Requirements for drug likeness
-Contain atoms C H O S N P - Low molecular weight - devoid of reactive chemical groups - devoid of toxophores - Relatively water soluble
Block Buster drugs
Causes of drug candidate failure
-Poor pharmacokinetics - Lack of efficacy - toxicity
Privileged structures
Certain structures which are often found in drug molecules even if acting at different targetts, benzorings, piperdizines and diphenyls
PSA
<140 = absorption <100 = BBB permeability
Changes in drug candidate from lead to oprtimization
Increase in MW Increase in Hydrophobicity Increasing potency
Lead like structures
• MW < 300, • H-bond donors is ≤3 • H-bond acceptors ≤ 3 and • Calculated logP ≤ 3
selection of a successful drug target?
Target identification via pathophysiology
Target identification via Phenotypic drug effects
-Chemicals (often existing drugs) are screened to see if they possess intrinsic pharmacological activity - i.e. phenothiazine initially used as a sedative became known for antipsychotic action mediated by activity at the D2 receptor.
Genetic drug discovery
Disease state can be emulated by using knock out mice or similar animal studies
How to make a KO mice step 1

How to make KO mice step 2
Limitations to KO mice

Gene silencing
this can be done ‘pharmacologically’ within animal models or cell assays, but also through genetic means such as antisense oligonucleotides or RNA interference (RNAi).
RNAi inhibits translation by neutrilizing target Mrna molecules.
Partial knockout

Inducible KO

TDD: Imatinib
PDD: Fingiloid
A biased library of S1P like small drug molecules were screened for immunosuprresive activity
Pros and conds of TDD
Pros:
Rational MOA
Can use siRNA to probe mRNA and validate trget before undetaking chemistry
can aid design thorugh protein isolation and determination of structure
Cons:
-
Pros and Cons of PDD
PROS:
Direct screening, direct validation
Target must be druggable
Can identify novel MOAs
Cons:
suitably diverse libraries are difficult to obtain
difficult to generate suitably robust assays
MOA unknown; difficult to predict disease relavance and human safety
Priorities in a TDD library
And PDD library
Drug likeness (oral bioavailibility) over potentness and selectivity which can be improved with optmization
PDD library places . high emphasis of potency and selectivity (needs to be ablet to induce a phenotypic outcome)
Lead like library
Recognises increasing MW and Log P is often required
Increasing log P and MW worsens pharmacokinetic profile (reduced solubility increased metabolism) so these are kept low
Offers Leads which will require furhter development
Fragment library
used in fragment based drug design (FBD), where very small molecules that bind to a biomolecular-target (may or may not have a biochemical effect) are used as start-point to generate higher affinity compounds with a biochemical effect
Parameters for evaluating hits
LE= log(Ki/N) > 0.3
LipE = - logKi -Log P > 0.45
LELP= Log P/LE 0-7.5
Where N = number of non hydrogens