dorsal/arxiv
View SchemaProteins associated with diseases show enhanced sequence correlation between charged residues
| Authors | Ruxandra I. Dima, D. Thirumalai |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0405006 |
| URL | https://arxiv.org/abs/q-bio/0405006 |
Abstract
Function of proteins or a network of interacting proteins often involves communication between residues that are well separated in sequence. The classic example is the participation of distant residues in allosteric regulation. Bioinformatic and structural analysis methods have been introduced to infer residues that are correlated. Recently, increasing attention has been paid to obtain the sequence properties that determine the tendency of disease related proteins (Abeta peptides, prion proteins, transthyretin etc.) to aggregate and form fibrils. Motivated in part by the need to identify sequence characteristics that indicate a tendency to aggregate, we introduce a general method that probes covariations in charged residues along the sequence in a given protein family. The method, which involves computing the Sequence Correlation Entropy (SCE) using the quenched probability Psk(i,j) of finding a residue pair at a given sequence separation sk, allows us to classify protein families in terms of their SCE. Our general approach may be a useful way in obtaining evolutionary covariations of amino acid residues on a genome wide level.
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"abstract": "Function of proteins or a network of interacting proteins often involves\ncommunication between residues that are well separated in sequence. The classic\nexample is the participation of distant residues in allosteric regulation.\nBioinformatic and structural analysis methods have been introduced to infer\nresidues that are correlated. Recently, increasing attention has been paid to\nobtain the sequence properties that determine the tendency of disease related\nproteins (Abeta peptides, prion proteins, transthyretin etc.) to aggregate and\nform fibrils. Motivated in part by the need to identify sequence\ncharacteristics that indicate a tendency to aggregate, we introduce a general\nmethod that probes covariations in charged residues along the sequence in a\ngiven protein family. The method, which involves computing the Sequence\nCorrelation Entropy (SCE) using the quenched probability Psk(i,j) of finding a\nresidue pair at a given sequence separation sk, allows us to classify protein\nfamilies in terms of their SCE. Our general approach may be a useful way in\nobtaining evolutionary covariations of amino acid residues on a genome wide\nlevel.",
"arxiv_id": "q-bio/0405006",
"authors": [
"Ruxandra I. Dima",
"D. Thirumalai"
],
"categories": [
"q-bio.BM"
],
"title": "Proteins associated with diseases show enhanced sequence correlation between charged residues",
"url": "https://arxiv.org/abs/q-bio/0405006"
},
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