In compound optimization stage, “reduce lipophilicity” is mantra for chemists. High lipophilicity compound tend to be metabolically unstable, promiscuous and binding many off targets. To reduce lipophilicity is important strategy for drug discovery process but it is not always suitable strategy.
Researchers from Genentech report their useful experience in JMC lett.
You can find the article in ASAP, url is below.
https://pubs.acs.org/doi/10.1021/acsmedchemlett.8b00047
They analyzed in house in vivo PK data and lipophilicity and summarized that “Decreasing lipophilicity without addressing a metabolic soft-spot will often lead to both lower clearance and volume of distribution without extending half-life”.
You know, reducing lipohilicity is decreasing permeability it is not good for PK. And also Fig2 shows clear cut of their opinion.
In rat PK-IV, it found weak correlation between volume of distribution of unbound fraction (VDss-u) and LogD, clearance of unbound fraction(CLu) and LogD. It means that VDss-u and CLu highly correlates as same as LogD.
And in one component model, half-time is defined as following equation.
T1/2 = VDss,u/CL,u * ln2
From the equation and relation ship between VDss and CL, simple reduction of lipophilicity decreases not only CL,u but also VDss,u and no effect for T1/2!
In the article, the authors analyzed in-house data with MMPA and showed some transformations for improve half-life.
I think it worth to read the article.
MMPA is performed with Knime vernalis node. This tool kit is open source, it can use everybody without fee.
https://www.knime.com/book/vernalis-nodes-for-knime-trusted-extension
MedChem x Chemoinformatics = exciting! ;-)
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