The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Ultra-fast FFT protein docking on graphics processors
Open accessAbstract
Motivation: Modelling protein–protein interactions (PPIs) is an increasingly important aspect of structural bioinformatics. However, predicting PPIs using in silico docking techniques is computationally very expensive. Developing very fast protein docking tools will be useful for studying large-scale PPI networks, and could contribute to the rational design of new drugs. Results: The Hex spherical polar Fourier protein docking algorithm has been implemented on Nvidia graphics processor units (GPUs). On a GTX 285 GPU, an exhaustive and densely sampled 6D docking search can be calculated in just 15 s using multiple 1D fast Fourier transforms (FFTs). This represents a 45-fold speed-up over the corresponding calculation on a single CPU, being at least two orders of magnitude times faster than a similar CPU calculation using ZDOCK 3.0.1, and estimated to be at least three orders of magnitude faster than the GPU-accelerated version of PIPER on comparable hardware. Hence, for the first time, exhaustive FFT-based protein docking calculations may now be performed in a matter of seconds on a contemporary GPU. Three-dimensional Hex FFT correlations are also accelerated by the GPU, but the speed-up factor of only 2.5 is much less than that obtained with 1D FFTs. Thus, the Hex algorithm appears to be especially well suited to exploit GPUs compared to conventional 3D FFT docking approaches. Availability: http://hex.loria.fr/ and http://hexserver.loria.fr/ Contact: dave.ritchie@loria.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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.
Integrity signals
Registry
Cites
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.
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
ZDOCK: An initial‐stage protein‐docking algorithm
Chen, R., Li, L., & Weng, Z. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10389 · Cited by 1,393
Principles of docking: An overview of search algorithms and a guide to scoring functions
Halperin, I., Ma, B., Wolfson, H., & Nussinov, R. (2002) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10115 · Cited by 1,294
Cited by
Software for molecular docking: a review
Pagadala, N. S., Syed, K., & Tuszynski, J. (2017) · Biophysical Reviews · doi:10.1007/s12551-016-0247-1 · Cited by 1,522
Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants
Yin, R., Feng, B. Y., Varshney, A., & Pierce, B. G. (2022) · Protein Science · doi:10.1002/pro.4379 · Cited by 335
Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants
Yin, R., Feng, B. Y., Varshney, A., & Pierce, B. G. (2021) · doi:10.1101/2021.10.23.465575 · Cited by 335
Amino-Functionalized Polystyrene Nanoparticles Activate the NLRP3 Inflammasome in Human Macrophages
Lunov, O., Syrovets, T., Loos, C., Nienhaus, G. U., Mailänder, V., Landfester, K., Rouis, M., & Simmet, T. (2011) · ACS Nano · doi:10.1021/nn203596e · Cited by 262
Valapala, M., Wilson, C., Hose, S., Bhutto, I. A., Grebe, R., Dong, A., Greenbaum, S., Gu, L., Sengupta, S., Cano, M., et al. (2014) · Autophagy · doi:10.4161/auto.27292 · Cited by 144
Metadata
- Authors
- Ritchie, D. W., & Venkatraman, V.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-08-04
- Volume
- 26
- Issue
- 19
- Pages
- 2398-2405
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2171778773
- Cited by
- 368
- References
- 2
- FWCI
- 9.57
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Ultra-fast FFT protein docking on graphics processors. https://app.cochat.ai/papers/10.1093/bioinformatics/btq444
- The paper
- Ritchie, D. W., & Venkatraman, V. (2010). Ultra-fast FFT protein docking on graphics processors. Bioinformatics. https://doi.org/10.1093/bioinformatics/btq444
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.