Evidence map›Paper›PMID 21371594›Full record

ArticleMethods in enzymology2011

Binding site identification and structure determination of protein-ligand complexes by NMR a semiautomated approach.

Joshua J Ziarek, Francis C Peterson, Betsy L Lytle, Brian F Volkman

Abstract read
In one paragraph

Article in Methods in enzymology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing 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

39 citing papers in PubMed.

  1. Combining MicroED and native mass spectrometry for structural discovery of enzyme-small molecule complexes.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

4 authors.

Joshua J ZiarekDepartment of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Francis C Peterson
Betsy L Lytle
Brian F Volkman

Funding

Structural Basis for Chemokine FunctionR01AI058072 · NIAID · MEDICAL COLLEGE OF WISCONSIN · PI VOLKMAN, BRIAN F · 2004 to 2019
$4.1M
Sulfotyrosine-guided discovery of small molecule chemokine inhibitorsR01GM097381 · NIGMS · MEDICAL COLLEGE OF WISCONSIN · PI VOLKMAN, BRIAN F · 2011 to 2021
$2.9M
Structural Basis for Chemokine FunctionR37AI058072 · NIAID · MEDICAL COLLEGE OF WISCONSIN · PI Brian F Volkman · 2020 to 2026
$2.8M
Conformational duality in the human chemokine Ltn/XCL1R01AI063325 · NIAID · MEDICAL COLLEGE OF WISCONSIN · PI VOLKMAN, BRIAN F · 2005 to 2009
$1.4M
NIAID NIH HHS R01 AI058072NIAID NIH HHS R01 AI063325NIAID NIH HHS R37 AI058072NIGMS NIH HHS R01 GM097381
6 · The paper itself

Abstract

Over the last 15 years, the role of NMR spectroscopy in the lead identification and optimization stages of pharmaceutical drug discovery has steadily increased. NMR occupies a unique niche in the biophysical analysis of drug-like compounds because of its ability to identify binding sites, affinities, and ligand poses at the level of individual amino acids without necessarily solving the structure of the protein-ligand complex. However, it can also provide structures of flexible proteins and low-affinity (K(d)>10(-6)M) complexes, which often fail to crystallize. This chapter emphasizes a throughput-focused protocol that aims to identify practical aspects of binding site characterization, automated and semiautomated NMR assignment methods, and structure determination of protein-ligand complexes by NMR.

Indexed as

Binding SitesAutomation, LaboratoryDrug DesignDrug DiscoveryHydrogen BondingLigandsMagnetic Resonance SpectroscopyModels, MolecularNuclear Magnetic Resonance, BiomolecularProteinsSoftwareLigandsProteins

Identifiers

PMID21371594
PMCPMC3635485

What OpenQuestion holds

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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.