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Related Concept Videos

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Amyloid fibrils are aggregates of misfolded proteins.  Under most circumstances, misfolded proteins are either refolded by chaperone proteins or degraded by the proteasome. However, in the case of a mutation or a disease, these proteins can accumulate to form large clusters and often further assemble to form elongated fibers, called fibrils. 
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Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
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Screening for Amyloid Aggregation by Semi-Denaturing Detergent-Agarose Gel Electrophoresis
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Predicting the aggregation propensity of prion sequences.

Alba Espargaró1, Maria Antònia Busquets1, Joan Estelrich1

  • 1Department of Physical Chemistry, Faculty of Pharmacy, University of Barcelona, Avda. Joan XXIII 27-31, E-08028 Barcelona, Spain; Institute of Nanoscience and Nanotechnology of the University of Barcelona (IN(2)UB), Spain.

Virus Research
|March 10, 2015
PubMed
Summary
This summary is machine-generated.

Prions cause neurodegenerative diseases by forming infectious, self-perpetuating protein aggregates. In silico prediction of prion and amyloid propensities aids in identifying new prion sequences and therapeutic targets.

Keywords:
Amyloid algorithmAmyloid predictionHot-spotPrion predictionβ-Sheet prediction

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Area of Science:

  • Biochemistry
  • Neuroscience
  • Molecular Biology

Background:

  • Prions are infectious protein agents causing neurodegenerative diseases in mammals and protein-based genetic elements in fungi.
  • Prions are a subclass of amyloids, characterized by self-aggregation into self-perpetuating and infectious fibers with a common cross-β structure.
  • Amyloid fibril formation is a complex process, and the presence of amyloid-prone regions does not always guarantee amyloid formation or prion activity.

Purpose of the Study:

  • To explore the utility of in silico prediction for identifying potential prion sequences in mammals.
  • To investigate the role of amyloid-prone regions in prion formation and understand the impact of mutations and polymorphisms.
  • To identify potential therapeutic targets for prion-related diseases.

Main Methods:

  • Utilizing mathematical algorithms to predict amyloid and prion propensities based on polypeptide sequences.
  • Analyzing the characteristics of amyloid fibril formation, including intermolecular β-sheet propensity.
  • Reviewing existing literature on the limitations of in silico prediction and the distinction between amyloid fibrils and prions.

Main Results:

  • In silico prediction methods can help detect potential new prion sequences in mammals, despite limitations.
  • Identifying amyloid-prone regions within prion sequences can offer insights into disease mechanisms.
  • The study highlights the potential of computational approaches in prion research.

Conclusions:

  • In silico prediction of prion and amyloid propensities is a valuable tool for discovering novel prion sequences.
  • Understanding amyloid-prone regions in prions is crucial for studying mutations, polymorphisms, and developing therapeutic strategies.
  • Computational methods offer promising avenues for advancing prion disease research and therapeutic development.