Pharmacology Flashcards
1
Q
Agonist
A
Can be full or partial causing an increase in chemical reaction. Partial agonist is especially beneficial for drugs as it works as a safety mechanism to avoid maximal response with faster onset.
2
Q
Selective antagonist
A
Another name for partial agonist as when the efficiency is low, it leads to lack of binding
3
Q
Key for understanding drug response
A
- there is an optimal concentration for the best response (inverted U)
- Readout is important, is it truly measuring the response?Maybe only 10% needs to be occupied for 100% response=> Occupancy =/= biological readout
- Location and/or subtypes of receptors, is drug hitting the target?
- Drug concentration is not proportionate to 50% occupancy (10% of drug concentration may be enough to half the 50% occupancy) => Concentratiom =/= occupancy
4
Q
Antagonist
A
Can be competitive (eversible or irreversible) or allosteric(/non-competitive). Does nothing to the receptor just blocks the agonist binding
5
Q
classic vs expanded drug model
A
Classical: ago & antag
Expanded: variance in binding efficiency of ago & antago e.g. insulin receptor via tyrosine kinase receptor
6
Q
tyrosine kinase receptor
A
Activation steps
1. Binding of ligand (e.g. insulin)
2. Two agonist binding monomer creates dimer
3. Activation by dimerisation /cross-phosphorylatedof tyrosine
4. Leads to activation of relay proteins (RTK signalling)
Agonist: brings two monomers together
Antagonist: just blocks, nothing else
Inverse agonist: separates the monomers away
7
Q
Cis vs transphosphorylation
A
cis autophosphorylation… kinases’ own active site catalyzes the phosphorylation reaction
trans autophosphorylation…another kinase of the same type provides the active site that carries out the chemistry
8
Q
Drug efficacy as continuum
A
Full ago - partial ago - antag - partial inverse ago - full inverse ago
9
Q
Life cycle of a drug
A
Application/Administration
- > resorption吸収
- > Distribution
- > (biotransformation)
- > excretion/disposition/elimination
10
Q
Pharmacokinetics vs pharmacodynamics
A
Both are measure for pharmacological effect Kin: what body does to the drug 1) absorption-via skin?blood? 2) distribution & storage-efficiency 3) excretion/metabolic elimination - lasting duration Dyn: what drug does to the body 1) doses 2) receptor-behaviour 3) non-R mediated effects
11
Q
How can drug work
A
A+R <=> AR <=> AR* 1st arrow: occupation governed by affinity dissociation constant Kd = K+1/K-1 2nd arrow: activation governed by efficacy
12
Q
Binding curve of a drug
A
X log[drug]
Y response/effect
Kd…[] where 1/2 of Rs are bound
Ec…[] where response are 1/2 of max
13
Q
relationship of Ec & Kd
A
Ec < Kd
Kd…[] where 1/2 of Rs are bound
Ec…[] where response are 1/2 of max
2 drugs with similar affinity can have different efficacy
14
Q
Efficacy of partial agonist
A
Efficacy/Intrinsic activity = max effect of partial agonist / max effect of full agonist
15
Q
Antagonist
A
does NOT change active/inactive state
16
Q
Hill-Langmuir equation state
A
State that “proportion of drug-R complex (occupied R) is determined by [Ago] and disassociation rate constant K
pAR = [A]/([A]+Ka)
17
Q
In Hill-Langmuir, if [A] = Ka
A
pAR = 50% (half R are occupied)
18
Q
Dose response curve for reversible competitive antagonism
A
- surmountable antagonism (same max response)
- no change in slope
- affinity modulation (side-way shift)
19
Q
agonist dose ratio
A
Agonist dose ratio increases linearly with [antag]
[ago]needed to achieve a certain response with antag/[ago]necessary w/o antag
20
Q
Dose response curve for irreversible competitive antagonism
A
- insurmountable antagonism (reduced max response)
- change in slope/shallower slope
- efficacy modulation (up-down shift)
21
Q
Dose response curve for non-competitive antagonism
A
Can cause
- affinity modulation
- efficacy modulation
- evoke a response themselves
22
Q
Agonist dose-response curve
A
Can be inverted U shape possibly due to
- increased dosage causing receptor desensitisation
- action on 2nd target protein opposing the effect of 1st
23
Q
Why analyse the full dose-response curve and not with one concentration?
A
To see whether it is simple increase or inverted U to see whether drug sensitivity is increased, decreased or not changed
24
Q
What are the types of administration
A
oral/rectal直腸の -> gut -> plasma percutaneous -> skin -> plasma intravenous -> plasma Intromuscular -> muscle -> plasma Intrathecal -> CSF -> plasma Inhalation -> lung
25
What happens after distribution of drug to plasma?
Plasma -> breast/sweat glands
Elimination via urine, feces, milk, sweat
For inhalation, via expired air
26
Movement of drugs
Drug move around the body via
- bulk flow transfer via blood stream
- diffusional transfer
27
What are "pharmacologically active" drug?
unbound free drug
28
explain D+S <=> DS
D free drug
S binding site on protein e.g. albumin
DS drug-protein complex
29
What does binding depend on?
[D], affinity for binding sites & [protein]
30
Why is lipophilic better?
The more lipophilic, the better penetration into the brain.
| However, some transport system can assist hydrophilic substance to pass at ease
31
What is biotransformation?
The metabolism of drugs
As pure renal elimination drugs (mostly lipophilic) take a long time (-months), the system make the substance more hydrophilic to fasten elimination
32
What is phase 1 of biotransformation?
Introduction/recovery of reactionary groups by cytochrome P450 family
causing:
- oxidation
- reduction
- hydrolysis
- hydratisation
33
What is phase 2 of biotransformation?
Conjugation reaction, in which transferase add f(x)nal groups on to reactionary group from phase one
e.g.
glucuronation
sulfatation
methylation/acetylation
Fxnal groups are often very polar & negatively charged
34
Cytochrome P450
An enzyme found ubiquitously in bacteria, plants & animals
35
Cytochrome P450 in human
Some plants produce substance that are toxic when ingested (e.g phytoalexins)
CYP
- broad specificity as toxins are diverse, a substance that can act on many CYP isoforms
- CYP family 1,2&3 is important for human drug metabolism
- can change in amount via increased gene transcription or decreased degradation
w/ CYP
- absorption @ gut 80%
- > presystemic elimination via CYP @ liver
- > only 5% bioavailability (toxin reaching the plasma) :)
w/o CYP
- absorption @ gut 80%
- > 75% bioavailability which could be above toxic level :(
36
Pharmacogenetics
Study the influence of polymorphism/rare genetic variants on drug metabolism
37
CYP2D6 polymorphism
e. g. of pharmacogenetic research
- 100+ variation found
- metabolise neuroleptics, antidepressants, beta-blockers & opioids
1) extreme slow metabolism 7%: concentration surpass thrapeutic level -> toxic with unwanted side effects
2) slow metab 5-10%: same as above
3) normal metab 80%: therapeutic
4) extreme fast metab 2-3%: concentration does not reach therapeutic level -> no side effect but not effective
38
Pharmacokinetic parameters
Assessment of drug amount in plasma @ absorption, distribution and elimination
1) bioavailability
2) clearance
3) half-life
4) distribution volume
39
Pharmacokinetic parameters: bioavailability
fraction of a substance that reaches the systemic circulation & thereby location of action
=> % of drug that enters blood-stream unaltered
100 for IV applied, lower for per os (orally) or other application
40
AUC
Area Under the Curve (used for bioavailability)
AUC is proportional to amount of substance that reach circulation (= bioavailable amount)
bioavailability f = AUC per os/AUCiv = AUC drugA/ AUC drugB
AUC = Q/CL = dose given/clearance
41
Relationship between absorption rate and bioavailability
INDEPENDENT to each other
| AUC = Q/CL = dose given/clearance
42
How can we say 2 drugs are bioequivalent?
Only if AUC, Cmax (max concentration overtime) & tmax (timepoint where Cmax is hit) are b/w 80-125% from each other
43
What causes reduction in bioavailability?
```
Pre-systemic/first-pass metabolism happens BEFORE initially entering blood stream
e.g.
@gut: degradation by bacteria
@intestinal mucosa粘膜
@liver via portal vein: by CYP
excretion via biliary胆汁 pathway
or direct elimination
```
44
First pass metabolism
First pass refers to the fact that hepatic metabolism happen before the drug enters the circulation for first time. Later in its life, drug will be transported to the liver again for further/final biotransformation
45
Drugs with high first-pass effect
It depends on enzymatic f(x) in liver
- clomethiazol
- Metoprolol
- nifedipin
- pentazocin
- Pethidin
- propranolol
- verapamil
46
Water and whole body weight
Water weight is 50-70% of body weight, There are 0.6L/kg water
47
Where's the body water kept at?
- Plasma (5%)
- Interstitial (16%)
- Fat (20%)
- Intracellular (35%)
- Transcellular (2%)
Transcellular fluids include cerebrospinal, intraocular, peritoneal, pleural
48
How is partitioning of water determined?
Partitioning to which compartments depend on barrier permeability, binding of drugs, fat & pH
49
What is volume of distribution
apparent volume of water needed for [drug] to be equal as in plasma. This is important as free drug molecule is pharmacologically active. This means molecules bound to fat etc needs to be ignored
50
Pharmacokinetic parameters: Clearance
The organism ability to eliminate a drug
| !Beneficial as it involves no kinetics, simply the plasma volume cleared/time (ml/min or L/h)
51
Pure renal 腎臓 clearance =
CLrenol = (Cu * Vu)/Cp = [substance] in urine*urine volume/[substance] in plasma
52
CL total =
CLtotal
= CL renal + CL extrarenal (mostly metabolic elimination by liver)
= Q/AUC = dose given/AUC
53
Rate of drug elimination
Delta Q = Cp * CL tot = [substance] in plasma * CL tot
From this, if drug delivery rate X (mg/h) is constant, Csteady-state is eventually achieved meaning rate of input equals rate of elimination
=> X = Css/CLtot => CL tot = X/Css
54
Clearance understood in 2 ways
1) volume of plasma liberated from drugs/substance over time
| 2) volume of plasma containing the total amount of drug removed from body over time
55
Single compartment model
Drug just simply goes in/out of one compartment (body)
| Parameters involve: Absorption K, Volume distribution, excretion K, metabolism K
56
[drug] in plasma depend on
Q, Vd, & elimination rate
| dosage, volume distribution & elimination rate
57
Bolus
急速静注
| Way of administering drug where [drug] does not gradually increase upon infusioning but goes straight up at timepoint 0
58
Rate of drug elimination for Csteady-state
At t=0 (injection), initial [plasma] C0
Q/C0 = distribution volume
linear decreasing slope between X time Y [plasma] is elimination constant of time = CLtot/Vd
59
Pharmacokinetic parameters: Half-life
time for [drug] to halve in plasma/body
most drug clearance follow first order kinetics meaning speed of decrease in [plasma] is proportional to [plasma]
-delta[A]/delta t = k[A]
decerase is fast at beginning, later the slower (linear relationship when put in log)
60
Half life depends on
Vd & clearance
t1/2 increase w/ Vd
t1/2 decrease w/CL
NOT ON DOSE
The longer the half-life, the longer it takes to reach Css
61
2 drugs with similar half time...
Half-life is a "hybrid" pharmacokinetic parameter meaning 2 drugs with similar half-life can have total different Vd and CL properties
62
Elimination rate constant (/time)
Kel = CLtot/Vd= fraction of drug eliminated /time
- greater the clearance, faster elimination rate
- larger Vd, longer elimination time
63
Zeroth order kinetics
-delta[A]/delta t = k
Drug is eliminated/time independent of [plasma]
e.g. ethanol
Underlying cause is due to the saturation kinetics, the saturation of degrading enzyme or transporter (rate-limiting step)
64
For the drug to work...
it needs to bind to
1) ionchannel
2) GPCR
3) R-tyrosine kinase R
4) nuclear R
65
Saturable binding
Concept that drug can occupy all the site on receptors and the reaction plateaus, it is considered unsaturable if all sites cannot be filled even with excessive amount of ligands
66
Type of drugs
- agonist
- antagonist
- modulators - binds but does not activate only changes the ago response
- competitive antag is completely neutral; no effect on response
67
Kinetics: on rate
- The second-order rate at which a drug binds to a receptor. Limited by diffusion to be 10^8 per second or less. Multiply by concentration to get “forward” binding rate. Units of Molar–1 s–1
- depends on concentration but not the off rate
68
Kinetics: off rate
The first-order rate at which a drug unbinds from a receptor. The inverse of the lifetime of the drug-receptor complex Independent of concentration! Units of s–1
69
Dissociation constant
K = Koff/Kon(M)
Agonist dissociation constant Ka
Antagonist dissociation constant Kb
70
In the ideal world of pharmacology...
we know the full list of all receptors, drugs, Kon, Koff and K value, drug action will be fairly predictable but in reality is not easy to get those info
71
What does smaller Kd mean?
That the binding is tight
| Good drug usually have micro, nanoM value
72
Pitfalls of Hill equation?
does not tell us anything about how the receptor work. E.g. efficacy
73
What is a hill slope?
Used in the Hill equation alteration to derive the generalised version to fit all cases (e.g. cooperative binding of haemoglobin)
It does NOT indicate the number of binding sites, at best it gives a lower estimate of the number of binding sites. This is due to the assumption that all binding sites are either full or empty.
74
Affinity is same as
potency (the binding), K value
75
Efficacy is same as
activity, E value
76
For R <=> AR <=> AR*, what is the difficult information to obtain?
E (AR <=> AR*)
77
Competitive antagonism
- The lifetime of the AR complex largely determines the potency (affinity)
- Weak antagonists unbind quickly (in ms) and can be replaced by agonists
- potent antagonists can stay bound for seconds or minutes
- Tighter bound = higher potency = ideal drug
- Life time (1/Koff) are fixed but Kon is determined by [A] and [B]
- For accurate competitive antagonist constant Kb, Schild method is the best instead of Hill equation or inhibition curve (IC 50)
- Schlid method is a microscopically-exact way to determine the binding constant of a competitive antagonist.
78
Equation that could be used for competitive antagonism
Schlid ( better than Hill or inhibition curve)
79
Schild equation
Explains that occupancy by agonist can be increased against antagonist by increasing [A]
Postulate/Assumption
-Equal response: R response only depends on the average occupancy of the R by A
-Exclusive binding: Binding of competitive B and A are mutually exclusive
-Binding only: B binding does not alter the shape of R
-Equal affinity: If there are multiple sites, B has the same affinity for all sites
-Equilibrium: measurements are made at equilibrium
80
Pitfalls for Schild equation
Explains that occupancy by agonist can be increased against antagonist by increasing [A]
It is a null method: it does not consider [A] and actual response does not matter => making it a reliable, robust method
For potulate,
-Equal response: Usually true
-Exclusive binding: Failure can be observed by insurmoutable antagonism
-Binding only: May be untrue but small effect
-Equal affinity: Usually hold true
-Equilibrium: Hard to obtain
81
IG: Schlid equation special case
Can also be written in log
log(r-1) = log[B] - log(Kb)
meaning when r=2
log[B] - log(Kb); pA = -log[Kb]
82
IG: Schild equation
| As [A] -> infinity
AR -E-> AR*
Par* = E * Par
Par* + Par = 1
Par* = E/(E+1)
83
What is EC50
- [agonist] to induce half the max response
| - it has no relation to KA
84
What is IC50
- [agonist] to reduce response to half max
| - always IC50 >> Kb
85
!!! Schild equation overall
Know that it is for
- competitive antagonist
- corrected on a microscopic level
- linear relationship between [K] and dose
86
IG: Schild equation and [B]
Cb = [B] / Kb
| Almost all experiments were done with [B] > KB
87
Why can we get Kb but not Ka?
- Agonist have 2 properties (affinity and efficacy)
- These two measures are commonly mixed up
- However, a true competitive antagonist have no efficacy
- Therefore only affinity needs to be considered, making it possible to measure
88
How do we know if a drug works?
-We do not know the whole system
-Repetition
-Experiment result is robust (do not get affected by small changes)
-Effect size
Usually effect size is small; error in measure or it could be organismal effect. In neuroscience both effect size as well as sample size could be small (expensive)
-P value
-Causality and association
89
Importance of statistical view
* Being careful with statistics encourages good experimental design
* Some problems are random - statistics are unavoidable.
* Statistics can give an idea of the uncertainty of conclusions.
* Systematic errors may be large, so statistics provide a minimum error. But still be aware of the errors
* Calculations may introduce bias to unbiassed observations.
* Statistics do not prove anything. P is a probability!
90
Why randomise?
-Cohort study: Patients choose their actions and depending on the choice are divided into groups (e.g. smokers vs non-smokers)
=> not suggested for causational study as it creates covariates/prognostic factors. Only associational
-Covariates: changes that occur along something (e.g. smokers are more susceptible to lung cancer not because of smoking but maybe their common characteristics/traits)
-By randomising the sample and having sufficient sample size, bias should be reduced
-Randomisation can reduce effect size but never increase.
-Overall, randomisation may have higher chance of avoiding bias and lead to more accurate statistical results when conducted properly
91
Effect size
how much one group differs from another (e.g. experimental vs control group)
Effect size = Hedge's G = (mean of experimental - mean of control)/standard deviation
92
Sample size & effect size
Larger the sample size, smaller the effect size
| More randomisation, smaller the effect size too
93
Odds ratio
ratio between the chance of an event for two/binary groups = effect
94
Issue with effect size
If sample size is small, it is likely to include some bias
For research, small sample inflate (increase) effect/OR due to an outlier etc
Therefore, researchers choose to conduct research with bigger sample
Although it means smaller effect size
To avoid p value fallacy, calculation of False Positive Risk may be worth calculating, which usually turns out to be about 6x bigger than the p value
