The Rule of 5

This review of Ro5 follows our earlier post on the subject. Ro5 was introduced about a decade ago in Adv Drug Deliv Rev 23 (1997) 3-25 which was re-printed in 2001. The article is still essential reading for those working in drug discovery and has proved extremely influential in the pharmaceutical industry. Our view is that while there are sound reasons for avoiding extremes of lipophilicity and molecular size, Ro5's creators do not present much evidence that violating the rule actually leads to lower solubility and permeability.

The rule of 5 can be states that poor permeation or absorption are likely when:

There are more than 5 H-bond donors (sum of OH and NH) in the molecule
There are more than 10 H-bond acceptors (sum of N and O) in the molecule
The MWT exceeds 500
Log P exceeds 5 (or MlogP is over 4.15)
Compound classes that are substrates for biological transporters are exceptions to the rule

Ro5 is based on analysis of a library (USAN) of 2245 orally-dosed drugs likely to have superior physicochemical properties. Cutoffs in the parameters that define Ro5 were set so that about 10% of the drugs in USAN exceeded the cutoff. The observed cutoffs were all found to be all close to 5 or a multiple of 5, leading to the simple mnemonic that the authors called the rule of 5. This approach should be contrasted with the sort of analysis that attempts to classify compounds as soluble/insoluble, druglike/un-druglike, hERG/un-hERG etc using training sets with representatives from each class.

The creators of Ro5 do make one comparison between the USAN library and the entire WDI data set from which it was selected. They state that molecular weights of the compounds in the 2245 USAN library were lower than those in the complete 50427 WDI data set. The proportions of compounds in the USAN library and full WDI set with set with molecular weights exceeding 500 were 11% and 22% respectively. At the risk of appearing unduly anal, we note that simply observing proportions of two distributions that lie a outside a cutoff does not allow conclusions to be drawn about differences in the mean values for the distributions. An alternative hypothesis could be that means are not significantly different but the variance for the whole WDI data set is greater (we guess that it probably is). Were this the case, a line drawn at a suitable low MWT would suggest that the USAN library was of higher average MWT than the whole WDI data set. The practice of slicing distributions is a commonly employed tactic in medicinal chemistry data analysis and we expect to review specific examples in future posts.

Ro5 presents two interesting asymmetries. The first is between hydrogen bond donors and acceptors. Are donors inherently more evil than acceptors? Does hydrogen bonding have an even darker side? Does the amide NH, in transit thru the core of the membrane remember that it had earlier been interacting with an oxygen lone pair rather than a water molecule's hydrogen atom? The creators of Ro5 note that "there is far more variation in hydrogen bond acceptor than donor ability across atom types". While we believe this assertion to be essentially correct, it is noted that strong hydrogen bond donors (e.g 4-nitrophenol) are known although these can find themselves excluded from databases like USAN for reasons unconnected with their their ability to participate in hydrogen bonding. The reason for donor acceptor asymmetry is that, as defined by Ro5, the number of donors can at best equal the number of acceptors. Even when more sophisticated definitions of hydrogen bonding are used, donors tend to be less common than acceptors in molecules of pharmaceutical interest. Analysis based on property distributions will necessarily set a lower cutoff for donors and you may wish to point this out tactfully to colleagues who invoke Ro5 in support of a view that donors (as opposed to acceptors) are bad for CNS penetration.

The second asymmetry is how the extremes of lipophilicity are defined. High lipophilicity is a consequence of poor solvation in the aqueous phase. Lipophilic molecules will do their best to get out of an aqueous environment and escape plans include finding friends (precipitate or at least aggregate promiscuously) and seeking lodging with The Anti-targets Of The Dark Side. Too much lipophilicity is Sinful. However if the drug is too happy (happy drugs?) in water, can it reasonably be expected to slum it in the membrane core? Ro5 eliminates excessively lipophilic drugs with a cutoff in ClogP (calculated octanol water partition coefficient) but the inadequately lipophilic are condemned for their hydrogen bonds. The roots of this asymmetry lie in the hydrogen bonding character of octanol which experimental ease makes the default solvent for partitioning studies.

One physico-chemical property on which Ro5 has surprisingly little to say is ionisation. Ionisable groups in molecules can greatly increase aqueous solubility but at the cost of reducing the proportion of neutral form that is required for passive transport thru the gut wall.

Is it fair to call Ro5 a Sacred Cow? It's creators present a useful and pioneering analysis clearly and honestly. Our experience suggests that those who hold the Ro5 most sacred are often those who have not actually looked at the publication. Management Brahmins? It is not for us to comment.

This brings us to the end of our review of Ro5. In the next two posts on the subject we will highlight some related studies before concluding with a look at what we will call now (and surely regret later) the 'sociological' implications of Ro5. We hope you have found the review useful and encourage you to share your own views and opinions on the subject.

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