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HIT TO LEAD
Hit to lead (H2L) also known as lead generation is a stage in
early drug discovery where small molecule hits from a high throughput
screen (HTS) are evaluated and undergo limited optimization to
identify promising lead compounds
These lead compounds undergo more extensive optimization in a
subsequent step of drug discovery called lead optimization (LO).
The drug discovery process generally follows the following path that
includes a hit to lead stage:
target validation (TV) → assay development → high-throughput
screening → hit to lead (H2L) → lead optimization (LO) → preclinical
drug development → clinical drug development
The hit to lead stage starts with confirmation and evaluation of
the initial screening hits and is followed by synthesis
of analogs (hit expansion).
Typically the initial screening hits display binding affinities for
their biological target in the micromolar (10−6 molar
concentration) range. Through limited H2L optimization, the
affinities of the hits are often improved by several orders of
magnitude to the nanomolar (10−9 M) range.
The hits also undergo limited optimization to
improve metabolic half life so that the compounds can be
tested in animal models of disease and also to
improve selectivity against other biological targets binding that
may result in undesirable side effects.
On average, only one in every 5,000 compounds that
enters drug discovery to the stage of pre-clinical
Hit confirmation
After hits are identified from a high throughput screen, the
hits are confirmed and evaluated using the following
methods:
Confirmatory testing: compounds that were found active
against the selected target are re-tested using the same
assay conditions used during the HTS to make sure that
the activity is reproducible.
Dose response curve: the compound is tested over a
range of concentrations to determine the concentration
that results in half maximal binding or activity
(IC50 or EC50 value respectively).
Orthogonal testing: confirmed hits are assayed using a
different assay which is usually closer to the target
physiological condition or using a different technology.
Secondary screening: confirmed hits are tested in a
functional cellular assay to determine efficacy.
Synthetic tractability: medicinal chemists evaluate
compounds according to their synthesis feasibility and other
parameters such as up-scaling or cost of goods.
Biophysical testing: nuclear magnetic
resonance (NMR), isothermal titration
calorimetry (ITC), dynamic light scattering (DLS), surface
plasmon resonance (SPR), dual polarisation
interferometry (DPI), microscale thermophoresis (MST) are
commonly used to assess whether the compound binds
effectively to the target, the kinetics,thermodynamics,
and stoichiometry of binding, any associated conformational
change and to rule out promiscuous binding.
Hit ranking and clustering: Confirmed hit compounds are
then ranked according to the various hit confirmation
experiments.
Freedom to operate evaluation: hit structures are checked in
specialized databases to determine if they are patentable
Hit expansion
Following hit confirmation, several compound clusters will
be chosen according to their characteristics in the
previously defined tests. An Ideal compound cluster will
contain members that possess:
high affinity towards the target (less than 1 µM)
selectivity versus other targets
significant efficacy in a cellular assay
druglikeness (moderate molecular weight
and lipophilicity usually estimated as ClogP). Affinity,
molecular weight and lipophilicity can be linked in single
parameter such asligand efficiency and lipophilic efficiency.
low to moderate binding to human serum albumin
low interference with P450 enzymes and P-glycoproteins
low cytotoxicity
metabolic stability
high cell membrane permeability
high water solubility (above 10 µM)
chemical stability
synthetic tractability
patentability
The project team will usually select between three and
six compound series to be further explored. The next
step will allow the testing of analogous compounds to
determine aquantitative structure-activity
relationship (QSAR). Analogs can be quickly selected
from an internal library or purchased from
commercially available sources ("SAR by catalog").
Medicinal chemists will also start synthesizing related
compounds using different methods such
as combinatorial chemistry, high-throughput chemistry,
or more classical organic chemistry synthesis.
Lead optimization phase
The objective of this drug discovery phase is to
synthesize lead compounds, new analogs with improved
potency, reduced off-target activities, and
physiochemical/metabolic properties suggestive of
reasonable in vivo pharmacokinetics. This optimization
is accomplished through chemical modification of the hit
structure, with modifications chosen by employing
knowledge of the structure-activity relationship (SAR) as
well as structure-based design if structural information
about the target is available.
Lead optimization is concerned with experimental testing
and confirmation of the compound based on animal
efficacy models and ADMET (in vitro and in situ) tools.
Application of ADME-Tox tools has increased the success
rate of drug development as well as helped in reducing the
cost and time factors. The use of in silico and in
vitro ADME-Tox has found universal acceptance. In
silico tools provide a much higher throughput, but they
suffer from adequate predictability, which limits their use.
However, the reliance onin silico models is due to their
ability to predict which compounds should be synthesized
based on confirmed hits and structural modifications since it
helps in selecting a drug-like compound.
The best way to implement the ADME-Tox property
prediction is the integration of both in silico and in
vitro approaches to supplement each other for the
production of candidate drugs.
CHEMINFORMATICS
Cheminformatics (also known as chemoinformatics, chemioinformatics and chemical informatics) is
the use of computer and
informational techniques applied to a range of problems in the field of chemistry.
These in silico techniques are used in, for example, pharmaceutical companies in the process of drug
discovery.
These methods can also be used in chemical and allied industries in various other forms.
History
The term chemoinformatics was defined by F.K. Brown in 1998:
Chemoinformatics is the mixing of those information resources to transform data into information
and information into knowledge for the intended purpose of making better decisions faster in the area of
drug lead identification and optimization.
Since then, both spellings have been used, and some have evolved to be established as Cheminformatics,
while European Academia settled in 2006 for Chemoinformatics.
The recent establishment of the Journal of Cheminformatics is a strong push towards the shorter variant.
Basics
Cheminformatics combines the scientific working fields of chemistry, computer science and information
science
for example in the areas of topology, chemical graph theory,information retrieval and data mining in
the chemical space.
Cheminformatics can also be applied to data analysis for various industries like paper and pulp, dyes and
such allied industries.
Drug design, sometimes referred to as rational drug design or
simply rational design, is the inventive process of finding
new medications based on the knowledge of a biological target. The drug
is most commonly an organic small molecule that activates or inhibits the
function of a biomolecule such as a protein, which in turn results in
a therapeutic benefit to the patient. In the most basic sense, drug design
involves the design of molecules that are complementary
in shape and charge to the biomolecular target with which they interact
and therefore will bind to it.
Drug design frequently but not necessarily relies oncomputer
modeling techniques. This type of modeling is often referred to
as computer-aided drug design. Finally, drug design that relies on the
knowledge of the three-dimensional structure of the biomolecular target is
known as structure-based drug design.
In addition to small molecules, biopharmaceuticals and
especially therapeutic antibodies are an increasingly important class of
drugs and computational methods for improving the affinity, selectivity,
and stability of these protein-based therapeutics have also been
The phrase "drug design" is to some extent a misnomer. A more
accurate term is ligand design (i.e., design of a molecule that will bind
tightly to its target).[4] Although design techniques for prediction of
binding affinity are reasonably successful, there are many other
properties, such as bioavailability, metabolic half-life, side effects, etc.,
that first must be optimized before a ligand can become a safe and
efficacious drug. These other characteristics are often difficult to predict
with rational design techniques.
Nevertheless, due to high attrition rates, especially during clinical
phases of drug development, more attention is being focused early in
the drug design process on selecting candidate drugs
whose physicochemical properties are predicted to result in fewer
complications during development and hence more likely to lead to an
approved, marketed drug.
Furthermore, in vitro experiments complemented with computation
methods are increasingly used in early drug discovery to select
compounds with more favorable ADME (absorption, distribution,
metabolism, and excretion) and toxicological profiles
Drug discovery cycle highlighting both ligand-based (indirect) and structure-
based (direct) drug design strategies.
Drug development is the process of
bringing a new pharmaceutical drug to
the market once a lead compound has
been identified through the process
of drug discovery. It includes pre-
clinical research on microorganisms
and animals, clinical trials on humans,
and may include the step of
obtaining regulatory approval to market
the drug.
Timeline showing the various drug approval tracks and research phases
Drug metabolism also known as xenobiotic metabolism is
the biochemical modification of pharmaceutical
substances or xenobioticsrespectively by living organisms, usually through
specialized enzymatic systems. Drug metabolism often
converts lipophilic chemical compounds into more
readily excreted hydrophilic products. The rate of metabolism determines the
duration and intensity of a drug's pharmacological action.
Cytochrome P450 oxidases are important enzymes in xenobioticmetabolism.
Phases I and II of the metabolism of a lipophilic xenobiotic.
Mechanism Involved enzyme[8] Co-factor[8] Location[8]
methylation methyltransferase S-adenosyl-L-methionine liver, kidney, lung, CNS
sulphation sulfotransferases 3'-phosphoadenosine-5'-phosphosulfate liver, kidney, intestine
acetylation
•N-acetyltransferases
•bile acid-CoA:amino acid N-
acyltransferases
acetyl coenzyme A
liver, lung, spleen, gastric
mucosa, RBCs, lymphocytes
glucuronidation UDP-glucuronosyltransferases UDP-glucuronic acid
liver, kidney, intestine, lung, skin,
prostate, brain
glutathione conjugation glutathione S-transferases glutathione liver, kidney
glycine conjugation acetyl Co-enzyme As glycine liver, kidney
High-content screening (HCS), also known as high-content analysis (HCA)
or cellomics, is a method that is used in biological research and drug discovery to
identify substances such as small molecules, peptides, or RNAi that alter
the phenotype of a cell in a desired manner.
Hence high content screening is a type of phenotypic screenconducted in cells.
Phenotypic changes may include increases or decreases in the production of cellular
products such as proteins and/or changes in the morphology (visual appearance) of
the cell. High content screening includes any method used to analyze whole cells or
components of cells with simultaneous readout of several parameters. Hence the
name "high content screening". Unlike high-content analysis, high-content screening
implies a level of throughput which is why the term "screening" differentiates HCS
from HCA, which may be high in content but low in throughput.
In high content screening, cells are first incubated with the substance and after a
period of time, structures and molecular components of the cells are analyzed. The
most common analysis involves labeling proteins with fluorescent tags, and finally
changes in cell phenotype are measured using automated image analysis. Through
the use of fluorescent tags with different absorption and emission maxima, it is
possible to measure several different cell components in parallel. Furthermore, the
imaging is able to detect changes at a subcellular level
(e.g., cytoplasm vs. nucleus vs. other organelles). Therefore a large number of data
points can be collected per cell. In addition to fluorescent labeling, various label free
assays have been used in high content screening
High-throughput screening (HTS) is a method for
scientific experimentation especially used in drug
discovery and relevant to the fields of biology and chemistry.
Using robotics, data processing and control software, liquid
handling devices, and sensitive detectors, High-throughput
screening allows a researcher to quickly conduct millions of
chemical, genetic, or pharmacological tests.
Through this process one can rapidly identify active
compounds, antibodies, or genes that modulate a particular
biomolecular pathway. The results of these experiments
provide starting points for drug design and for understanding
the interaction or role of a particular biochemical process in
biology.
High-throughput screening robots
Fragment-based lead discovery (FBLD) also known
as fragment-based drug discovery (FBDD) is a method used
for finding lead compounds as part of the drug
discoveryprocess.
It is based on identifying small chemical fragments, which may
bind only weakly to the biological target, and then growing
them or combining them to produce a lead with a higher
affinity. FBLD can be compared with high-throughput
screening (HTS).
In HTS, libraries with up to millions of compounds, with
molecular weights of around 500 Da, are screened, and
nanomolar binding affinities are sought. In contrast, in the early
phase of FBLD, libraries with a few thousand compounds with
molecular weights of around 200 Da may be screened, and
millimolar affinities can be considered useful.
In drug development, pre-clinical development,
also named preclinical studies and nonclinical
studies, is a stage of research that begins
before clinical trials (testing in humans) can begin,
and during which important feasibility, iterative
testing and drug safety data is collected.
The main goals of pre-clinical studies are to
determine the safe dose for First-in-man study and
start to assess product's safety profile. Products
may include new or iterated or like-kind medical
devices, drugs, gene therapy solutions, etc.
On average, only one in every 5,000 compounds
that enters drug discovery to the stage of pre-
clinical development becomes an approved drug
Drug design, sometimes referred to as rational drug design or
simply rational design, is the inventive process of finding
new medications based on the knowledge of a biological target.[1] The
drug is most commonly an organic small molecule that activates or
inhibits the function of a biomolecule such as a protein, which in turn
results in a therapeutic benefit to the patient. In the most basic sense,
drug design involves the design of molecules that are complementary
in shape and charge to the biomolecular target with which they interact
and therefore will bind to it.
Drug design frequently but not necessarily relies oncomputer
modeling techniques.This type of modeling is often referred to
as computer-aided drug design. Finally, drug design that relies on the
knowledge of the three-dimensional structure of the biomolecular target is
known as structure-based drug design.
In addition to small molecules, biopharmaceuticals and
especially therapeutic antibodies are an increasingly important class of
drugs and computational methods for improving the affinity, selectivity,
and stability of these protein-based therapeutics have also been
Diagram showing how structure-based
drug design affects enzyme function
Small molecule design consists of assembly, docking, and scoring. Since Rosetta
already has a docking algorithm (RosettaLigand) and a scoring framework, ...
Computational drug design
Structure Based Drug Design: The iterative process whereby compounds
generated by molecular modeling are synthesized and crystallized with their
A schematic illustration of the method of fragment-based screening and drug design.
Initially, a fragment is identified in a screening effort. At the subsequent stages the
fragment may be modified for more efficient binding and further "grown" to cover the
whole ligand binding site.
Flow chart for structure based drug design
principle of the INPHARMA NOEs.
SUMMARY
Target Type
What is meant by the term ‘challenging target’?
Initial fragment screening campaigns focused on kinases
These have clearly defined ATP pockets and are
considered more druggable
Typical hit rate: 5-10%
Protein-protein interactions are more difficult to target as
these do not have clearly defined pockets. These tend to
have ‘hot-spots’ on the protein surface where binding
occurs
Typical hit rate: 0.1-4%
CYP121
(Metalloprotein)
Hit rate 3.9%
CDK
(Kinase)
Hit rate 8.7%
RAD51-BRCA2
(Protein-Protein Interaction)
Hit rate 0.2 %
Few slides of
Case study
Fragment Elaboration
This is the most frequent method of increasing potency for a fragment and a number of successful fragment campaigns
have been carried out using this strategy
Typically a single fragment in a binding pocket is ‘grown’ using chemical synthesis to pick up further interactions with the
protein.
This is the case that is the most likely to arise where a single fragment binds to protein or multiple fragments bind to a
specific area of the binding pocket
Structural information on how the ligand binds to the protein is key to guiding fragment development
Enzyme
Enzyme
Fragment A
Fragment Growing
Fragment Growing –Kinases (CDK2)
Human Kinome
ATP
ADP
General phosphorylation reaction catalysed by kinases
The first targets that were screened using a fragment
based approach were kinases.
In many cases a key chemotype mimicking the
aminopurine ring typically comes out these fragment
screens
Typically the hit-rate for kinases are high due to the nature
of the ATP binding pocket
A major problem in targeting kinases is selectivity
(over 500 in human genome)
CDK2
Fragment Library
500 Fragments
Primary Screening
X-Ray crystallography
(Cocktails of 4 fragments)
X-Ray Crystallography
Isothermal titration calorimetry (ITC)
500 Fragments
>30 Fragments
4 Fragments
With companies such as Astex the screening
is carried out using X-ray crystallography
where the fragment are screened in cocktails
With this type of screening it is important to
ensure when cocktailing there is sufficient
fragment difference to ensure that when the
hits are deconvoluted that the fragment can
be identified
In some cases fragment libraries containing
Br modified fragments is used
Fragment Growing – CDK2 (Astex)
The fragment library was composed of a focused
kinase set, a drug fragment set and compounds
identified by virtual screening against a structure of
CDK 2
Small fragment library size
Fragment Screening Cascade - CDK2
Fragment Screening – X-ray crystallography
How are these fragments binding to
CDK2?
Fragment Growing – CDK Series 3
IC50 185 mM
LE 0.57
IC50 3 mM
LE 0.42
IC50 97 mM
LE 0.39
IC50 3 nM
LE 0.45
IC50 47 nM
LE 0.40
AT7519
Fragment growing of the initial indazole hit led to a compound with a 50 fold increase in potency. Removal of the phenyl
ring of the indazole offered a new startpoint and this was subsequently elaborated to a compound with a IC50 of 47 nM
with only a small drop in LE (AT7519)
Interestingly the piperidine is protruding out of the pocket toward solvent and the two chlorine atoms in the 2 and 6
position of the phenyl ring fill small hydrophobic pockets on the protein
AT7519 is currently in Phase II clinical trials and has shown good indications against a range of human tumor cell lines
The structure of AT7519 makes amenable to scale-up which is important in the later stage clinical trials
Series 3
THANKS
amcrasto@gmail.co
m

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Drug discovery hit to lead

  • 1.
  • 2.
  • 3. HIT TO LEAD Hit to lead (H2L) also known as lead generation is a stage in early drug discovery where small molecule hits from a high throughput screen (HTS) are evaluated and undergo limited optimization to identify promising lead compounds These lead compounds undergo more extensive optimization in a subsequent step of drug discovery called lead optimization (LO). The drug discovery process generally follows the following path that includes a hit to lead stage: target validation (TV) → assay development → high-throughput screening → hit to lead (H2L) → lead optimization (LO) → preclinical drug development → clinical drug development
  • 4.
  • 5.
  • 6. The hit to lead stage starts with confirmation and evaluation of the initial screening hits and is followed by synthesis of analogs (hit expansion). Typically the initial screening hits display binding affinities for their biological target in the micromolar (10−6 molar concentration) range. Through limited H2L optimization, the affinities of the hits are often improved by several orders of magnitude to the nanomolar (10−9 M) range. The hits also undergo limited optimization to improve metabolic half life so that the compounds can be tested in animal models of disease and also to improve selectivity against other biological targets binding that may result in undesirable side effects. On average, only one in every 5,000 compounds that enters drug discovery to the stage of pre-clinical
  • 7.
  • 8. Hit confirmation After hits are identified from a high throughput screen, the hits are confirmed and evaluated using the following methods: Confirmatory testing: compounds that were found active against the selected target are re-tested using the same assay conditions used during the HTS to make sure that the activity is reproducible. Dose response curve: the compound is tested over a range of concentrations to determine the concentration that results in half maximal binding or activity (IC50 or EC50 value respectively). Orthogonal testing: confirmed hits are assayed using a different assay which is usually closer to the target physiological condition or using a different technology. Secondary screening: confirmed hits are tested in a functional cellular assay to determine efficacy.
  • 9.
  • 10. Synthetic tractability: medicinal chemists evaluate compounds according to their synthesis feasibility and other parameters such as up-scaling or cost of goods. Biophysical testing: nuclear magnetic resonance (NMR), isothermal titration calorimetry (ITC), dynamic light scattering (DLS), surface plasmon resonance (SPR), dual polarisation interferometry (DPI), microscale thermophoresis (MST) are commonly used to assess whether the compound binds effectively to the target, the kinetics,thermodynamics, and stoichiometry of binding, any associated conformational change and to rule out promiscuous binding. Hit ranking and clustering: Confirmed hit compounds are then ranked according to the various hit confirmation experiments. Freedom to operate evaluation: hit structures are checked in specialized databases to determine if they are patentable
  • 11.
  • 12. Hit expansion Following hit confirmation, several compound clusters will be chosen according to their characteristics in the previously defined tests. An Ideal compound cluster will contain members that possess: high affinity towards the target (less than 1 µM) selectivity versus other targets significant efficacy in a cellular assay druglikeness (moderate molecular weight and lipophilicity usually estimated as ClogP). Affinity, molecular weight and lipophilicity can be linked in single parameter such asligand efficiency and lipophilic efficiency. low to moderate binding to human serum albumin low interference with P450 enzymes and P-glycoproteins low cytotoxicity
  • 13. metabolic stability high cell membrane permeability high water solubility (above 10 µM) chemical stability synthetic tractability patentability The project team will usually select between three and six compound series to be further explored. The next step will allow the testing of analogous compounds to determine aquantitative structure-activity relationship (QSAR). Analogs can be quickly selected from an internal library or purchased from commercially available sources ("SAR by catalog"). Medicinal chemists will also start synthesizing related compounds using different methods such as combinatorial chemistry, high-throughput chemistry, or more classical organic chemistry synthesis.
  • 14. Lead optimization phase The objective of this drug discovery phase is to synthesize lead compounds, new analogs with improved potency, reduced off-target activities, and physiochemical/metabolic properties suggestive of reasonable in vivo pharmacokinetics. This optimization is accomplished through chemical modification of the hit structure, with modifications chosen by employing knowledge of the structure-activity relationship (SAR) as well as structure-based design if structural information about the target is available. Lead optimization is concerned with experimental testing and confirmation of the compound based on animal efficacy models and ADMET (in vitro and in situ) tools.
  • 15.
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  • 17.
  • 18.
  • 19. Application of ADME-Tox tools has increased the success rate of drug development as well as helped in reducing the cost and time factors. The use of in silico and in vitro ADME-Tox has found universal acceptance. In silico tools provide a much higher throughput, but they suffer from adequate predictability, which limits their use. However, the reliance onin silico models is due to their ability to predict which compounds should be synthesized based on confirmed hits and structural modifications since it helps in selecting a drug-like compound. The best way to implement the ADME-Tox property prediction is the integration of both in silico and in vitro approaches to supplement each other for the production of candidate drugs.
  • 20.
  • 21.
  • 22. CHEMINFORMATICS Cheminformatics (also known as chemoinformatics, chemioinformatics and chemical informatics) is the use of computer and informational techniques applied to a range of problems in the field of chemistry. These in silico techniques are used in, for example, pharmaceutical companies in the process of drug discovery. These methods can also be used in chemical and allied industries in various other forms. History The term chemoinformatics was defined by F.K. Brown in 1998: Chemoinformatics is the mixing of those information resources to transform data into information and information into knowledge for the intended purpose of making better decisions faster in the area of drug lead identification and optimization. Since then, both spellings have been used, and some have evolved to be established as Cheminformatics, while European Academia settled in 2006 for Chemoinformatics. The recent establishment of the Journal of Cheminformatics is a strong push towards the shorter variant. Basics Cheminformatics combines the scientific working fields of chemistry, computer science and information science for example in the areas of topology, chemical graph theory,information retrieval and data mining in the chemical space. Cheminformatics can also be applied to data analysis for various industries like paper and pulp, dyes and such allied industries.
  • 23. Drug design, sometimes referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies oncomputer modeling techniques. This type of modeling is often referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been
  • 24. The phrase "drug design" is to some extent a misnomer. A more accurate term is ligand design (i.e., design of a molecule that will bind tightly to its target).[4] Although design techniques for prediction of binding affinity are reasonably successful, there are many other properties, such as bioavailability, metabolic half-life, side effects, etc., that first must be optimized before a ligand can become a safe and efficacious drug. These other characteristics are often difficult to predict with rational design techniques. Nevertheless, due to high attrition rates, especially during clinical phases of drug development, more attention is being focused early in the drug design process on selecting candidate drugs whose physicochemical properties are predicted to result in fewer complications during development and hence more likely to lead to an approved, marketed drug. Furthermore, in vitro experiments complemented with computation methods are increasingly used in early drug discovery to select compounds with more favorable ADME (absorption, distribution, metabolism, and excretion) and toxicological profiles
  • 25.
  • 26. Drug discovery cycle highlighting both ligand-based (indirect) and structure- based (direct) drug design strategies.
  • 27. Drug development is the process of bringing a new pharmaceutical drug to the market once a lead compound has been identified through the process of drug discovery. It includes pre- clinical research on microorganisms and animals, clinical trials on humans, and may include the step of obtaining regulatory approval to market the drug.
  • 28. Timeline showing the various drug approval tracks and research phases
  • 29. Drug metabolism also known as xenobiotic metabolism is the biochemical modification of pharmaceutical substances or xenobioticsrespectively by living organisms, usually through specialized enzymatic systems. Drug metabolism often converts lipophilic chemical compounds into more readily excreted hydrophilic products. The rate of metabolism determines the duration and intensity of a drug's pharmacological action. Cytochrome P450 oxidases are important enzymes in xenobioticmetabolism.
  • 30. Phases I and II of the metabolism of a lipophilic xenobiotic.
  • 31. Mechanism Involved enzyme[8] Co-factor[8] Location[8] methylation methyltransferase S-adenosyl-L-methionine liver, kidney, lung, CNS sulphation sulfotransferases 3'-phosphoadenosine-5'-phosphosulfate liver, kidney, intestine acetylation •N-acetyltransferases •bile acid-CoA:amino acid N- acyltransferases acetyl coenzyme A liver, lung, spleen, gastric mucosa, RBCs, lymphocytes glucuronidation UDP-glucuronosyltransferases UDP-glucuronic acid liver, kidney, intestine, lung, skin, prostate, brain glutathione conjugation glutathione S-transferases glutathione liver, kidney glycine conjugation acetyl Co-enzyme As glycine liver, kidney
  • 32. High-content screening (HCS), also known as high-content analysis (HCA) or cellomics, is a method that is used in biological research and drug discovery to identify substances such as small molecules, peptides, or RNAi that alter the phenotype of a cell in a desired manner. Hence high content screening is a type of phenotypic screenconducted in cells. Phenotypic changes may include increases or decreases in the production of cellular products such as proteins and/or changes in the morphology (visual appearance) of the cell. High content screening includes any method used to analyze whole cells or components of cells with simultaneous readout of several parameters. Hence the name "high content screening". Unlike high-content analysis, high-content screening implies a level of throughput which is why the term "screening" differentiates HCS from HCA, which may be high in content but low in throughput. In high content screening, cells are first incubated with the substance and after a period of time, structures and molecular components of the cells are analyzed. The most common analysis involves labeling proteins with fluorescent tags, and finally changes in cell phenotype are measured using automated image analysis. Through the use of fluorescent tags with different absorption and emission maxima, it is possible to measure several different cell components in parallel. Furthermore, the imaging is able to detect changes at a subcellular level (e.g., cytoplasm vs. nucleus vs. other organelles). Therefore a large number of data points can be collected per cell. In addition to fluorescent labeling, various label free assays have been used in high content screening
  • 33.
  • 34. High-throughput screening (HTS) is a method for scientific experimentation especially used in drug discovery and relevant to the fields of biology and chemistry. Using robotics, data processing and control software, liquid handling devices, and sensitive detectors, High-throughput screening allows a researcher to quickly conduct millions of chemical, genetic, or pharmacological tests. Through this process one can rapidly identify active compounds, antibodies, or genes that modulate a particular biomolecular pathway. The results of these experiments provide starting points for drug design and for understanding the interaction or role of a particular biochemical process in biology.
  • 36. Fragment-based lead discovery (FBLD) also known as fragment-based drug discovery (FBDD) is a method used for finding lead compounds as part of the drug discoveryprocess. It is based on identifying small chemical fragments, which may bind only weakly to the biological target, and then growing them or combining them to produce a lead with a higher affinity. FBLD can be compared with high-throughput screening (HTS). In HTS, libraries with up to millions of compounds, with molecular weights of around 500 Da, are screened, and nanomolar binding affinities are sought. In contrast, in the early phase of FBLD, libraries with a few thousand compounds with molecular weights of around 200 Da may be screened, and millimolar affinities can be considered useful.
  • 37.
  • 38. In drug development, pre-clinical development, also named preclinical studies and nonclinical studies, is a stage of research that begins before clinical trials (testing in humans) can begin, and during which important feasibility, iterative testing and drug safety data is collected. The main goals of pre-clinical studies are to determine the safe dose for First-in-man study and start to assess product's safety profile. Products may include new or iterated or like-kind medical devices, drugs, gene therapy solutions, etc. On average, only one in every 5,000 compounds that enters drug discovery to the stage of pre- clinical development becomes an approved drug
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44.
  • 45.
  • 46.
  • 47.
  • 48.
  • 49. Drug design, sometimes referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target.[1] The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies oncomputer modeling techniques.This type of modeling is often referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been
  • 50.
  • 51.
  • 52.
  • 53.
  • 54.
  • 55.
  • 56.
  • 57.
  • 58. Diagram showing how structure-based drug design affects enzyme function
  • 59. Small molecule design consists of assembly, docking, and scoring. Since Rosetta already has a docking algorithm (RosettaLigand) and a scoring framework, ...
  • 60.
  • 62.
  • 63. Structure Based Drug Design: The iterative process whereby compounds generated by molecular modeling are synthesized and crystallized with their
  • 64.
  • 65.
  • 66. A schematic illustration of the method of fragment-based screening and drug design. Initially, a fragment is identified in a screening effort. At the subsequent stages the fragment may be modified for more efficient binding and further "grown" to cover the whole ligand binding site.
  • 67.
  • 68. Flow chart for structure based drug design
  • 69.
  • 70.
  • 71.
  • 72.
  • 73.
  • 74.
  • 75.
  • 76.
  • 77.
  • 78.
  • 79.
  • 80.
  • 81.
  • 82.
  • 83.
  • 84. principle of the INPHARMA NOEs.
  • 86. Target Type What is meant by the term ‘challenging target’? Initial fragment screening campaigns focused on kinases These have clearly defined ATP pockets and are considered more druggable Typical hit rate: 5-10% Protein-protein interactions are more difficult to target as these do not have clearly defined pockets. These tend to have ‘hot-spots’ on the protein surface where binding occurs Typical hit rate: 0.1-4% CYP121 (Metalloprotein) Hit rate 3.9% CDK (Kinase) Hit rate 8.7% RAD51-BRCA2 (Protein-Protein Interaction) Hit rate 0.2 % Few slides of Case study
  • 87. Fragment Elaboration This is the most frequent method of increasing potency for a fragment and a number of successful fragment campaigns have been carried out using this strategy Typically a single fragment in a binding pocket is ‘grown’ using chemical synthesis to pick up further interactions with the protein. This is the case that is the most likely to arise where a single fragment binds to protein or multiple fragments bind to a specific area of the binding pocket Structural information on how the ligand binds to the protein is key to guiding fragment development Enzyme Enzyme Fragment A Fragment Growing
  • 88. Fragment Growing –Kinases (CDK2) Human Kinome ATP ADP General phosphorylation reaction catalysed by kinases The first targets that were screened using a fragment based approach were kinases. In many cases a key chemotype mimicking the aminopurine ring typically comes out these fragment screens Typically the hit-rate for kinases are high due to the nature of the ATP binding pocket A major problem in targeting kinases is selectivity (over 500 in human genome)
  • 89. CDK2 Fragment Library 500 Fragments Primary Screening X-Ray crystallography (Cocktails of 4 fragments) X-Ray Crystallography Isothermal titration calorimetry (ITC) 500 Fragments >30 Fragments 4 Fragments With companies such as Astex the screening is carried out using X-ray crystallography where the fragment are screened in cocktails With this type of screening it is important to ensure when cocktailing there is sufficient fragment difference to ensure that when the hits are deconvoluted that the fragment can be identified In some cases fragment libraries containing Br modified fragments is used Fragment Growing – CDK2 (Astex) The fragment library was composed of a focused kinase set, a drug fragment set and compounds identified by virtual screening against a structure of CDK 2 Small fragment library size Fragment Screening Cascade - CDK2 Fragment Screening – X-ray crystallography How are these fragments binding to CDK2?
  • 90. Fragment Growing – CDK Series 3 IC50 185 mM LE 0.57 IC50 3 mM LE 0.42 IC50 97 mM LE 0.39 IC50 3 nM LE 0.45 IC50 47 nM LE 0.40 AT7519 Fragment growing of the initial indazole hit led to a compound with a 50 fold increase in potency. Removal of the phenyl ring of the indazole offered a new startpoint and this was subsequently elaborated to a compound with a IC50 of 47 nM with only a small drop in LE (AT7519) Interestingly the piperidine is protruding out of the pocket toward solvent and the two chlorine atoms in the 2 and 6 position of the phenyl ring fill small hydrophobic pockets on the protein AT7519 is currently in Phase II clinical trials and has shown good indications against a range of human tumor cell lines The structure of AT7519 makes amenable to scale-up which is important in the later stage clinical trials Series 3