fun facts 2-4 Flashcards
drug target characteristics
- good ip status
- promising toxicity profile
- confirmed role
- easily assayable with HTS
- 3D structure available 4 druggability
- uneven target expression// distribution
modern drug discovery
target identification (f+r)
target characterisation ( c the mech)
target validation ( mod -> TE)
research and discovery
- target identification
- hit generation
- lead generation
unmet medical need occurance
- no approved molecules
- late stages of clinical trials
- correct dose effects existing molecules
TARGET IDENTIFICATION
IN SILICO
IN LAB
TI SILICO
SILICO SCREENING
MACHINE BASED LEARNING
TI LABORATORY
FUNCTIONAL SCREENING (G KO, KD, OE)
BIOLOGICAL ASSAYS
(EXPRESSION PROFILLING)
TARGET IDENTIFICATION
SIL LAB
SILSCREEN, MBL
BA FS
target validation
chemical
genetic
tv chemical
use of drugs to show inhibition -> inhibition
tv genetic
g kd
g ko
tv validation
in vivo
in vitro
tv val vivo
disease animal model
animal alternatives
tv val vitro
- parameters studied
- function of target when bound to different ligands
- cell + tissu exp
Hit Confirmation
- Confirmatory Testing
- Secondary Screening
- Dr Curves
- Synthetic Tractability
- Freedom To Operate
efficacy
ability for drug - receptor complex to produce max functional response.
Hit Identification Definition
identifying + delivering compound with confirmed activity to a biological target
Hit Identification
- Functional Assays
- Phenotypic Assays
- Ai
Hi
Fa
- HTS
- biochem assays
- in vitro assays
Hi
Pa
- HCI
Hi
Ai
in silico virtual drug discovery
Hi
Expansion
- selectivity
- affinity
- efficacy in assays
- drug likeness
- high cc50
- synthetic tractibility
- patentability
lead compound characteristics
- confirmed potency
- confirmed selectivity
- desired adme
- desired safety profie
- emerging sar
optimise a lc
synthesise a structural varient on it in order to optimise its properties
optimise adme
sar techniques
- FG // alter
+ FG
size and shape (position, chain length, ring systems)
cig lit azone to
rosig lit azone
qsar
quantitative.
math relationship between structure and physiochem properties // patameters
parameter
numbers that rep a molecular property
parameter examples
e- distribution
shape
lipophilicity
lipo parameter
log p
partition coefficient
log [ octantol ] // [ aq buffer]
size parameter
- molecular weight
- molecular volume
- surface area
electronic parameter
HAMMETT CONSTANTS
measure e- wd // e- donation
structural parameter
h bond donors
h bond acceptors
rotary bonds
lipinskis rule of 5
log p < 5
mol weight < 500
5 h donors
10 h acceptors
rule for oral drugs
predicts if compound will be drug like
modelling
3D qsar
- design new molecules based on receptor pharmacophore (u dont know receptor structure)
model receptors
- generate 3d receptor models based off 3d pharmacophore + place aa side chains appropriately.
virtual screening
pharmacophore matching: screen data bases for those with desired pharmacophores
docking calculations:
receptor is known. computer positions ligands in receptor sites and rates them based on binding strength.
what is a pharmacophore
abstract description of molecular features
