Evidence map›Paper›PMID 34843238›Full record

ArticleJournal of chemical information and modeling2021

Automated Determination of Nuclear Magnetic Resonance Chemical Shift Perturbations in Ligand Screening Experiments: The PICASSO Web Server.

Vincenzo Laveglia, Andrea Giachetti, Linda Cerofolini, Kevin Haubrich, Marco Fragai, Alessio Ciulli, Antonio Rosato

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Harmonizing Peak Matching between Multidimensional NMR Spectra.Journal of chemical information and modeling · 2026
    Article
  3. Harmonizing Peak Matching Between Multidimensional NMR Spectra.bioRxiv : the preprint server for biology · 2026
    Article
  4. Methods for the Investigation of Protein-Ligands Interactions.Advances in experimental medicine and biology · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

7 authors.

Vincenzo LavegliaConsorzio Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy.
Andrea GiachettiConsorzio Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy.
Linda CerofoliniConsorzio Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy.
Kevin HaubrichSchool of Life Sciences, Division of Biological Chemistry and Drug Discovery, The University of Dundee, James Black Centre, Dow Street, DD1 5EH, Dundee, United Kingdom.
Marco FragaiConsorzio Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy.ORCID 0000-0002-8440-1690
Alessio CiulliSchool of Life Sciences, Division of Biological Chemistry and Drug Discovery, The University of Dundee, James Black Centre, Dow Street, DD1 5EH, Dundee, United Kingdom.ORCID 0000-0002-8654-1670
Antonio RosatoConsorzio Interuniversitario di Risonanze Magnetiche di Metallo Proteine, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy.ORCID 0000-0001-6172-0368

Funding

Wellcome TrustWellcome Trust 094090/Z/10/ZWellcome Trust 100476/Z/12/Z
6 · The paper itself

Abstract

Nuclear magnetic resonance (NMR) is an effective, commonly used experimental approach to screen small organic molecules against a protein target. A very popular method consists of monitoring the changes of the NMR chemical shifts of the protein nuclei upon addition of the small molecule to the free protein. Multidimensional NMR experiments allow the interacting residues to be mapped along the protein sequence. A significant amount of human effort goes into manually tracking the chemical shift variations, especially when many signals exhibit chemical shift changes and when many ligands are tested. Some computational approaches to automate the procedure are available, but none of them as a web server. Furthermore, some methods require the adoption of a fairly specific experimental setup, such as recording a series of spectra at increasing small molecule:protein ratios. In this work, we developed a tool requesting a minimal amount of experimental data from the user, implemented it as an open-source program, and made it available as a web application. Our tool compares two spectra, one of the free protein and one of the small molecule:protein mixture, based on the corresponding peak lists. The performance of the tool in terms of correct identification of the protein-binding regions has been evaluated on different protein targets, using experimental data from interaction studies already available in the literature. For a total of 16 systems, our tool achieved between 79% and 100% correct assignments, properly identifying the protein regions involved in the interaction.

Indexed as

AlgorithmsProteinsAmino Acid SequenceHumansLigandsMagnetic Resonance SpectroscopyNuclear Magnetic Resonance, BiomolecularLigandsProteins

Identifiers

PMID34843238
PMCPMC8715503

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.