Evidence map›Paper›PMID 37111304›Full record

ReviewPharmaceuticals (Basel, Switzerland)2023

Technologies for Direct Detection of Covalent Protein-Drug Adducts.

Elma Mons, Robbert Q Kim, Monique P C Mulder

Abstract readReview
In one paragraph

Review in Pharmaceuticals (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
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

3 authors.

Elma MonsDepartment of Cell and Chemical Biology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0003-1105-6424
Robbert Q KimDepartment of Cell and Chemical Biology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0003-1834-8673
Monique P C MulderDepartment of Cell and Chemical Biology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.ORCID 0000-0001-5386-7132

Funding

Dutch Research Council VI. 213.110
6 · The paper itself

Abstract

In the past two decades, drug candidates with a covalent binding mode have gained the interest of medicinal chemists, as several covalent anticancer drugs have successfully reached the clinic. As a covalent binding mode changes the relevant parameters to rank inhibitor potency and investigate structure-activity relationship (SAR), it is important to gather experimental evidence on the existence of a covalent protein-drug adduct. In this work, we review established methods and technologies for the direct detection of a covalent protein-drug adduct, illustrated with examples from (recent) drug development endeavors. These technologies include subjecting covalent drug candidates to mass spectrometric (MS) analysis, protein crystallography, or monitoring intrinsic spectroscopic properties of the ligand upon covalent adduct formation. Alternatively, chemical modification of the covalent ligand is required to detect covalent adducts by NMR analysis or activity-based protein profiling (ABPP). Some techniques are more informative than others and can also elucidate the modified amino acid residue or bond layout. We will discuss the compatibility of these techniques with reversible covalent binding modes and the possibilities to evaluate reversibility or obtain kinetic parameters. Finally, we expand upon current challenges and future applications. Overall, these analytical techniques present an integral part of covalent drug development in this exciting new era of drug discovery.

Indexed as

ABPPchemical probescovalent inhibitorscovalent warheadsdrug developmentdrug discoverymass spectrometrymedicinal chemistrymode of action studiesNMRprotein crystallographytarget validation

Identifiers

PMID37111304
PMCPMC10146396

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.