Identification of nonrandom patterns in structural and mutational data: the case of prion protein
Kuznetsov, I.B.
Rackovsky, S.
Dept. of Biomath. Sci., Mount Sinai Sch. of Med., New York, NY, USA;
This paper appears in: Bioinformatics Conference, 2003. CSB 2003. Proceedings of the 2003 IEEE
Publication Date: 11-14 Aug. 2003
On page(s): 604- 608
ISSN:
ISBN: 0-7695-2000-6
INSPEC Accession Number: 7898775
Digital Object Identifier: 10.1109/CSB.2003.1227420
Current Version Published: 2003-09-08
Abstract
Prion diseases (mad cow disease, CJD, etc.) are a group of fatal neurodegenerative disorders associated with structural conversion of a normal, mostly α-helical cellular prion protein (PrP) into a pathogenic β-sheet-rich conformation. Little is known about which parts of PrP undergo conformational transition and how disease associated mutations facilitate this transition. In this work, we utilize a computational statistical approach to detect unusual patterns in prion protein, (i) We construct a novel entropic index which provides a quantitative measure of context-dependent conformational flexibility of a sequence fragment. This index is used to study conformational flexibility of PrP fragments, (ii) We identify PrP fragments that show unusual intrinsic structural propensities. (Hi) We estimate the statistical significance of clusters of disease-associated PrP mutations using a stochastic model of mutational process with unequal substitution rates and context-dependent mutational hot spots.
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