The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Protein Folding in the Hydrophobic-Hydrophilic ( HP ) Model is NP-Complete
Abstract
One of the simplest and most popular biophysical models of protein folding is the hydrophobic-hydrophilic (HP) model. The HP model abstracts the hydrophobic interaction in protein folding by labeling the amino acids as hydrophobic (H for nonpolar) or hydrophilic (P for polar). Chains of amino acids are configured as self-avoiding walks on the 3D cubic lattice, where an optimal conformation maximizes the number of adjacencies between H's. In this paper, the protein folding problem under the HP model on the cubic lattice is shown to be NP-complete. This means that the protein folding problem belongs to a large set of problems that are believed to be computationally intractable.
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Cites
Funnels, pathways, and the energy landscape of protein folding: A synthesis
Bryngelson, J. D., Onuchic, J. N., Socci, N. D., & Wolynes, P. G. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340210302 · Cited by 2,648
Principles of protein folding — A perspective from simple exact models
Dill, K. A., Bromberg, S., Yue, K., Chan, H. S., Fiebig, K. M., Yee, D. P., & Thomas, P. D. (1995) · Protein Science · doi:10.1002/pro.5560040401 · Cited by 1,525
Theory for the folding and stability of globular proteins
Dill, K. A. (1985) · Biochemistry · doi:10.1021/bi00327a032 · Cited by 1,249
The protein threading problem with sequence amino acid interaction preferences is NP-complete
Lathrop, R. H. (1994) · "Protein Engineering, Design and Selection" · doi:10.1093/protein/7.9.1059 · Cited by 276
Unger, R., & Moult, J. (1993) · Bulletin of Mathematical Biology · doi:10.1007/bf02460703 · Cited by 196
Fraenkel, A. S. (1993) · Bulletin of Mathematical Biology · doi:10.1007/bf02460704 · Cited by 154
Robust Proofs of NP-Hardness for Protein Folding: General Lattices and Energy Potentials
Hart, W. E., & Istrail, S. (1997) · Journal of Computational Biology · doi:10.1089/cmb.1997.4.1 · Cited by 139
Computational complexity of a problem in molecular structure prediction
Ngo, J., & Marks, J. (1992) · Protein Engineering Design and Selection · doi:10.1093/protein/5.4.313 · Cited by 99
Agarwala, R., Batzoglou, S., Dančík, V., Decatur, S. E., Farach-Colton, M., Hannenhalli, S. S., Muthukrishnan, S., & Skiena, S. (1997) · Research in Computational Molecular Biology · doi:10.1145/267521.267522 · Cited by 88
Agarwala, R., Batzoglou, S., Dančík, V., Decatur, S. E., Hannenhalli, S. S., Farach-Colton, M., Muthukrishnan, S., & Skiena, S. (1997) · Journal of Computational Biology · doi:10.1089/cmb.1997.4.275 · Cited by 59
Cited by
Ising formulations of many NP problems
Lucas, A. (2014) · Frontiers in Physics · doi:10.3389/fphy.2014.00005 · Cited by 2,512
Finding low-energy conformations of lattice protein models by quantum annealing
Perdomo-Ortiz, A., Dickson, N., Drew-Brook, M., Rose, G., & Aspuru-Guzik, A. (2012) · Scientific Reports · doi:10.1038/srep00571 · Cited by 366
Simulating Chemistry Using Quantum Computers
Kassal, I., Whitfield, J. D., Perdomo-Ortiz, A., Yung, M.-H., & Aspuru-Guzik, A. (2011) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-032210-103512 · Cited by 352
The prospects of quantum computing in computational molecular biology
Outeiral, C., Strahm, M., Shi, J., Morris, G. M., Benjamin, S. C., & Deane, C. M. (2021) · WIREs Computational Molecular Science · doi:10.1002/wcms.1481 · Cited by 232
Perdomo, A., Truncik, C., Tubert-Brohman, I., Rose, G., & Aspuru-Guzik, A. (2008) · Physical Review A · doi:10.1103/physreva.78.012320 · Cited by 120
Metadata
- Authors
- BERGER, B., & LEIGHTON, T.
- Venue
- Journal of Computational Biology
- Publisher
- SAGE Publications
- Published
- 1998-01
- Volume
- 5
- Issue
- 1
- Pages
- 27-40
- ISSN
- 1066-5277 (ISSN-L)
- 1557-8666
- OpenAlex
- W2611927968
- Cited by
- 420
- References
- 11
- FWCI
- 2.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- BERGER, B., & LEIGHTON, T. (1998). Protein Folding in the Hydrophobic-Hydrophilic ( HP ) Model is NP-Complete. Journal of Computational Biology. https://doi.org/10.1089/cmb.1998.5.27
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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.
