Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Jan 12;21(1):75.
doi: 10.3390/molecules21010075.

Chemical Structure-Related Drug-Like Criteria of Global Approved Drugs

Affiliations

Chemical Structure-Related Drug-Like Criteria of Global Approved Drugs

Fei Mao et al. Molecules. .

Abstract

The chemical structure of a drug determines its physicochemical properties, further determines its ADME/Tox properties, and ultimately affects its pharmacological activity. Medicinal chemists can regulate the pharmacological activity of drug molecules by modifying their structure. Ring systems and functional groups are important components of a drug. The proportion of non-hydrocarbon atoms among non-hydrogen atoms reflects the heavy atoms proportion of a drug. The three factors have considerable potential for the assessment of the drug-like properties of organic molecules. However, to the best of our knowledge, there have been no studies to systematically analyze the simultaneous effects of the number of aromatic and non-aromatic rings, the number of some special functional groups and the proportion of heavy atoms on the drug-like properties of an organic molecule. To this end, the numbers of aromatic and non-aromatic rings, the numbers of some special functional groups and the heavy atoms proportion of 6891 global approved small drugs have been comprehensively analyzed. We first uncovered three important structure-related criteria closely related to drug-likeness, namely: (1) the best numbers of aromatic and non-aromatic rings are 2 and 1, respectively; (2) the best functional groups of candidate drugs are usually -OH, -COOR and -COOH in turn, but not -CONHOH, -SH, -CHO and -SO3H. In addition, the -F functional group is beneficial to CNS drugs, and -NH2 functional group is beneficial to anti-infective drugs and anti-cancer drugs; (3) the best R value intervals of candidate drugs are in the range of 0.05-0.50 (preferably 0.10-0.35), and R value of the candidate CNS drugs should be as small as possible in this interval. We envision that the three chemical structure-related criteria may be applicable in a prospective manner for the identification of novel candidate drugs and will provide a theoretical foundation for designing new chemical entities with good drug-like properties.

Keywords: chemical structure-related criteria; drug design; drug-like property; functional group; ring system; the heavy atoms proportion.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Example of aromatic ring count, non-aromatic ring count, functional group count and R value for clocapramine.
Figure 2
Figure 2
The percentage of different aromatic drugs in the whole database and five sub-databases.
Figure 3
Figure 3
The percentage of aromatic drugs containing different ring count in the whole database and five sub-databases. The bars represent the percentages of drugs with different aromatic ring count in corresponding aromatic drugs databases.
Figure 4
Figure 4
The percentage of different non-aromatic drugs in the whole database and five sub-databases.
Figure 5
Figure 5
The percentage of non-aromatic drugs containing different ring counts in the whole database and five sub-databases. The bars represent the percentages of drugs with different non-aromatic ring counts in the corresponding non-aromatic drugs databases.
Figure 6
Figure 6
Heavy atoms proportion (R value) distribution of different kinds of approved drugs.
Figure 6
Figure 6
Heavy atoms proportion (R value) distribution of different kinds of approved drugs.
Figure 7
Figure 7
Schematic representation of the approved drugs database source, data collection and classification.

References

    1. Price Waterhouse Coopers (PWC) From Vision to Decision. Pharma 2020 Report. PWC; London, UK: 2012. [(accessed on 16 November 2015)]. Available online: http://www.pwc.com/gx/en/industries/pharmaceuticals-life-sciences/pharma....
    1. Sugiyama Y. Druggability: Selecting optimized drug candidates. Drug Discov. Today. 2005;10:1577–1579. doi: 10.1016/S1359-6446(05)03675-5. - DOI - PubMed
    1. Lipinski C.A. Drug-like properties and the causes of poor solubility and poor permeability. J. Pharmacol. Toxicol. 2000;44:235–249. doi: 10.1016/S1056-8719(00)00107-6. - DOI - PubMed
    1. Borchardt R.T. Pharmaceutical Profiling in Drug Discovery for Lead Selection. American Association of Pharmaceutical Scientists; Arlington, VA, USA: 2004.
    1. Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliver. Rev. 1997;23:3–25. doi: 10.1016/S0169-409X(96)00423-1. - DOI - PubMed

Publication types

MeSH terms