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Lipinski's Rule of Five

Lipinski's Rule of Five[1] is a rule of thumb to evaluate druglikeness, or determine if a chemical compound with a certain pharmacological or biological activity has properties that would make it a likely orally active drug in humans. The rule was formulated by Christopher A. Lipinski in 1997, based on the observation that most medication drugs are relatively small and lipophilic molecules.[2]

The rule describes molecular properties important for a drug's pharmacokinetics in the human body, including their absorption, distribution, metabolism, and excretion ("ADME"). However, the rule does not predict if a compound is pharmacologically active.

The rule is important for drug development where a pharmacologically active lead structure is optimized step-wise for increased activity and selectivity, as well as drug-like properties as described by Lipinski's rule. The modification of the molecular structure often leads to drugs with higher molecular weight, more rings, more rotatable bonds, and a higher lipophilicity.[3]

Contents

The rule

Lipinski's Rule of Five states that, in general, an orally active drug has no more than one violation of the following criteria:

Note that all numbers are multiples of five, which is the origin of the rule's name.

Improvements

To evaluate druglikeness better, the rules have spawned many extensions, for example one from a 1999 paper by Ghose et al.:[4]

  • Partition coefficient log P in -0.4 to +5.6 range
  • Molar refractivity from 40 to 130
  • Molecular weight from 160 to 480
  • Number of heavy atoms from 20 to 70

Over the past decade Lipinski's profiling tool for druglikeness has led to further investigations by scientists to extend profiling tools to lead-like properties of compounds in the hope that a better starting point in early discovery can save time and cost.

See also

References

  1. ^ Lipinski CA,Lombardo F,Dominy BW and Feeney PJ.Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.Adv Drug Del Rev,1997,23:3-25.
  2. ^ C. A. Lipinski, F. Lombardo, B. W. Dominy, P. J. Feeney, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv. Drug Del. Rev., 2001, 46, 3-26. (doi:10.1016/S0169-409X(00)00129-0)
  3. ^ T. I. Oprea, A. M. Davis, S. J. Teague, P. D. Leeson, Is There a Difference between Leads and Drugs? A Historical Perspective, J. Chem. Inf. Comput. Sci., 2001, 41, 1308-1315.
  4. ^ Arup K. Ghose, Vellarkad N. Viswanadhan, and John J. Wendoloski, A Knowledge-Based Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery, J. Combin. Chem., 1999, 1, 55-68. (doi:10.1021/cc9800071)

External links

The original article is from Wikipedia. To view the original article please click here.
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