Cross‐docking benchmark for automated pose and ranking prediction of ligand binding-Reference-Cited by-同舟云学术

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Cross‐docking benchmark for automated pose and ranking prediction of ligand binding

Published:2019-11-28 Issue:1 Volume:29 Page:298-305
ISSN:0961-8368
Container-title:Protein Science
language:en
Short-container-title:Protein Science

Author:

Wierbowski Shayne D.¹,Wingert Bentley M.²^ORCID,Zheng Jim³,Camacho Carlos J.²

Affiliation:

1. Department of Biology University of Scranton Scranton Pennsylvania

2. Department of Computational and Systems Biology University of Pittsburgh Pittsburgh Pennsylvania

3. Department of Computer Science University of Pittsburgh Pittsburgh Pennsylvania

Funder

National Institutes of Health

National Science Foundation

Publisher

Wiley

Subject

Molecular Biology,Biochemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pro.3784

Reference25 articles.

1. Recommendations for evaluation of computational methods

2. Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking

3. CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

4. CSAR Data Set Release 2012: Ligands, Affinities, Complexes, and Docking Decoys

5. Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment

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1. Edaravone N-benzyl pyridinium derivatives: BACE-1 inhibition, kinetics and in silico binding pose determination;European Journal of Pharmaceutical Sciences;2024-10

2. Fully Flexible Molecular Alignment Enables Accurate Ligand Structure Modeling;Journal of Chemical Information and Modeling;2024-07-29

3. Generic protein–ligand interaction scoring by integrating physical prior knowledge and data augmentation modelling;Nature Machine Intelligence;2024-06-06

4. A new paradigm for applying deep learning to protein–ligand interaction prediction;Briefings in Bioinformatics;2024-03-27

5. PackDock: a Diffusion Based Side Chain Packing Model for Flexible Protein-Ligand Docking;2024-02-03

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