Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials.

Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Research Abstract Details 

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Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Abstract Text:

Dmitry Rykunov, Fiser,

Statistical distance dependent pair potentials are frequently used in a variety of folding, threading, and modeling studies of proteins. The applicability of these types of potentials is tightly connected to the reliability of statistical observations. We explored the possible origin and extent of false positive signals in statistical potentials by analyzing their distance dependence in a variety of randomized protein-like models. While on average potentials derived from such models are expected to equal zero at any distance, we demonstrate that systematic and significant distortions exist. These distortions originate from the limited statistical counts in local environments of proteins and from the limited size of protein structures at large distances. We suggest that these systematic errors in statistical potentials are connected to the dependence of amino acid composition on protein size and to variation in protein sizes. Additionally, atom-based potentials are dominated by a false positive signal that is due to correlation among distances measured from atoms of one residue to atoms of another residue. The significance of residue-based pairwise potentials at various spatial pair separations was assessed in this study and it was found that as few as approximately 50% of potential values were statistically significant at distances below 4 A, and only at most approximately 80% of them were significant at larger pair separations. A new definition for reference state, free of the observed systematic errors, is suggested. It has been demonstrated to generate statistical potentials that compare favorably to other publicly available ones.

Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Publishing Authors By Initials

D Rykunov,A Fiser,

For similar proteins research abstracts see: proteins research

PUBMED ID PMID:

MEDLINE DATE:

Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Proteins

VOLUME: 67

Page Numbers: 559-68

Journal Abbreviation:

ISSN: 1097-0134

DAY: 15

MONTH: May

YEAR: 2007

Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 8700181

Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Keywords Mesh Terms:

KEYWORDS: Proteins

MESH TERMS: chemistry

Chemical & Substance for Abstract: Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials. Information

Substance Name: Proteins

Registry Number: 0

Grant and Affiliation Information for Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials.

AFFILIATION: Department of Biochemistry, Seaver Center for Bioinformatics, Albert Einstein College of Medicine, Bronx, New York 10461, USA.

Country: United States

AGENCY: United States NIGMS

GRANT: GM62519-04

ACRONYM: GM

MEDLINETA: Proteins

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