Simulations as analytical tools to understand protein aggregation and predict amyloid conformation.

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Abstract Text:

Buyong Ma,Ruth Nussinov,

Computational tools are increasingly being applied to solve the protein aggregation problem, providing insight into amyloid structures and aggregation mechanisms. The paradigm of Abeta amyloid structure elucidation provides an example of an innovative experimental design and endeavor, echoing the computational testing of possible molecular associations, all reflected in the current Ma-Nussinov-Tycko model of the Abeta amyloid. Simulations have shown that dimer formation can lock some misfolded conformations, and catalyze the shift of the equilibrium away from the native state. In most cases, a stable amyloid seed requires at least two-layered beta-sheets with properly registered side-chains. Under kinetic control, the final protein aggregations are the outcome of maximizing the van der Waals interactions between side chains and backbone hydrogen bonds.

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Publishing Authors By Initials

B Ma,R Nussinov,

For similar abstracts research abstracts see: abstracts research

PUBMED ID PMID:

MEDLINE DATE:

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Journal Published:

PUBLICATION TYPE: Review

Journal: Current opinion in chemical biology

VOLUME: 10

Page Numbers: 445-52

Journal Abbreviation:

ISSN: 1367-5931

DAY: 28

MONTH: 08

YEAR: 2006

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 9811312

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Keywords Mesh Terms:

KEYWORDS:

MESH TERMS:

Chemical & Substance for Abstract: Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Information

Substance Name:

Registry Number:

Grant and Affiliation Information for Simulations as analytical tools to understand protein aggregation and predict amyloid conformation.

AFFILIATION: Basic Research Program, SAIC-Frederick Inc, Center for Cancer Research, Nanobiology Program, NCI-Frederick, Frederick MD 21702, USA.

Country: England

AGENCY:

GRANT:

ACRONYM:

MEDLINETA: Curr Opin Chem Biol

REFSOURCE:

DATABASENAME:

ACCESSION NUMBER:

Number Hits: 0

Simulations as analytical tools to understand protein aggregation and predict amyloid conformation Related Publications

• "Similarity trap" in protein-protein interactions could be carcinogenic: simulations of p53 core domain complexed with 53BP1 and BRCA1 BRCT domains.
• A hierarchical protein folding scheme based on the building block folding model.
• Allosteric effects in the marginally stable von Hippel-Lindau tumor suppressor protein and allostery-based rescue mutant design.
• Allostery: Absence of a Change in Shape Does Not Imply that Allostery Is Not at Play.
• Backbone conformational preferences and pseudorotational ring puckering of 1-aminocyclopentane-1-carboxylic acid.
• Changing the charge distribution of beta-helical-based nanostructures can provide the conditions for charge transfer.
• Conformational study of the protegrin-1 (PG-1) dimer interaction with lipid bilayers and its effect.
• Consensus features in amyloid fibrils: sheet-sheet recognition via a (polar or nonpolar) zipper structure.
• Designing a nanotube using naturally occurring protein building blocks.
• How different are structurally flexible and rigid binding sites? Sequence and structural features discriminating proteins that do and do not undergo conformational change upon ligand binding.
• Interaction of protegrin-1 with lipid bilayers: membrane thinning effect.
• Modeling the Alzheimer Abeta17-42 fibril architecture: tight intermolecular sheet-sheet association and intramolecular hydrated cavities.
• Models of beta-amyloid ion channels in the membrane suggest that channel formation in the bilayer is a dynamic process.
• Modular architecture of protein structures and allosteric communications: potential implications for signaling proteins and regulatory linkages.
• MolAxis: a server for identification of channels in macromolecules.
• Molecular dynamics simulations of Alzheimer Abeta40 elongation and lateral association.
• Nanostructure design using protein building blocks enhanced by conformationally constrained synthetic residues.
• New structures help the modeling of toxic amyloidss ion channels.
• Principles of nanostructure design with protein building blocks.
• Residue centrality, functionally important residues, and active site shape: analysis of enzyme and non-enzyme families.
• Sequence analysis of p53 response-elements suggests multiple binding modes of the p53 tetramer to DNA targets.
• Similar binding sites and different partners: implications to shared proteins in cellular pathways.
• Simulations as analytical tools to understand protein aggregation and predict amyloid conformation.
• Structural basis for p53 binding-induced DNA bending.
• Structural dynamics of the cooperative binding of organic molecules in the human cytochrome P450 3A4.
• Structural stability and dynamics of an amyloid-forming peptide GNNQQNY from the yeast prion sup-35.
• Structure by design: from single proteins and their building blocks to nanostructures.
• Towards drugs targeting multiple proteins in a systems biology approach.
• Trp/Met/Phe hot spots in protein-protein interactions: potential targets in drug design.
• p53-Induced DNA bending: the interplay between p53-DNA and p53-p53 interactions.