Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 215

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Comparative Assessment of Scoring Functions on an Updated Benchmark: 1. Compilation of the Test Set

Li, Yan, Liu, Zhihai, Li, Jie, Han, Li, Liu, Jie, Zhao, Zhixiong, Wang, Renxiao·2014·Journal of Chemical Information and Modeling

Abstract

Scoring functions are often applied in combination with molecular docking methods to predict ligand binding poses and ligand binding affinities or to identify active compounds through virtual screening. An objective benchmark for assessing the performance of current scoring functions is expected to provide practical guidance for the users to make smart choices among available methods. It can also elucidate the common weakness in current methods for future improvements. The primary goal of our comparative assessment of scoring functions (CASF) project is to provide a high-standard, publicly accessible benchmark of this type. Our latest study, i.e., CASF-2013, evaluated 20 popular scoring functions on an updated set of protein-ligand complexes. This data set was selected out of 8302 protein-ligand complexes recorded in the PDBbind database (version 2013) through a fairly complicated process. Sample selection was made by considering the quality of complex structures as well as binding data. Finally, qualified complexes were clustered by 90% similarity in protein sequences. Three representative complexes were chosen from each cluster to control sample redundancy. The final outcome, namely, the PDBbind core set (version 2013), consists of 195 protein-ligand complexes in 65 clusters with binding constants spanning nearly 10 orders of magnitude. In this data set, 82% of the ligand molecules are "druglike" and 78% of the protein molecules are validated or potential drug targets. Correlation between binding constants and several key properties of ligands are discussed. Methods and results of the scoring function evaluation will be described in a companion work in this issue (doi: 10.1021/ci500081m ).

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ci500080q

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 7 references

Cited by

See all 215

Metadata

Authors
Li, Y., Liu, Z., Li, J., Han, L., Liu, J., Zhao, Z., & Wang, R.
Venue
Journal of Chemical Information and Modeling
Published
2014-06-02
Volume
54
Issue
6
Pages
1700-1716
ISSN
  • 1549-9596 (ISSN-L)
  • 1549-960X
OpenAlex
W1969017960
Cited by
215
References
7
FWCI
17.75
Type
journal article
Language
en
Open access
closed

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Comparative Assessment of Scoring Functions on an Updated Benchmark: 1. Compilation of the Test Set. https://app.cochat.ai/papers/10.1021/ci500080q
The paper
Li, Y., Liu, Z., Li, J., Han, L., Liu, J., Zhao, Z., & Wang, R. (2014). Comparative Assessment of Scoring Functions on an Updated Benchmark: 1. Compilation of the Test Set. Journal of Chemical Information and Modeling. https://doi.org/10.1021/ci500080q

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.