_edited.png)
Article by: Sharon Wong Shi May
Drug discovery involves identifying potential compounds that exhibit favorable properties, which are absorption (A), distribution (D), metabolism (M), excretion (E), and toxicity (T). Therefore, these compounds must be screened before being considered for therapeutic use. To improve the chances of successfully passing clinical trials, several drug-likeness rules are applied during the selection process. Drug-likeness refers to a compound’s ability to possess characteristics of an effective drug with a good ADMET profile. Rules such as Lipinski Rule, Pfizer Rule, GSK Rule, and Golden Triangle, serve as binary descriptors to either reject or accept a compound during screening.
Lipinski Rule
This rule evaluates the solubility and permeability of a compound. A compound with poor solubility and permeability properties contains more than five hydrogen bond (HB) donors, more than 10 HB acceptors, a molecular weight (MW) > 500, and a calculated octanol–water coefficient (log𝑃) > 5.0. Violations of two or more of these conditions indicate poor solubility and permeability. Conversely, a compound fulfilling this rule is likely to exhibit good distribution and good oral bioavailability (Lipinski et al., 1997).
Pfizer Rule
This rule predicts the likelihood of a compound to exhibit any toxicity. If a compound has high lipophilicity (logP > 3) but low total polar surface area (TPSA < 75), it is more likely to be toxic. Compounds with high lipophilicity are more likely to diffuse into the lipid membrane but favours the lipophilic environment within the membrane, leading to excessive retention (Hughes et al., 2008).
GSK Rule
It states that compounds with MW ≤ 400; and logP ≤ 4 have an acceptable ADMET profile. This emphasizes a lower MW and low logP enhance the permeability and stability of a compound (Gleeson, 2008).
Golden Triangle
Compounds with favourable ADMET profiles must have 200 ≤MW ≤50 and -2 ≤ logD ≤5. LogD measures the lipophilicity of both ionized and non-ionized compounds. The greater the logD, the greater the lipophilicity and permeability. However, if it exceeds 0.3, it favours the lipophilic environment in the membrane, resulting in retention. Therefore, this rule involves finding a balance between logD and MW for optimal drug development (Johnson, Dress and Edwards, 2009).
In drug discovery, evaluating drug-likeness is significant in identifying potential compounds for therapeutic development. These rules serve as important guidelines to assess the ADMET properties. However, experimental and computational methods should be incorporated along with the rules for the selection of the best drug candidates.
Citations:
Gleeson, M.P. (2008). Generation of a Set of Simple, Interpretable ADMET Rules of Thumb. Journal of Medicinal Chemistry, 51(4), pp.817–834. doi:https://doi.org/10.1021/jm701122q. [12 February 2025]
Hughes, J.D., Blagg, J., Price, D.A., Bailey, S., DeCrescenzo, G.A., Devraj, R.V., Ellsworth, E., Fobian, Y.M., Gibbs, M.E., Gilles, R.W., Greene, N., Huang, E., Krieger-Burke, T., Loesel, J., Wager, T., Whiteley, L. and Zhang, Y. (2008). Physiochemical Drug Properties Associated with in Vivo Toxicological Outcomes. Bioorganic & Medicinal Chemistry Letters, [online] 18(17), pp.4872–4875. doi:https://doi.org/10.1016/j.bmcl.2008.07.071. [12 February 2025]
Johnson, T.W., Dress, K.R. and Edwards, M. (2009). Using the Golden Triangle to Optimize Clearance and Oral Absorption. Bioorganic & Medicinal Chemistry Letters, 19(19), pp.5560–5564. doi:https://doi.org/10.1016/j.bmcl.2009.08.045. [12 February 2025]
Lipinski, C.A., Lombardo, F., Dominy, B.W. and Feeney, P.J. (1997). Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Advanced Drug Delivery Reviews, [online] 23(1-3), pp.3–25. doi:https://doi.org/10.1016/s0169-409x(96)00423-1. [13 February 2025]
Comments