Drug Design 2 - Applied Bioinformatics Group

PharmacokineDc ProperDes
• log P, pK a (for acids/bases), and log S play a key role in the
predic%on of the pharmacokine%c proper%es of a compound
• Predic%ng pharmacokine%c proper%es is a non-­‐trivial, but
worthwhile, task
• Experimental determina%on of these proper%es is too expensive
for large libraries (e.g., HTS libraries!)
• For many of these proper%es, simple addi%ve models (increment
models) have been developed
• These models assume that the property is given as the sum of the
proper%es of the structural fragments contained in the compound
PredicDon of log P
• We assume that the property of a molecule (e.g., log P) can be
expressed as the contribu%ons of groups
log P = ∑ i a i f i
where a i is the number of fragments of type i occurring in the
structure and f i the fragment‘s contribu%on to log P
• This trivial approach works surprisingly well and can be further
improved through the inclusion of correcDon factors
• These factors compensate for effects like interac%ons between
fragments
Fujita et al., J. Am. Chem. Soc. (1961), 86, 5179
ClogP
• One of the most widely used
approaches for log P predic%on is
ClogP
• ClogP uses a library of fragment
proper%es and correc%on factors
• Fragments are generated by
decomposing the structures at
‘isola%ng carbon atoms’
• These atoms have neither double
nor triple bonds to heteroatoms
F
F
F
OH
NH O
F
F
F
Leo, Chem. Rev. (1993), 93, 1281