Computational models for the prediction of amyloid fibril forming protein segments

Nair, Smitha Sunil Kumaran and Subbareddy , NV and Hareesha , K S (2010) Computational models for the prediction of amyloid fibril forming protein segments. In: 1st International Conference on Bioinformatics and Systems Biology, Feb 2010, Annamalai University.

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Abstract

A reliable identification of amyloid fibril forming segments in proteins has a great impact in the development of antiamyloid therapeutics. Amyloid fibrils are associated with a number of pathologies including neurodegenerative diseases that result in brain tissue atrophy. Experimental evidence is compelling in favor of the hypothesis that small regions of a protein (hexpeptides) are responsible for its amyloidogenic behavior. Thus, identifying these short peptides is critical for understanding diseases associated with protein misfolding and for developing sequence-targeted anti-aggregation drugs. Researchers initially determined such sequence stretches through wet lab experiments. Owing to the limitations of the molecular techniques for the identification of protein targets, it became apparent that clever computational techniques might enable their discovery in silico. Large amount of protein sequences provided by large scale proteomics initiatives is now demanding for computational methods to predict the candidate segments. Several computational approaches that have been developed for the prediction of fibril forming sequences either use models based on physicochemical properties of the amino acids, or combine atomistic simulations of a protein segment with the microcrystal structure of short fibril-forming peptides, or a sequence pattern obtained by saturation mutagenesis analysis. Even though the algorithms for their predictions have improved over time, accurate predictions still remain a challenging task and are still subject of intense investigations. This study takes into consideration a review and the potential for the computational prediction of short protein hexpeptides associated with amyloid fibrillar aggregates of proteins so that further efforts can be made for their improvement.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Protein misfolding; Amyloid fibril; Hexpeptides; Computational prediction
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 04 Jul 2011 08:47
Last Modified: 04 Jul 2011 08:47
URI: http://eprints.manipal.edu/id/eprint/460

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