORPHINE ANALOGS...............................................................................................................19

STRUCTURES.......................................................................................................................................................19

PROPERTIES........................................................................................................................................................19

RESULT.................................................................................................................................................................24

MORPHINE.......................................................................................................................................................24

HEROIN.............................................................................................................................................................25

NALORPHINE..................................................................................................................................................27

CONCLUSION......................................................................................................................................................28

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PREFACEIn the 1990s and the new millennium, major changes have occurred in the pharmaceutical industry from the vantage points of research and development as well as commercial operations. New technologies and processes such as “high throughput screening” and “combinatorial chemistry” were widely embraced and developed to a high state of performance during this period. Combinatorial chemistry, a process in which a core molecule is modified with a broad spectrum of chemical reactions in single or multiple reaction vessels, can produce tens of thousands of compounds for screening. The objective of both approaches is to provide very large numbers of new chemical entities to be screened for biological activity in vitro. The use of computers to design new drug candidates has been developed to a significant level of sophistication. By viewing on the computer, the “active site” to which one wants the drug candidate to bind, a molecule can often be designed to accomplish that goal.

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ACKNOWLEDGEMENTI thank my teachers Mrs Dipali and Mr Mhatre for giving me this opportunity to work in this project and also for their unmatched support and guidance which has helped me get par many difficulties without being affected. I would also like to thank my elder brother Prashant for giving me unconditional support and help throughout the project.

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Introduction

A Brief HistoryPrior to the 20th century, the discovery of drug substances for the treatment of human diseases was primarily a matter of “hit or miss” use in humans, based on folklore and anecdotal reports. Most of our earliest therapeutic remedies were derived from plants or plant extracts that had been administered to sick humans. Some of these early medications were truly effective. But the remaining were perceived as effective by the patient because of the psychological aspects of consuming a “medication” exerted positive effects in a wide range of disease states, attesting to the “power of suggestion” under certain circumstances.

In the 1960s and 1970s, pioneers in the field of medicinal chemistry became instrumental in initiating the transition from the study of plants or their extracts with purported therapeutic activities to the deliberate synthesis, in the laboratory, of a specific drug substance. They began to modify the chemical structures produced by the microorganisms and thus gave rise to the antibiotics. The biomedical scientists in pharmaceutical companies started actively pursuing purified extracts and pure compounds derived from plants and animal sources as human medicaments, and thus commercialized the drugs for common use.

As the drug discovery process increased in intensity in the mid- to late 20th century, primarily as a result of the major screening and chemical synthetic efforts in the pharmaceutical industry in industrialized countries worldwide, but also as a result of the biotechnology revolution, the need for increased sophistication and efficacy in (1) how to discover new drugs, (2) how to reproducibly prepare bulk chemicals, (3) how to determine the activity and safety of new drug candidates in preclinical animal models prior to their administration to human beings and, finally, (4) how to establish their efficacy and safety in man, became of paramount importance.

Drug Discovery And its Importance In the 1990s and the new millennium, major changes have occurred in the pharmaceutical industry from the vantage points of research and development as well as commercial operations. New technologies and processes such as “high throughput screening” and “combinatorial chemistry” were widely embraced and developed to a high state of performance during this period. Combinatorial chemistry, a process in which a core molecule is modified with a broad spectrum of chemical reactions in single or multiple reaction vessels, can produce tens of thousands of compounds for screening. The objective of both approaches is to provide very large numbers of new chemical entities to be screened for biological activity in vitro. The use of computers to design new drug candidates has been developed to a significant level of sophistication. By viewing on the computer, the “active site” to which one wants the drug candidate to bind, a molecule can often be designed to accomplish that goal.

Studies in the last few years in the fields of genomics and proteomics have made available to us an unprecedented number of targets with which to search for new drug candidates. While knowledge of a particular gene sequence, for example, may not directly point to a specific disease when the sequences

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are first determined, investigations of their presence in normal and diseased tissues could well lead to a quantitative in vitro test system that is not available today.

As genomics advanced, animal models can now be derived using gene manipulation and cloning methods that give us never-before available in vivo models to be used in new drug screening and development. A large number of mammalian cell culture systems have also been developed not only to be used in primary screening but also for secondary evaluations. For example, the in vitro Caco 2 system shows some very interesting correlation with drug absorption in vivo. A test such as this is mandatory when one is dealing with several thousands of compounds or mixtures in a given experiment. More time will be needed to be absolutely certain of the predictability of such test systems but, appropriately, Caco 2 is widely used today in screening and prioritizing new drug candidates. As is always the case, the ultimate predictability of all the in vitro tests must await extensive studies in humans.

In the cancer field, new methodologies in science have, again, given us new targets with which to search for chemotherapeutic agents. The humanization of monoclonal antibodies has resulted in the marketing of some truly impressive drugs that are much better tolerated by the patient than the previously used ones. Unfortunately, drug resistance once again plagues the cancer field, as are the cases with AIDS and various infectious diseases. As a result, researchers are seeking compounds that are not cross-resistant with existing therapies. Very significant advances in drug discovery are also expected to be seen in central nervous system, cardiovascular, and other chronic diseases as a result of breakthrough research in these fields.

During the past decade, clinical trial methodology has been expanded, improved and standardized. The clinical testing phase of new drug development is the most expensive single activity performed. No financial incentive for the drug researches has been received from the pharmaceutical industry. As the result of the very complicated nature of drug discovery and development, unbelievable costs accrue in order to bring a new therapeutic agent to market. In addition to cost, it is very time consuming since, with chronic diseases, one must investigate the new drug candidate in a significant number of patients over a period of months or years, in randomized, double-blind, placebo- or active-drug-controlled studies. The cost for the development of a major drug inclusive of the cost of “lost” compounds that did not make the grade during preclinical or clinical testing, has been widely stated to be US $800 million per new therapeutic agent placed on the market. It has recently been reported that, while historically 14% of drugs that entered phase I clinical trials eventually won approval, now only 8% succeed. Furthermore, 50% of the drug candidates fail in the late stage of phase III trials compared to 20% in past years.

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Drug Design Scheme

Target DiscoveryDrug discovery and development can broadly follow two different paradigms—physiology based drug discovery and target-based discovery. The main difference between these two paradigms lies in the time point at which the drug target is actually identified. Physiology-based drug discovery follows physiological readouts, for example, the amelioration of a disease phenotype in an animal model or cell-based assay. Compounds are screened and profiled based on this readout. A purely physiology-based approach would initially forgo target identification/validation and instead jump right into screening. Identification of the drug target and the mechanism of action would follow in later stages of the process by deduction based on the specific pharmacological properties of lead compounds. By contrast, the road of target-based drug discovery begins with identifying the function of a possible therapeutic target and its role in disease. Given the thousands of human or pathogen genes and the variety of their respective gene products, this can be a difficult task. Furthermore, insight into the "normal" or "native" function of a gene or gene product does not necessarily connect the gene or gene product to disease. The two paradigms are not mutually exclusive, and drug discovery projects can employ a two pronged approach. The genomics revolution has been the main driver of the target-based paradigm over the last decade. Currently, all existing therapies together hit only about 400 different drug targets and there are at least 10 times as many potential drug targets that could be exploited for future drug therapy.

Assay Development

The key to drug discovery is an assay that fulfills the following criteria- Relevance: Does the readout unequivocally relate to the target? Reliability/Robustness: Are results reproducible and statistically significant?

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Practicality: Do time, reagents, and effort correlate with quality and quantity of results?

Feasibility: Can assay be run with resources at hand?

Automation: In order to screen large numbers of compounds, can assay be automated and run in highly parallel format?

Cost: Does cost of the assay permit scale-up for high-throughput screening?

The quality of an assay determines the quality of data, i.e., compromising on assay development can have substantial downstream consequences.

Screening and Hits to Leads

After successful development of an assay, screening of compound libraries follows. Primary screens will identify hits. Subsequently, confirmation screens and counter screens will identify leads out of the pool of hits. This winnowing process is commonly referred to as "hits-to-leads." The success of screening depends on the availability of compounds, as well as their quality and diversity. Efforts to synthesize, collect, and characterize compounds are an essential and costly part of drug discovery.

Lead Optimization

Lead optimization is the complex, non-linear process of refining the chemical structure of a confirmed hit to improve its drug characteristics with the goal of producing a preclinical drug candidate. This stage frequently represents the bottleneck of a drug discovery program. Lead optimization employs a combination of empirical, combinatorial, and rational approaches that optimize leads through a continuous, multi-step process based on knowledge gained at each stage. Typically, one or more confirmed hits are evaluated in secondary assays, and a set of related compounds, called analogs, are synthesized and screened. The testing of analog series results in quantitative information that correlates changes in chemical structure to biological and pharmacological data generated to establish Structure Activity Relationships (SAR). The lead optimization process is highly iterative. Leads are assessed in pharmacological assays for their "drug-likeness." Medicinal chemists change the lead molecules based on these results in order to optimize pharmacological properties such as bioavailability or stability. At that point the new analogs feed back into the screening hierarchy for the determination of potency, selectivity, and MOA. These data then feed into the next optimization cycle. The lead optimization process continues for as long as it takes to achieve a defined drug profile that warrants testing of the new drug in humans.

Development

The decision to take a new drug candidate into the development phase entails a significant commitment in terms of money, resources, and time. The attrition rate for making it to market is a disheartening nine in 10 compounds, and development costs per approved drug amount to $800 million. The average time to develop a new drug was 12 years and 10 months in 2002.The number of new chemical entities (NCEs) gaining market approval has decreased over the last decade down to 20 per year. At the same

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time, the estimated average of new NCEs needed for the pharmaceutical and biotech industry to sustain a 5 percent growth rate is 50. In terms of standards, drug development requires attention to the following:

GLP - Good Laboratory Practice refers to nonclinical laboratory studies that support or are intended to support applications for research or marketing permits.

GMP - Good Manufacturing Practice, also known as cGMP ("current" GMP), is a set of regulations requiring that quality, safety, and effectiveness be built into foods, drugs, medical devices, and biological products.

21 CFR - describing the code of regulations for food and drugs. Part 11 has become particularly relevant describing the standards and regulations on electronic data and electronic signatures.

Clinical Trials

Clinical trials are a peculiar hybrid between a formalized and strictly regulated process on the one hand and a sophisticated stratagem on the other, particularly when it comes to patient selection, statistical methodology, disease markers, and endpoints employing cutting-edge research. They are also expensive, accounting for 50 to 70 percent of the drug discovery and development cost. They can be very long, lasting many years depending on therapeutic area. Ninety percent of NCEs entering clinical trials fail. Forty percent of compounds fail in Phase 1, 62 percent of successful Phase1 compounds fail in Phase 2, 40 percent of successful Phase 2 compounds fail in Phase 3, and a surprising 23 percent of successful Phase 3 compounds fail at the registration stage, when the FDA denies approval for a completed New Drug Application (NDA.). The main reason for failure was problems in PK/bioavailability (40 percent) followed by lack of efficacy (30 percent) and toxicology (12 percent), lack of efficacy (27 percent), followed by commercial and market reasons (21 percent) and toxicology (20 percent) etc.

Phase 1

Phase 1 includes the initial introduction of an investigational new drug into humans. These studies are closely monitored and may be conducted in patients, but are usually conducted in healthy volunteer subjects. These studies are designed to determine the metabolic and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on efficacy. During Phase 1, sufficient information about the drug's pharmacokinetics and pharmacological effects should be obtained to permit the design of well-controlled, scientifically valid Phase 2 studies. Phase 1 studies also evaluate drug metabolism, structure-activity relationships (SAR), and the mechanism of action (MOA) in humans. These studies also determine which investigational drugs are used as research tools to explore biological phenomena or disease processes. The total number of subjects included in Phase 1 studies varies with the drug, but is generally in the range of 20 to 80. In Phase 1 studies, CDER (Center for Drug Evaluation and Research) can impose a clinical hold (i.e., prohibit the study from proceeding or stop a trial that has started) for reasons of safety, or because of a sponsor's failure to accurately disclose the risk of study to investigators. Although CDER routinely provides advice in such cases, investigators may choose to ignore any advice regarding the design of Phase 1 studies in areas other than patient safety.

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Phase 2

Phase 2 includes early controlled clinical studies conducted to obtain some preliminary data on the efficacy of the drug for a particular indication (or indications) in patients with the disease. This testing phase also helps determine common short-term side effects and risks associated with the drug. Decisive or pivotal trials are usually run as randomized controlled trials (RCT). Randomization introduces a deliberate element of chance into the assignment of treatments to trial patients. Phase 2a : Pilot trials to evaluate efficacy and safety in selected populations of about 100 to 300

patients who have the condition to be treated, diagnosed, or prevented. They often involve hospitalized patients who can be closely monitored. Objectives may focus on dose-response, type of patient, frequency of dosing, or any of a number of other issues involved in safety and efficacy.

Phase 2b : Well-controlled trials to evaluate safety and efficacy in patients who have the condition to

be treated, diagnosed, or prevented. These trials usually represent the most rigorous demonstration of a medicine's efficacy.

Phase 3

Phase 3 studies are expanded, controlled, and uncontrolled trials. They are performed after preliminary evidence of effectiveness has been obtained in Phase 2, and are intended to gather the additional information about safety and effectiveness needed to evaluate the overall benefit-risk relationship of the drug. Phase 3 trials should provide an adequate basis for extrapolating the results to the general population and conveying that information in the physician labeling. These studies usually include several hundred to several thousand people. In both Phase 2 and 3, the Center for Drug Evaluation and Research (CDER), a branch of the FDA, can impose a clinical hold if a study is unsafe or if the protocol design is deficient in meeting its stated objectives. The FDA aims to ensure that this determination reflects current scientific knowledge, agency experience with clinical trial design, and experience with the class of drugs under investigation. FDA approval/disapproval decisions are based on the results of pivotal studies. To be considered pivotal, a study must meet at least these 4 criteria:– Be controlled using placebo or a standard therapy.– Have a double-blinded design when such a design is practical and ethical.

NDA

Although the amount of information and data submitted in NDAs varies, the components of NDAs are uniform. The components of any NDA are, in part, a function of the nature of the subject drug and the information available to the applicant at the time of submission. NDAs can consist of as many as 15 different sections:

Index; Summary; Chemistry, Manufacturing, and Control (CMC); Samples, Methods Validation Package, and Labeling; Nonclinical Pharmacology and Toxicology;

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Human Pharmacokinetics and Bioavailability; Microbiology (for anti-microbial drugs only); Clinical Data; Safety Update Report (typically submitted 120 days after the NDA's submission); Statistical; Case Report Tabulations; Case Report Forms; Patent Information; Patent Certification; and Other Information.

Phase 4

Phase 4 trials are done after a drug has received a market approval. These trials are monitoring drugs that are available for doctors to prescribe, rather than experimental drugs that are still being developed.

Approaches to Drug Design

Structure-Activity Relationships (SARS)Compounds with similar structures to a pharmacologically active drug are often themselves biologically active. This activity may be either similar to that of the original compound but different in potency and unwanted side effects or completely different to that exhibited by the original compound. These structurally related activities are commonly referred to as Structure-Activity Relationships (SARS). A

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study of the SAR of the lead compound that is responsible for both its beneficial biological activity and its unwanted side effects.

Structure-activity relationships are usually determined by making minor changes to the structure of the lead to produce analogues and assessing the effects these structures have on the biological activity. The investigations of numerous lead compounds and their analogues have made it possible to make some broad generalizations about the biological effects of specific types of structural change.

These changes may be conveniently classified as changing –

The size and shape of the carbon skeleton The nature and degree of substitution The stereochemistry of the lead

Changing shape and size

The shapes and sizes of molecules can be modified in a variety of ways, such as changing the number of methylene groups in chains and rings, increasing or degree of unsaturation and introducing or removing a ring system. These types of structural change result in analogues that exhibit either a different potency or a different type of activity to the lead.

Introduction of new substitution

Introduction of new substituent will impart its own characteristic chemical, pharmacokinetic and pharmacodynamic properties to the analogue.

New substituents can be introduced in the following ways –

i) Introduction of a group in an unsubstituted position ii) Introduction of a group by replacing an existing group

Introduction of a group in an unsubstituted position

The incorporation of any group will always result in analogues with a different size and shape to the lead compound. It may also introduce a chiral centre, which will result in the formation of stereoisomers, which may or may not have different pharmacological activities. Alternatively, it may impose conformation restrictions of some of the bonds in the analogue.

The introduction of a new group may result in an increase or a reduction in the rate of metabolism or an alternative route for metabolism. These changes could also change the duration of action and the nature of any side effects. For example, mono- and diortho-methylation with respect to the phenolic hydroxyl

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group of paracetamol produces analogues with reduced hepatotoxicity. This reduction is due to the methyl groups preventing metabolic hydroxylation of these ortho positions.

Introduction of a group by replacing an existing group

Analogues formed by replacing an existing by a new group may exhibit the general stereochemical and metabolic changes as exhibited by introducing a group in an unsubstituted position. The choice of the group is made using the concept of isosteres. Isosteres are group that exhibit some similarities in their chemical and / or physical properties. As a result, they may exhibit similar pharmacokinetic and pharmacodynamic properties. In other words, the replacement of a substituent by its isostere is more likely to result in the formation of an analogue with the same type activity as the lead than the totally random selection of an alternative substituent. However, luck still plays a part, and an isosteric analogue may have a totally different type of activity from its lead.

Quantitative Structure-Activity Relationships (QSARS)QSAR is an attempt to remove the element of luck from drug design by establishing a mathematical relationship in the form of an equation between biological activity and measurable physicochemical parameters. These parameters are used to represent properties such as lypophilicity, shape and electron distribution, which have a major influence on the drug’s activity. They are normally defined so that they are in the form of numbers, which are derived from practical data that is thought to be related to the property the parameter represents. This makes it possible to calculate these parameters for a group of compounds and relate their values to the biological activity of these compounds by means of mathematical equations using statistical methods.

QSAR derived equations take the general form:

Biological activity = function {parameter(s)}

Factors Influencing Drug-Activity

The major factors that influence the drug-activity are-

i) Lipophilicityii) Electronic effectsiii) Steric effects

Lypophilicity

Lypophilicity is the measure of the drug’s solubility in lipid memberanes. The parameters that represent lypophilicity are – i) Partition Coefficients (P)

ii) Lypophilicity substituent constant (π)

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Partition Coefficient (P)A drug has to pass through a number of biological membranes in order to reach its site of action. Consequently, organic medium or aqueous system partition coefficients were the parameters to use as a measure of the ease of movement of the drug through these membranes. The accuracy of the correlation of drug activity with partition coefficients will depend on the solvent system used as a model for the membrane. A variety of organic solvents, such as n-octanol, chloroform and olive oil, are used to represent the membrane (organic medium), whilst both pure water and buffered solutions are used for the aqueous medium. The n-octanol water system is frequently chosen because it appears to be a good mimic of lipid polarity and has an extensive database.

The nature of the relationship between P and drug activity depends on the range of P values obtained for the compounds used. If this range is small the results may be expressed as a straight line equation having the general form:

log(1/C) = k1 log P + k2 ,where k1 & k2 are constants

This equation indicates a linear relationship between the activity of the drug and its partition coefficient. Over larger ranges of P values the graph of log(1/C) against lop P often has a parabolic form with a maximum value (log P0). The existence of this maximum value implies that there is an optimum balance between aqueous and lipid solubility for maximum biological activity. Below P0 the drug will be reluctant to leave the membrane. Log P0 represents the optimum partition coefficient for biological activity. This means that analogues with partition coefficients near this optimum value are likely to be the most active and worth further investigation. Many of these parabolic relationships could be represented reasonably accurately by equation of the form:

Where k1,k2,k3 are constants that are normally determined by regression analysis.

Lypophilic substituent constants (π)Lipophylic substituent constants are also known as hydrophobic substituent constants. They represent the contribution that a group makes to the partition coefficient and were defined by Hansch and co=workers by the equation:

Where PRH and PRX are the partition coefficients of the standard compound and its monosubstituted derivative respectively. The value of π for a specific substituent will vary with the structural environment of the substituent. The average values or the values relevant to the type of structure being investigated may be used in determining activity relationships. It also depends on the solvent system used to determine the partition coefficients. The values of π will also depend on the solvent system used to determine the partition coefficients used in their calculations. Most values are determined using the n-

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octal/water system. A positive π value indicates that a substituent has a higher lipophylicity than hydrogen and so will probably increase the concentration of the compound in the n-octanol layer and by inference its concentration in the lipid material of biological system. Conversely, a negative π value shows that the substituent has lower lipophylicity than hydrogen and so probably increases the concentration of the compound tin the aqueous media of biological systems. Furthermore, biological activity- π relationships that have high regression constants and low standard deviations demonstrate demonstrate that the substituents are important in determining the lipophylic character of the drug.

Electronic effects

The distribution of the electrons in the drug model has a considerable influence on the distribution and activity of a drug. In general, nonpolar and polar drugs in their unionized form are more readily transported through membranes than polar drugs and drugs in their ionized forms. Furthermore, once the drug reaches its target site the distribution of electrons in its structure will control the type of bond it forms with that target, which in turn effects its biological activity. The first attempt to quantify the electronic affects of groups on the physicochemical properties of compounds was made by Hammet.

The Hammet ConstantThe distribution of electrons within a molecule depends on the nature of the electron withdrawing and donating groups found in that structure. Hammet used this conceptto calculate what are now known as Hammett constants (σx) for a variety of monosubstituted benzoic acids. He used these constants to calculate equilibrium and rate constants for chemical reactions. However, they are now used as parameters in QSAR relationships.

Hammet constants are defined as:

, where KB and BBX are the equilibrium constants for benzoic acid and monosubstituted benzoic acids respectively. Its value varies depending on whether the substituent is an overall electron donor or acceptor. A negative value for σx indicates that the substituent is acting as an electron donor group since Kb>Kbx. Conversely, a positive value for σx shows that the substituent is acting as an electron withdrawing group as KB<KBX. The value of σx for a specific substituent contains both inductive and mesomeric (resonance) contributions, and so varies with the position of that substituent in the molecule.

Steric EffectsThe drug size and shape will determine whether the drug molecule is able to get close enough to its target site in order to bind to that site. The first parameter used to show the relationship between the

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shape and size (bulk) of a drug, the dimensions of its target site and the drug’s activity was the Taft steric parameters (Es).

The Taft Steric ParameterTaft used the relative rate constants of the acid catalysed hydrolysis of α-substituted methyl ethanoates to define his steric parameter because it had been shown that the rates of these hydrolyses were almost entirely dependent on steric factors. He used methyl ethanoate as his standard and defined Es as:

Es = log (kXCH2COOCH3/ kCH3COOCH3) = log kXCH2OOCH3 - log kCH3COOCH3

Where k is the rate constant of the appropriate hydrolysis and the value of E s = 0 when X = CH3. It is assumed that the values for Es obtained for a group using the hydrolysis data are applicable to other structures containing that group. The methyl based Es values can be can be converted to H based values by adding-1.24 to the corresponding methyl based values.

Taft steric parameters have been fond to be useful in a number of investigations but they suffer from one disadvantage that they are determined only by experiments. This has limited the number of values recorded in the literature.

Molar refractivity (MR)The molar refractivity is a measure of both the volume of a compound and how easily it is polarized. It is defined as:

Where n is the refractive index, M the relative mass and ρ the density of the compound. The M/ρ term is a measure of the molar volume whilst the refractive index term is a measure of the polarizability of the compound. Although MR is calculated for the whole molecule, it is an additive parameter, and so the MR values for a molecule can be added together the MR values for its component parts.

Other ParametersThese can be broadly divided into those that apply to sections of the molecule and those that involve the whole molecule. The former include parameters such as van der Waal’s radii, Charton’s steric constants and the Verloop steric parameters.

Hansch Analysis

Hansch analysis attempts to mathematically relate drug activity to measurable chemical properties.

On the basis of this analysis drug action could be divided into two stages:

Transport of the drug to its site of action The binding of the drug to its target site.

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Each of these stages is depended on the chemical and physical properties of the drug and its target site. These properties are described using the parameters discussed above. Hansch postulated that the biological activity of these parameters could be related to these parameters by simple mathematical equations of the format:

Log(1/C) = k1(partition parameter) + k2(electronic parameter) + k3(steric parameter) + k4

Where C is the minimum concentration required to cause a biological response, k1, k2, k3 and k4 are the numerical constants obtained by feeding the values of the parameters selected by the investigating team into a suitable computer statistical package.

The equations derived on the basis of Hansch’s format are called as Hansch equations. These equations often take the general format :

The accuracy of a Hansch equation will depend on :

1. The number of analogues (n) used: the greater the number the higher the probability of obtaining a Hansch equation;

2. The accuracy of the biological data used in the derivation of the equation. The degree of variation normally found in biological measurements means that a statistically viable number of measurements should be taken for each analogue and an average and an average value used in the derivation of the Hansch equation.

3. The choice of parameters.

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S.A.R STUDIES ON MORPHINE ANALOGS

STRUCTURES PROPERTIES

MORPHINE

MORPHINE

Addiction Respiratory depression Nausea Vomiting Cough suppression Sedation Constipation Urinary retention

CODEINE

5x less potent than morphine It is a pro-drug converted to

morphine in vivo. Only 10% converted to morphine

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HYDROMORPHONE

7x more potent than morphine Superior solubility Rapid onset of action Lower side effects

OXYMORPHONE

8x more potent than morphine

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HEROIN

2x more potent than morphine Conversion of two –OH groups to –

OAc facilitates crossing of blood brain barrier

DIHYDROMORPHINE

Stronger than morphine Same side effects as morphine Better euphoriant Less addictive Better bioavailability Longer action (4-7 hrs) Rapid onset of action

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OXYCODONE

Synthesized from Thebaine.

NALTREXONE

NALTREXONE

Is a Morphine antagonist Has higher binding affinity than

morphine. Used for treatment of Drug

addiction.

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NALOXONE

Is a Morphine antagonist Has higher binding affinity than

nalorphine. Used for treatment of Drug

addiction

NALORPHINE

Is a Morphine antagonist Has lower binding affinity than

naloxone. Used for treatment of Drug

addiction

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RESULTUsing the software Marvin Beans , I’ve calculated the drug activity of Morphine and its analogues and following are my readings:

MORPHINE

1] ELEMENT ANALYSIS

Mass = 285.338 Formula = C17H19NO3

Atom count = 40 Composition = C(71.56%),H(6.71%),N(4.91%),O(16.82%)

2] pKa=10.22

3] log P of non-ionic species = 1.53

Log P at pI = 1.26

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4] CHARGE

5] REFRACTIVITY= 80.12

HEROIN

1] ELEMENTARY ANALYSIS

Mass = 369.411 Formula – C21H23NO5

Composition = C(68.28%),H(6.28%),N(3.79%),O(21.66%) Atom Count = 50

2] pKa = 8.95

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3] log P =1.45

4] CHARGE

5] REFRACTIVITY = 98.43

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NALORPHINE

1] ELEMENTARY ANALYSIS

Mass = 327.374 Formula – C19 H21 NO4

Composition = C(69.71%),H(6.47%),N(4.28%),O(19.55%) Atom Count = 45

2] pKa

3] log P = 1.92

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4] CHARGE

4] REFRACTIVITY = 88.2

CONCLUSIONIn Drug discovery, we can identify the lead compound in two ways –

(i) Taking existing structures and modifying them (Scaffold Based Drug Design)(ii) By creating a combinatorial library and screening the compounds for the desired properties.

It can be easily observed that even by slight modification of the structure of a compound, its activity changes completely. An SAR or a QSAR study helps us to identify the lead compounds on the basis of their chemical properties in the form of mathematical values and thus enable a high throughput identification of possible potent leads. In this project, I’ve found that even slight modification in the structure of morphine completely changes its activity, thereby highlighting the importance of chemistry based tools and techniques in the field of medical and pharmaceutical sciences.

Finally it can be concluded that a study of all the possible chemical parameters related to the biological activity of a compound enables us to design a drug so efficient that the moment it enters the body it behaves in a way suited to the environment it is subjected to such as, an acidic environment in the stomach to a basic environment in the intestines so that it moves like a targeted signal with a constant

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efficiency through all biological barriers to reach its target and then to bind to the target with equal ease and trigger a potent response.

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