Cited by 498Computational Drug Discovery MethodsProtein Degradation and InhibitorsSynthesis and biological activity

Polypharmacology by Design: A Medicinal Chemist’s Perspective on Multitargeting Compounds

Proschak, Ewgenij, Stark, Holger, Merk, Daniel·2019·Journal of Medicinal Chemistry

Abstract

Multitargeting compounds comprising activity on more than a single biological target have gained remarkable relevance in drug discovery owing to the complexity of multifactorial diseases such as cancer, inflammation, or the metabolic syndrome. Polypharmacological drug profiles can produce additive or synergistic effects while reducing side effects and significantly contribute to the high therapeutic success of indispensable drugs such as aspirin. While their identification has long been the result of serendipity, medicinal chemistry now tends to design polypharmacology. Modern in vitro pharmacological methods and chemical probes allow a systematic search for rational target combinations and recent innovations in computational technologies, crystallography, or fragment-based design equip multitarget compound development with valuable tools. In this Perspective, we analyze the relevance of multiple ligands in drug discovery and the versatile toolbox to design polypharmacology. We conclude that despite some characteristic challenges remaining unresolved, designed polypharmacology holds enormous potential to secure future therapeutic innovation.

Integrity signals

Registry

Crossref · 10.1021/acs.jmedchem.8b00760

Cites

251 of 251 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Proschak, E., Stark, H., & Merk, D.
Affiliations
  • Goethe University Frankfurt (DE)
  • Heinrich Heine University Düsseldorf (DE)
Corresponding author
Merk, Daniel
Venue
Journal of Medicinal Chemistry
Published
2018-07-23
Volume
62
Issue
2
Pages
420-444
ISSN
  • 0022-2623 (ISSN-L)
  • 1520-4804
OpenAlex
W2884740260
Cited by
498
References
251
Citations by year
2026: 51 · 2025: 56 · 2024: 74 · 2023: 60 · 2022: 86 · 2021: 64 · 2020: 67 · 2019: 39 · 2018: 1
FWCI
35.15
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Medicinal Chemistry (publishedVersion)
  • PubMed (publishedVersion)
  • Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (submittedVersion)
  • Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
Funders
  • Eidgen?ssische Technische Hochschule Z?rich (16-2 FEL-07)
  • Deutsche Forschungsgemeinschaft (SFB1039, PR1405/2-2, PR1405/4-1)
  • European Cooperation in Science and Technology (CA15135)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
  • Physical Sciences › Chemistry › Organic Chemistry › Synthesis and biological activity
Keywords
polypharmacology, multi-target drug design, drug discovery, chemical probes, fragment-based design, crystallography, computer-aided drug design, complex diseases, drug synergy, side effect reduction
MeSH terms
Machine Learning, Animals, Chemistry, Pharmaceutical, Humans, Ligands, Structure-Activity Relationship, Drug Design, Crystallography, X-Ray, Models, Animal, Metabolic Networks and Pathways

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review