Evidence map›Paper›PMID 19812734›Full record

ArticlePerspectives in medicinal chemistry2007

The pK(a) Distribution of Drugs: Application to Drug Discovery.

David T Manallack

Open access · greenAbstract read
In one paragraph

Article in Perspectives in medicinal chemistry, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
109citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

109 citing papers in PubMed, 1 synthesis or guideline pooled it, 218 citations in OpenAlex.

  1. Pooled it
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  11. SelectiveThe Journal of organic chemistry · 2025
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  12. Article
  13. Article
  14. Review
  15. Determination of the pAnalytical chemistry · 2024
    Article
  16. Article
  17. Structure-activity relationship of pharmacophores and toxicophores: the need for clinical strategy.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2024
    Review
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  19. Salt forms of amides: protonation of acetanilide.Acta crystallographica. Section C, Structural chemistry · 2024
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  20. QupKake: Integrating Machine Learning and Quantum Chemistry for Micro-pJournal of chemical theory and computation · 2024
    Article

49 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

David T ManallackDepartment of Medicinal Chemistry, Victorian College of Pharmacy, Monash University, 381 Royal Parade, Parkville, 3052, Australia.
Monash University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The acid-base dissociation constant (pK(a)) of a drug is a key physicochemical parameter influencing many biopharmaceutical characteristics. While this has been well established, the overall proportion of non-ionizable and ionizable compounds for drug-like substances is not well known. Even less well known is the overall distribution of acid and base pK(a) values. The current study has reviewed the literature with regard to both the proportion of ionizable substances and pK(a) distributions. Further to this a set of 582 drugs with associated pK(a) data was thoroughly examined to provide a representative set of observations. This was further enhanced by delineating the compounds into CNS and non-CNS drugs to investigate where differences exist. Interestingly, the distribution of pK(a) values for single acids differed remarkably between CNS and non-CNS substances with only one CNS compound having an acid pK(a) below 6.1. The distribution of basic substances in the CNS set also showed a marked cut off with no compounds having a pK(a) above 10.5.The pK(a) distributions of drugs are influenced by two main drivers. The first is related to the nature and frequency of occurrence of the functional groups that are commonly observed in pharmaceuticals and the typical range of pK(a) values they span. The other factor concerns the biological targets these compounds are designed to hit. For example, many CNS targets are based on seven transmembrane G protein-coupled receptors (7TM GPCR) which have a key aspartic acid residue known to interact with most ligands. As a consequence, amines are mostly present in the ligands that target 7TM GPCR's and this influences the pK(a) profile of drugs containing basic groups. For larger screening collections of compounds, synthetic chemistry and the working practices of the chemists themselves can influence the proportion of ionizable compounds and consequent pK(a) distributions. The findings from this study expand on current wisdom in pK(a) research and have implications for discovery research with regard to the composition of corporate databases and collections of screening compounds. Rough guidelines have been suggested for the profile of compound collections and will evolve as this research area is expanded.

Indexed as

absorptionacidsADMEampholytesbasesbioavailabilitydissociation constantdistributiondrug discoverydrugspharmacokineticspKa

Identifiers

PMID19812734
PMCPMC2754920
OpenAlexW1895187576

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.