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drug discovery > fun facts 2-4 > Flashcards

fun facts 2-4 Flashcards

1
Q

drug target characteristics

A
  • good ip status
  • promising toxicity profile
  • confirmed role
  • easily assayable with HTS
  • 3D structure available 4 druggability
  • uneven target expression// distribution
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2
Q

modern drug discovery

A

target identification (f+r)

target characterisation ( c the mech)

target validation ( mod -> TE)

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3
Q

research and discovery

A
  • target identification
  • hit generation
  • lead generation
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4
Q

unmet medical need occurance

A
  • no approved molecules
  • late stages of clinical trials
  • correct dose effects existing molecules
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5
Q

TARGET IDENTIFICATION

A

IN SILICO

IN LAB

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6
Q

TI SILICO

A

SILICO SCREENING
MACHINE BASED LEARNING

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7
Q

TI LABORATORY

A

FUNCTIONAL SCREENING (G KO, KD, OE)

BIOLOGICAL ASSAYS
(EXPRESSION PROFILLING)

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8
Q

TARGET IDENTIFICATION

A

SIL LAB

SILSCREEN, MBL

BA FS

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9
Q

target validation

A

chemical
genetic

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10
Q

tv chemical

A

use of drugs to show inhibition -> inhibition

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11
Q

tv genetic

A

g kd
g ko

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12
Q

tv validation

A

in vivo

in vitro

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13
Q

tv val vivo

A

disease animal model
animal alternatives

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14
Q

tv val vitro

A
  • parameters studied
  • function of target when bound to different ligands
  • cell + tissu exp
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15
Q

Hit Confirmation

A
  • Confirmatory Testing
  • Secondary Screening
  • Dr Curves
  • Synthetic Tractability
  • Freedom To Operate
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16
Q

efficacy

A

ability for drug - receptor complex to produce max functional response.

17
Q

Hit Identification Definition

A

identifying + delivering compound with confirmed activity to a biological target

18
Q

Hit Identification

A
  • Functional Assays
  • Phenotypic Assays
  • Ai
19
Q

Hi
Fa

A
  • HTS
  • biochem assays
  • in vitro assays
20
Q

Hi
Pa

A
  • HCI
21
Q

Hi
Ai

A

in silico virtual drug discovery

22
Q

Hi
Expansion

A
  • selectivity
  • affinity
  • efficacy in assays
  • drug likeness
  • high cc50
  • synthetic tractibility
  • patentability
23
Q

lead compound characteristics

A
  • confirmed potency
  • confirmed selectivity
  • desired adme
  • desired safety profie
  • emerging sar
24
Q

optimise a lc

A

synthesise a structural varient on it in order to optimise its properties

optimise adme

25
Q

sar techniques

A
  • FG // alter
    + FG
    size and shape (position, chain length, ring systems)
26
Q

cig lit azone to

A

rosig lit azone

27
Q

qsar

A

quantitative.

math relationship between structure and physiochem properties // patameters

28
Q

parameter

A

numbers that rep a molecular property

29
Q

parameter examples

A

e- distribution

shape

lipophilicity

30
Q

lipo parameter

A

log p

partition coefficient

log [ octantol ] // [ aq buffer]

31
Q

size parameter

A
  • molecular weight
  • molecular volume
  • surface area
32
Q

electronic parameter

A

HAMMETT CONSTANTS

measure e- wd // e- donation

33
Q

structural parameter

A

h bond donors
h bond acceptors
rotary bonds

34
Q

lipinskis rule of 5

A

log p < 5
mol weight < 500
5 h donors
10 h acceptors

rule for oral drugs

predicts if compound will be drug like

35
Q

modelling

A

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.

36
Q

virtual screening

A

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.

37
Q

what is a pharmacophore

A

abstract description of molecular features

drug discovery (18 decks)

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