PreprintCited by 9Computational Drug Discovery MethodsProtein Structure and DynamicsReceptor Mechanisms and Signaling

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Assessing Protein Homology Models with Docking Reproducibility

Open access
Plonski, Alexander P., Reed, Scott M.·2022·Journal of Molecular Graphics and Modelling

Preprint — published as 10.1016/j.jmgm.2023.108430 · Paper page

Abstract

Results of the most recent Critical Assessment of Protein Structure (CASP) competition demonstrate that protein backbones can be predicted with very high accuracy. In particular, the artificial intelligence methods of AlphaFold 2 from DeepMind were able to produce structures that were similar enough to experimental structures that many described the problem of protein prediction solved. However, for such structures to be used for drug docking studies requires precision in the placement of side chain atoms as well. Here we built a library of 1334 small molecules and examined how reproducibly they bound to the same site on a protein using QuickVina-W, a branch of the program Autodock that is optimized for blind searches. We discovered that the higher the backbone quality of the homology model the greater the similarity between the small molecule docking to the experimental and modeled structures. Furthermore, we found that specific subsets of this library were particularly useful for identifying small differences between the best of the best modeled structures. Specifically, when the number of rotatable bonds in the small molecule increased, differences in binding sites became more apparent.

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 · 10.1101/2022.02.17.480964

Cites

1 of 1 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

Flagged first, then by citations

Research works printed but not linked: 31

  1. 10.1146/annurev.biophys.37.092707.153558 · DOI · Paper page
  2. 2019, Applications of Molecular Dynamics Simulation in Structure Prediction of Peptides and Proteins, Comput Struct Biotechnol J, 17, 1162, 10.1016/j.csbj.2019.07.010 · DOI
  3. 10.1126/science.1208351 · DOI · Paper page
  4. 10.1021/ja044449u · DOI
  5. 10.1021/ja808843h · DOI
  6. 2009, Protein structure homology modeling using SWISS-MODEL workspace, Nature Protocols, 4, 1, 10.1038/nprot.2008.197 · DOI
  7. 10.1093/nar/28.1.235 · DOI · Paper page
  8. 2020, Improved protein structure prediction using potentials from deep learning, Nature, 577, 706, 10.1038/s41586-019-1923-7 · DOI · Paper page
  9. Kryshtafovych, A. ; Schwede, T. ; Topf, M. ; Fidelis, K. ; Moult, J. , Critical assessment of methods of protein structure prediction (CASP)-Round XIV. Proteins 2021. · DOI · Paper page
  10. 2021, Highly accurate protein structure prediction for the human proteome, Nature, 596, 590, 10.1038/s41586-021-03828-1 · DOI · Paper page
  11. 10.2174/157340911795677602 · DOI · Paper page
  12. 10.2174/156802611795860951 · DOI
  13. 2017, A benchmark testing ground for integrating homology modeling and protein docking, Proteins, 85, 10, 10.1002/prot.25063 · DOI
  14. Outeiral, C. ; Nissley, D. A. ; Deane, C. M. , Current structure predictors are not learning the physics of protein folding. Bioinformatics 2022. · DOI · Paper page
  15. 2021, Assessing the binding properties of CASP14 targets and models, Proteins, 89, 1922, 10.1002/prot.26209 · DOI · Paper page
  16. 2019, Critical assessment of methods of protein structure prediction (CASP)-Round XIII, Proteins, 87, 1011, 10.1002/prot.25823 · DOI · Paper page
  17. 10.1093/bioinformatics/btt473 · DOI · Paper page
  18. 2015, The FTMap family of web servers for determining and characterizing ligandbinding hot spots of proteins, Nature Protocols, 10, 733, 10.1038/nprot.2015.043 · DOI
  19. 10.1002/pro.4050 · DOI · Paper page
  20. 10.1093/nar/gkw1058 · DOI
  21. 10.1093/nar/gkv1060 · DOI
  22. 10.1093/nar/gkx1089 · DOI · Paper page
  23. 10.1021/ci9902696 · DOI
  24. 10.1002/jcc.21256 · DOI
  25. 2017, Protein-Ligand Blind Docking Using QuickVina-W With Inter-Process Spatio-Temporal Integration, Scientific Reports, 7, 15451, 10.1038/s41598-017-15571-7 · DOI
  26. 10.1016/j.jmgm.2003.12.005 · DOI
  27. Raschka, S. , BioPandas: Working with molecular structures in pandas DataFrames. The Journal of Open Source Software 2017, 2 (14). · DOI
  28. 10.1110/ps.0202302 · DOI
  29. 10.1093/protein/10.11.1241 · DOI
  30. 2015, Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?, Journal of Cheminformatics, 7, 20, 10.1186/s13321-015-0069-3 · DOI
  31. 2018, LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening, Bioinformatics, 34, 2209, 10.1093/bioinformatics/bty081 · DOI

Metadata

Authors
Plonski, A. P., & Reed, S. M.
Affiliations
University of Colorado Denver (US)
Corresponding author
Reed, Scott M.
Venue
Journal of Molecular Graphics and Modelling
Publisher
openRxiv
Published
2022-02-19
Volume
121
Pages
108430-108430
ISSN
1093-3263 (ISSN-L)
OpenAlex
W4320019092
Cited by
9
References
1
Citations by year
2026: 1 · 2025: 2 · 2024: 5 · 2023: 1
FWCI
1.08
Type
journal article
Language
en
Open access
Locations
  • Journal of Molecular Graphics and Modelling (acceptedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
National Institute of General Medical Sciences (T34GM096958)
Topics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
Keywords
small molecule docking, AutoDock, blind docking, rotatable bonds, binding site comparison, AlphaFold2, CASP, protein structure prediction
MeSH terms
Artificial Intelligence, Binding Sites, Ligands, Protein Binding, Protein Conformation, Proteins, Reproducibility of Results

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