Prediction of "aggregation-prone" and "aggregation-susceptible" regions in proteins associated with neurodegenerative diseases.
By Amol P Pawar, Kateri F. Dubay, J. Zurdo, Fabrizio Chiti, Michele Vendruscolo, Christopher M. Dobson. Journal of Molecular Biology, 2005
596 citations recorded by the source corpus.
Subfields: Molecular Biology, Neurology, Physiology
View Paper: https://www.semanticscholar.org/paper/bb8729399e4d17b59d9fc549247c27f60074ee8e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Yaoqi Zhou
- Zhixiu Li
- Michele Vendruscolo
- Christopher M. Dobson
- Fabrizio Chiti
- Pietro Sormanni
- F. Aprile
- Eshel Faraggi
In Neurology
In Physiology
- Christopher M. Dobson
- Michele Vendruscolo
- Fabrizio Chiti
- F. Aprile
- Pietro Sormanni
- Tuomas P. J. Knowles
- F. Hartl
- E. K. Kim
Citations in the corpus
- Protein Misfolding, Amyloid Formation, and Human Disease: A Summary of Progress Over the Last Decade. (2017, background): “Figure 4 shows the comparison between the aggregation propensity profiles generated by one representative algorithm (131, 132) for four representative peptides and proteins, namely Aβ, αs, IAPP, and the K19 fragment from tau, and the experimental data available for the fibrils of these four systems.”
- Missense meanderings in sequence space: a biophysical view of protein evolution (2005, background): “Although it seems that all proteins are able to aggregate, they differ substantially in their intrinsic propensity to do so under physiological condition”
- AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides (2007, unknown): “Pawar and co-workers proposed an aggregation scale based on phenomenological expressions relating protein intrinsic factors with the aggregation rates of a set point mutants scattered along acylphosphatase sequence and of a few other polypeptides [30].”
- The CamSol method of rational design of protein mutants with enhanced solubility. (2015, methodology): “In order to obtain a “solubility profile”, that is, a function that associates to each residue in an amino acid sequence a number that reflects its impact on the overall solubility, in this work, we used a strategy similar to that of the Zyggregator method of predicting protein aggregation propensit”
- β-Lactoglobulin nanofibrils: Effect of temperature on fibril formation kinetics, fibril morphology and the rheological properties of fibril dispersions (2012, unknown): “Specific regions of the intact or nicked molecules with high hydrophobicity, low charge and the ability to form β -sheets (Pawar, et al. , 2005) would form the core of the fibril, with connecting or outlying regions being more mobile and solvent-exposed (Török, et al. , 2002) and therefore…”
- Intrinsically Semi-disordered State and Its Role in Induced Folding and Protein Aggregation (2013, background): “The role of semi-disorder in protein aggregation, however, seems to contradict observed anti-correlation between disorder propensity and amyloid aggregation propensity of 20 amino-acid residue types [46, 47].”