Evidence map›Paper›PMID 31458770›Full record

ArticleACS omega2018

A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions.

Lena Kalinowsky, Julia Weber, Shantheya Balasupramaniam, Knut Baumann, Ewgenij Proschak

Abstract read
In one paragraph

Article in ACS omega, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Food science & nutrition · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Biochemistry and biophysics reports · 2021
    Article
  11. 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

5 authors.

Lena KalinowskyInstitute of Pharmaceutical Chemistry, Goethe University Frankfurt, Max-von-Laue Str. 9, Frankfurt am Main D-60438, Germany.
Julia WeberInstitute of Pharmaceutical Chemistry, Goethe University Frankfurt, Max-von-Laue Str. 9, Frankfurt am Main D-60438, Germany.
Shantheya BalasupramaniamInstitute of Medicinal and Pharmaceutical Chemistry, University of Technology of Braunschweig, Beethovenstr. 55, Braunschweig D-38106, Germany.
Knut BaumannInstitute of Medicinal and Pharmaceutical Chemistry, University of Technology of Braunschweig, Beethovenstr. 55, Braunschweig D-38106, Germany.
Ewgenij ProschakInstitute of Pharmaceutical Chemistry, Goethe University Frankfurt, Max-von-Laue Str. 9, Frankfurt am Main D-60438, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prediction of protein-ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications. Docking and scoring is broadly used to propose the binding mode and underlying interactions as well as to provide a measure for ligand affinity or differentiate between active and inactive ligands. Various studies have revealed that most docking software packages reliably predict the binding mode, although scoring remains a challenge. Here, a diverse benchmark data set of 99 matched molecular pairs (3D-MMPs) with experimentally determined X-ray structures and corresponding binding affinities is introduced. This data set was used to study the predictive power of 13 commonly used scoring functions to demonstrate the applicability of the 3D-MMP data set as a valuable tool for benchmarking scoring functions.

Identifiers

PMID31458770
PMCPMC6641919

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.