
pmid: 14988117
arXiv: q-bio/0310034
Abstract Motivation: Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone or by non-local tertiary interactions? To answer this question, we measure the entropy densities of primary and secondary structure sequences, and the local inter-sequence mutual information density. Results: We find that the important inter-sequence interactions are short ranged, that correlations between neighboring amino acids are essentially uninformative and that only one-fourth of the total information needed to determine the secondary structure is available from local inter-sequence correlations. These observations support the view that the majority of most proteins fold via a cooperative process where secondary and tertiary structure form concurrently. Moreover, existing single-sequence secondary structure prediction algorithms are almost optimal, and we should not expect a dramatic improvement in prediction accuracy. Availability: Both the data sets and analysis code are freely available from our Web site at http://compbio.berkeley.edu/
Models, Molecular, Models, Statistical, Sequence Homology, Amino Acid, Entropy, Molecular Sequence Data, Statistics as Topic, Proteins, Biomolecules (q-bio.BM), Markov Chains, Protein Structure, Secondary, Quantitative Biology - Biomolecules, Models, Chemical, Sequence Analysis, Protein, FOS: Biological sciences, Computer Simulation, Amino Acid Sequence, Sequence Alignment, Algorithms
Models, Molecular, Models, Statistical, Sequence Homology, Amino Acid, Entropy, Molecular Sequence Data, Statistics as Topic, Proteins, Biomolecules (q-bio.BM), Markov Chains, Protein Structure, Secondary, Quantitative Biology - Biomolecules, Models, Chemical, Sequence Analysis, Protein, FOS: Biological sciences, Computer Simulation, Amino Acid Sequence, Sequence Alignment, Algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 65 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
