The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
MassiveFold: unveiling AlphaFold’s hidden potential with optimized and parallelized massive sampling
Open accessPublished version of a preprint
Abstract
Massive sampling in AlphaFold enables access to increased structural diversity. In combination with its efficient confidence ranking, this unlocks elevated modeling capabilities for monomeric structures and foremost for protein assemblies. However, the approach struggles with GPU cost and data storage. Here we introduce MassiveFold, an optimized and customizable version of AlphaFold that runs predictions in parallel, reducing the computing time from several months to hours. MassiveFold is scalable and able to run on anything from a single computer to a large GPU infrastructure, where it can fully benefit from all the computing nodes.
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Citations
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861
ColabFold - Making protein folding accessible to all
Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2021) · doi:10.1101/2021.08.15.456425 · Cited by 9,391
Varadi, M., Anyango, S., Deshpande, M., Nair, S., Natassia, C., Yordanova, G., Yuan, D., Stroe, O., Wood, G., Laydon, A., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1061 · Cited by 7,850
Protein complex prediction with AlphaFold-Multimer
Evans, R., O’Neill, M., Pritzel, A., Antropova, N., Senior, A., Green, T., Žídek, A., Bates, R., Blackwell, S., Yim, J., et al. (2021) · doi:10.1101/2021.10.04.463034 · Cited by 3,808
Critical assessment of methods of protein structure prediction (CASP)—Round XIV
Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K., & Moult, J. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26237 · Cited by 503
Critical assessment of methods of protein structure prediction ( CASP )—Round XV
Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K., & Moult, J. (2023) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26617 · Cited by 148
Improved Multimer Prediction using Massive Sampling with AlphaFold in CASP15
Wallner, B. (2023) · doi:10.22541/au.168170986.60158084/v1 · Cited by 53
Self-citation
Flagged first, then by citations
Research works printed but not linked: 6
- Lensink, M. F. et al. Impact of AlphaFold on structure prediction of protein complexes: the CASP15-CAPRI experiment. Proteins 91, 1658–1683 (2023). · DOI
- Johansson-Åkhe, I. & Wallner, B. Improving peptide-protein docking with AlphaFold-Multimer using forced sampling. Front. Bioinform. 2, 959160 (2022). · DOI · Paper page
- Wallner, B. AFsample: improving multimer prediction with AlphaFold using massive sampling. Bioinform. Oxf. Engl. 39, btad573 (2023). · DOI · Paper page
- Yin, R. & Pierce, B. G. Evaluation of AlphaFold antibody-antigen modeling with implications for improving predictive accuracy. Protein Sci. Publ. Protein Soc. 33, e4865 (2024). · DOI · Paper page
- Sala, D., Engelberger, F., Mchaourab, H. S. & Meiler, J. Modeling conformational states of proteins with AlphaFold. Curr. Opin. Struct. Biol. 81, 102645 (2023). · DOI · Paper page
- Raouraoua, N., Lensink, M. F. & Brysbaert, G. Massive sampling strategy for antibody-antigen targets in CAPRI Round 55 with MassiveFold. Preprint at TechRxiv https://doi.org/10.22541/au.172592104.47153431/v2 (2024). · DOI
Cited by
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An in-depth review of AI-powered advancements in cancer drug discovery
Le, M. H. N., Nguyen, P. K., Nguyen, T. P. T., Nguyen, H. Q., Tam, D. N. H., Huynh, H. H., Huynh, P. K., & Le, N. Q. K. (2025) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2025.167680 · Cited by 15
Metadata
- Authors
- Raouraoua, N., Mirabello, C., Véry, T., Blanchet, C., Wallner, B., Lensink, M. F., & Brysbaert, G.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Linköping University (SE)
- Corresponding author
- Brysbaert, Guillaume
- Venue
- Nature Computational Science
- Published
- 2024-11-11
- Volume
- 4
- Issue
- 11
- Pages
- 824-828
- ISSN
- 2662-8457 (ISSN-L)
- PMC
- PMC11578886
- OpenAlex
- W4404224798
- Cited by
- 51
- References
- 8
- Citations by year
- 2026: 15 · 2025: 34 · 2024: 2
- FWCI
- 6.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Computational Science (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- DiVA (Linkoping University) (submittedVersion, other-oa)
- LillOA (Université de Lille (University Of Lille)) (submittedVersion)
- Funders
- Knut och Alice Wallenbergs Stiftelse
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- AlphaFold, protein structure prediction, parallel computing, GPU acceleration, protein assembly, structural diversity, monomeric protein
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