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Correction

Correction: Giri et al. Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge. Biomolecules 2023, 13, 132

Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
*
Author to whom correspondence should be addressed.
Biomolecules 2024, 14(11), 1404; https://doi.org/10.3390/biom14111404
Submission received: 1 October 2024 / Accepted: 7 October 2024 / Published: 4 November 2024
There was an error in the original publication [1]. There are two references [8,9] in the original version, which do not genuinely enhance our paper.
A correction has been made to Introduction, Paragraph Number: 3.
The corrected sentence in the paragraph is as follows: One of the most popular approaches to modeling the protein–ligand complexes is molecular docking [4–7], which uses physics- or statistical potential-based molecular simulations to generate protein–ligand complex models and a scoring function for the estimation of their binding affinities to rank them.
With this correction, the order of some references has been adjusted accordingly. The authors state that the scientific conclusions are unaffected. This correction was approved by the academic editor. The original publication has also been updated.

Reference

  1. Giri, N.; Cheng, J. Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge. Biomolecules 2023, 13, 132. [Google Scholar] [CrossRef] [PubMed]
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Share and Cite

MDPI and ACS Style

Giri, N.; Cheng, J. Correction: Giri et al. Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge. Biomolecules 2023, 13, 132. Biomolecules 2024, 14, 1404. https://doi.org/10.3390/biom14111404

AMA Style

Giri N, Cheng J. Correction: Giri et al. Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge. Biomolecules 2023, 13, 132. Biomolecules. 2024; 14(11):1404. https://doi.org/10.3390/biom14111404

Chicago/Turabian Style

Giri, Nabin, and Jianlin Cheng. 2024. "Correction: Giri et al. Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge. Biomolecules 2023, 13, 132" Biomolecules 14, no. 11: 1404. https://doi.org/10.3390/biom14111404

APA Style

Giri, N., & Cheng, J. (2024). Correction: Giri et al. Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge. Biomolecules 2023, 13, 132. Biomolecules, 14(11), 1404. https://doi.org/10.3390/biom14111404

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