Chris Lipinski, author of the 1997 'rule
of five',1 believes that although the rule has altered medicinal
chemistry for oral small molecule drugs, predicting the behavior of newer
biologics might not be far off, and optimization of RNA or protein delivery
could be the opportunity for the next big breakthrough in computer-based
What was the impetus that led you to develop the rule of five?
Chris Lipinski: At that time, 1997, at least 90% of the small molecule
medicinal chemistry efforts were directed at oral compounds. People were
heavily influenced by a high throughput screening philosophy and were making
large numbers of compounds that were evaluated for potency without regard for
Do you believe the rule of five has changed how medicinal chemists create
When you came up with the rule of five were there compound classes you knew or
suspected it would not apply to?
Yes. At Pfizer we looked for compounds that were orally active and broke the
rule and found they were mostly natural products.
Your original predictions related to small molecule drugs. Can we make similar
predictions for other modalities?
We are beginning to see better software for dealing with proteins. I often talk
about the 'in-between-world size'.
SciBX: Do you think there
are newer strategies that could help improve on the rule of five?
Matched fragment pairs add value, as they typically occur in lead optimization,
and unlike the physicochemical properties used in the rule of five, this
approach directly implements experimental data from in vitro and in
There are various software packages that predict how small molecules will
behave based on their chemical structures. How good do you think those programs
are, and what is the most effective way to implement the information they
In general, the usefulness depends on how structurally similar your new
compound is to the software's training set of molecules.
Has computational prediction peaked or can it still improve?
It could get better from two angles.
Do you believe that ultimately these predictive programs can lead to shorter
drug development times and cost savings that will affect the industry?
I'm not sure about shorter. It may reduce attrition. These kinds of tools used
efficiently and knowledgeably can eliminate a lot of the mistakes and wasted
effort that currently goes on.
What has surprised you most in the field of molecule design and predicting drug
behavior, and what are the biggest successes and failures?
The success of fragment screening took me completely by surprise. If
someone had told me 15 years ago that you could have a small lipophilic
fragment that would bind selectively, and that screening compounds in the 100 mM to [low] mM
range could give you enough information to optimize and reach a clinical
candidate in just 100 or 150 compounds, I wouldn᾽t have believed it. But that᾽s what happened, and that technology is a rare success
What might be the next area of drug development in which in silico approaches
will break through?
One of the biggest challenges is the delivery of protein and RNA therapeutics.
There are certain adjuvants that work partially, often by forming a complex
between the compound and a cationic carrier.
Thank you very much for your time.
Fishburn, C.S. SciBX 6(46); doi:10.1038/scibx.2013.1309
Published online Dec. 5, 2013
1. Lipinski, C.A. et
al. Adv. Drug Deliv. Rev. 23, 3-25 (1997)
2. Lowe, D. Lipinski's anchor. Corante
(Nov. 25, 2013)
AND INSTITUTIONS MENTIONED
American Chemical Society, Washington, D.C.
Melior Discovery Inc., Exton, Pa.
National Institutes of Health, Bethesda, Md.
Pfizer Inc. (NYSE:PFE), New York, N.Y.