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• W2005696873 abstract "Key to successful protein structure prediction is a potential that recognizes the native state from misfolded structures. Recent advances in empirical potentials based on known protein structures include improved reference states for assessing random interactions, sidechain-orientation-dependent pair potentials, potentials for describing secondary or supersecondary structural preferences and, most importantly, optimization protocols that sculpt the energy landscape to enhance the correlation between native-like features and the energy. Improved clustering algorithms that select native-like structures on the basis of cluster density also resulted in greater prediction accuracy. For template-based modeling, these advances allowed improvement in predicted structures relative to their initial template alignments over a wide range of target–template homology. This represents significant progress and suggests applications to proteome-scale structure prediction." @default.
• W2005696873 created "2016-06-24" @default.
• W2005696873 creator A5010808261 @default.
• W2005696873 date "2006-04-01" @default.
• W2005696873 modified "2023-10-01" @default.
• W2005696873 title "In quest of an empirical potential for protein structure prediction" @default.
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• W2005696873 doi "https://doi.org/10.1016/j.sbi.2006.02.004" @default.
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