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A gradient-directed Monte Carlo method for global optimization in a discrete space: Application to protein sequence design and folding
We apply the gradient-directed Monte Carlo (GDMC) method to select optimal members of a discrete space, the space of chemically viable proteins described by a model Hamiltonian. In contrast to conventional Monte Carlo approaches, our GDMC method uses local property gradients with respect to chemical...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
American Institute of Physics
2009
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2776780/ https://ncbi.nlm.nih.gov/pubmed/20568857 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1063/1.3236834 |
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