Solubility optimization
is a crucial step to obtaining oral PROTACs.
Here we measured the thermodynamic solubilities (log S) of 21 commercial PROTACs. Next, we measured BRlogD and log k
w
IAM (lipophilicity), EPSA, and Δ
log k
w
IAM (polarity) and showed
that lipophilicity plays a major role in governing log S, but a contribution of polarity cannot be neglected. Two-/three-dimensional
descriptors calculated on conformers arising from conformational sampling
and steered molecular dynamics failed in modeling solubility. Infographic
tools were used to identify a privileged region of soluble PROTACs
in a chemical space defined by BRlogD, log k
w
IAM and topological polar surface area, while machine
learning provided a log S classification model. Finally,
for three pairs of PROTACs we measured the solubility, lipophilicity,
and polarity of the building blocks and identified the limits of estimating
PROTAC solubility from the synthetic components. Overall, this paper
provides promising guidelines for optimizing PROTAC solubility in
early drug discovery programs.