Literature DB >> 25883144

AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures.

Rafael Zambrano1, Michal Jamroz2, Agata Szczasiuk2, Jordi Pujols1, Sebastian Kmiecik3, Salvador Ventura4.   

Abstract

Protein aggregation underlies an increasing number of disorders and constitutes a major bottleneck in the development of therapeutic proteins. Our present understanding on the molecular determinants of protein aggregation has crystalized in a series of predictive algorithms to identify aggregation-prone sites. A majority of these methods rely only on sequence. Therefore, they find difficulties to predict the aggregation properties of folded globular proteins, where aggregation-prone sites are often not contiguous in sequence or buried inside the native structure. The AGGRESCAN3D (A3D) server overcomes these limitations by taking into account the protein structure and the experimental aggregation propensity scale from the well-established AGGRESCAN method. Using the A3D server, the identified aggregation-prone residues can be virtually mutated to design variants with increased solubility, or to test the impact of pathogenic mutations. Additionally, A3D server enables to take into account the dynamic fluctuations of protein structure in solution, which may influence aggregation propensity. This is possible in A3D Dynamic Mode that exploits the CABS-flex approach for the fast simulations of flexibility of globular proteins. The A3D server can be accessed at http://biocomp.chem.uw.edu.pl/A3D/.
© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25883144      PMCID: PMC4489226          DOI: 10.1093/nar/gkv359

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  32 in total

Review 1.  The Zyggregator method for predicting protein aggregation propensities.

Authors:  Gian Gaetano Tartaglia; Michele Vendruscolo
Journal:  Chem Soc Rev       Date:  2008-05-27       Impact factor: 54.564

Review 2.  Prediction of the aggregation propensity of proteins from the primary sequence: aggregation properties of proteomes.

Authors:  Virginia Castillo; Ricardo Graña-Montes; Raimon Sabate; Salvador Ventura
Journal:  Biotechnol J       Date:  2011-04-29       Impact factor: 4.677

3.  Amyloidogenic potential of transthyretin variants: insights from structural and computational analyses.

Authors:  Laura Cendron; Antonio Trovato; Flavio Seno; Claudia Folli; Beatrice Alfieri; Giuseppe Zanotti; Rodolfo Berni
Journal:  J Biol Chem       Date:  2009-07-14       Impact factor: 5.157

Review 4.  beta2-microglobulin-derived amyloidosis: an update.

Authors:  J Floege; M Ketteler
Journal:  Kidney Int Suppl       Date:  2001-02       Impact factor: 10.545

5.  Amyotrophic lateral sclerosis and structural defects in Cu,Zn superoxide dismutase.

Authors:  H X Deng; A Hentati; J A Tainer; Z Iqbal; A Cayabyab; W Y Hung; E D Getzoff; P Hu; B Herzfeldt; R P Roos
Journal:  Science       Date:  1993-08-20       Impact factor: 47.728

6.  Experimental free energy surfaces reveal the mechanisms of maintenance of protein solubility.

Authors:  Alfonso De Simone; Anne Dhulesia; Gemma Soldi; Michele Vendruscolo; Shang-Te Danny Hsu; Fabrizio Chiti; Christopher M Dobson
Journal:  Proc Natl Acad Sci U S A       Date:  2011-12-12       Impact factor: 11.205

7.  The role of conformational flexibility in β2-microglobulin amyloid fibril formation at neutral pH.

Authors:  John P Hodkinson; Sheena E Radford; Alison E Ashcroft
Journal:  Rapid Commun Mass Spectrom       Date:  2012-08-30       Impact factor: 2.419

8.  CABS-flex: Server for fast simulation of protein structure fluctuations.

Authors:  Michal Jamroz; Andrzej Kolinski; Sebastian Kmiecik
Journal:  Nucleic Acids Res       Date:  2013-05-08       Impact factor: 16.971

9.  AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides.

Authors:  Oscar Conchillo-Solé; Natalia S de Groot; Francesc X Avilés; Josep Vendrell; Xavier Daura; Salvador Ventura
Journal:  BMC Bioinformatics       Date:  2007-02-27       Impact factor: 3.169

10.  CABS-flex predictions of protein flexibility compared with NMR ensembles.

Authors:  Michal Jamroz; Andrzej Kolinski; Sebastian Kmiecik
Journal:  Bioinformatics       Date:  2014-04-15       Impact factor: 6.937

View more
  58 in total

1.  Computational tools help improve protein stability but with a solubility tradeoff.

Authors:  Aron Broom; Zachary Jacobi; Kyle Trainor; Elizabeth M Meiering
Journal:  J Biol Chem       Date:  2017-07-14       Impact factor: 5.157

2.  Engineering a Cysteine-Free Form of Human Fibroblast Growth Factor-1 for "Second Generation" Therapeutic Application.

Authors:  Xue Xia; Ozan S Kumru; Sachiko I Blaber; C Russell Middaugh; Ling Li; David M Ornitz; Mason A Sutherland; Connie A Tenorio; Michael Blaber
Journal:  J Pharm Sci       Date:  2016-04       Impact factor: 3.534

3.  sw ApoMb Amyloid Aggregation under Nondenaturing Conditions: The Role of Native Structure Stability.

Authors:  Natalya S Katina; Vitalii A Balobanov; Nelly B Ilyina; Victor D Vasiliev; Victor V Marchenkov; Anatoly S Glukhov; Alexey D Nikulin; Valentina E Bychkova
Journal:  Biophys J       Date:  2017-09-05       Impact factor: 4.033

4.  ANTISOMA: A Computational Pipeline for the Reduction of the Aggregation Propensity of Monoclonal Antibodies.

Authors:  Katerina C Nastou; Eleftheria G Karataraki; Nikos C Papandreou; Anna-Isavella G Rerra; Vassiliki P Grimanelli; Ilias Maglogiannis; Stavros J Hamodrakas; Vassiliki A Iconomidou
Journal:  Adv Exp Med Biol       Date:  2020       Impact factor: 2.622

5.  VIPdb, a genetic Variant Impact Predictor Database.

Authors:  Zhiqiang Hu; Changhua Yu; Mabel Furutsuki; Gaia Andreoletti; Melissa Ly; Roger Hoskins; Aashish N Adhikari; Steven E Brenner
Journal:  Hum Mutat       Date:  2019-08-17       Impact factor: 4.878

6.  Purification and characterisation of the dimeric group 12 allergen from Blomia tropicalis heterologously expressed by Escherichia coli Top10F´.

Authors:  Eduardo Santos da Silva; Luis Gustavo Carvalho Pacheco; Antônio Márcio Santana Fernandes; Claudia Asam; Elisânia Fontes Silveira; Carina da Silva Pinheiro; Neuza Maria Alcantara-Neves
Journal:  Mol Biol Rep       Date:  2021-04-29       Impact factor: 2.316

7.  A3D 2.0 Update for the Prediction and Optimization of Protein Solubility.

Authors:  Jordi Pujols; Valentín Iglesias; Jaime Santos; Aleksander Kuriata; Sebastian Kmiecik; Salvador Ventura
Journal:  Methods Mol Biol       Date:  2022

8.  Characterization of TDP-43 RRM2 Partially Folded States and Their Significance to ALS Pathogenesis.

Authors:  Davide Tavella; Jill A Zitzewitz; Francesca Massi
Journal:  Biophys J       Date:  2018-09-21       Impact factor: 4.033

Review 9.  Protein aggregation: in silico algorithms and applications.

Authors:  R Prabakaran; Puneet Rawat; A Mary Thangakani; Sandeep Kumar; M Michael Gromiha
Journal:  Biophys Rev       Date:  2021-01-17

10.  Solubility and Aggregation of Selected Proteins Interpreted on the Basis of Hydrophobicity Distribution.

Authors:  Magdalena Ptak-Kaczor; Mateusz Banach; Katarzyna Stapor; Piotr Fabian; Leszek Konieczny; Irena Roterman
Journal:  Int J Mol Sci       Date:  2021-05-08       Impact factor: 5.923

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.