Journal
JOURNAL OF MEDICINAL CHEMISTRY
Volume 47, Issue 1, Pages 224-232Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jm030267j
Keywords
-
Categories
Ask authors/readers for more resources
An increasingly competitive pharmaceutical market demands improvement in the efficiency and probability of drug candidate discovery. Usually these new drug candidates are targeted for oral administration, so a detailed understanding of the molecular-level properties that relate to optimal pharmacokinetics is a critical step toward improving the probability of selecting successful clinical candidates. Although the characteristics of druglike molecules have been previously discussed in the literature, the importance of this topic sustains a continued interest for additional perspective and further detailed statistical analyses. In this contribution, we approach the analysis from the perspective of profiling distinguishing features of orally administered drugs. We have compiled both structural and route-administration information for a total of 1729 marketed drugs to provide a solid basis for developing a new perspective on the characteristics of over 1000 orally administered drugs. The molecular properties and most commonly occurring structural elements are statistically analyzed to capture the differences between routes of administration, as well as between marketed drugs and SAR or clinical compounds. We find that, with respect to other routes of administration, oral drugs tend to be lighter and have fewer H-bond donors, acceptors, and rotatable bonds than drugs with other routes of administration. These differences are particularly pronounced when comparing the mean values for oral vs injectable drugs. We also demonstrate that the mean property values for oral drugs do not vary substantially with respect to launch date, suggesting that the range of acceptable oral properties is independent of synthetic complexity or targeted receptor. Finally, we note that, while these properties are descriptive of each class, they are not necessarily predictive of what class any particular drug will reside in, since there is significant overlap in the acceptable ranges found for each drug class.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available