Druglikeness

Druglikeness is a qualitative concept used in drug design for how "druglike" a substance is with respect to factors like bioavailability. It is estimated from the molecular structure before the substance is even synthesized and tested. A druglike molecule has properties such as:

A traditional method to evaluate druglikeness is to check compliance of Lipinski's Rule of Five, which covers the numbers of hydrophilic groups, molecular weight and hydrophobicity.

Based on one definition, a drug-like molecule has a logarithm of partition coefficient (log P) between -0.4 and 5.6, molecular weight 160-480 g/mol, molar refractivity of 40-130, which is related to the volume and molecular weight of the molecule and has 20-70 atoms.[4]

Also, other factors such as substructures with known toxic, mutagenic or teratogenic properties affect the usefulness of a designed molecule. In fact, several poisons have a good druglikeness. Natural toxins are used in pharmacological research to find out their mechanism of action, and if it could be exploited for beneficial purposes.

Druglikeness indices are inherently limited tools. Druglikeness can be estimated for any molecule, and does not evaluate the actual specific effect that the drug achieves (biological activity). Simple rules are not always accurate and may unnecessarily limit the chemical space to search: many best-selling drugs have features that cause them to score low on various druglikeness indices.[5] Furthermore, first-pass metabolism, which is biochemically selective, can destroy the pharmacological activity of a compound despite good druglikeness.

Druglikeness is not relevant for most biologics, since they are usually proteins that need to be injected, because proteins are digested if eaten.

See also

References

  1. Uetrecht J (January 2001). "Prediction of a new drug's potential to cause idiosyncratic reactions". Current Opinion in Drug Discovery & Development 4 (1): 55–9. PMID 11727323.
  2. Uetrecht J (January 2008). "Idiosyncratic drug reactions: past, present, and future". Chem. Res. Toxicol. 21 (1): 84–92. doi:10.1021/tx700186p. PMID 18052104.
  3. Smith GF (February 2011). "Designing drugs to avoid toxicity". Prog. Med. Chem. 50 (1): 1–47. doi:10.1016/B978-0-12-381290-2.00001-X. PMID 21315927.
  4. Ghose AK, Viswanadhan VN, Wendoloski JJ (January 1999). "A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases". J Comb Chem 1 (1): 55–68. doi:10.1021/cc9800071. PMID 10746014.
  5. http://pipeline.corante.com/archives/2012/03/26/whats_the_ugliest_drug_or_the_ugliest_drug_candidate.php

External links