AGGRESCAN : a server for the prediction and evaluation of &quot;hot spots&quot; of aggregation in polypeptides

Conchillo-Solé, Oscar; Sánchez de Groot, Natalia; Avilés, Francesc Xavier; Vendrell i Roca, Josep; Daura i Ribera, Xavier; Ventura, Salvador

doi:10.1186/1471-2105-8-65

Cita bibliogràfica -- Enllaç permanent: https://ddd.uab.cat/record/112404

Web of Science: 751 cites, Scopus: 779 cites, Google Scholar: cites,

AGGRESCAN : a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides
Conchillo-Solé, Oscar

(Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Sánchez de Groot, Natalia

(Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Avilés, Francesc Xavier

(Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Vendrell i Roca, Josep

(Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Daura i Ribera, Xavier

(Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Ventura, Salvador

(Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")

Data:	2007
Resum:	Background: Protein aggregation correlates with the development of several debilitating human disorders of growing incidence, such as Alzheimer's and Parkinson's diseases. On the biotechnological side, protein production is often hampered by the accumulation of recombinant proteins into aggregates. Thus, the development of methods to anticipate the aggregation properties of polypeptides is receiving increasing attention. AGGRESCAN is a web-based software for the prediction of aggregation-prone segments in protein sequences, the analysis of the effect of mutations on protein aggregation propensities and the comparison of the aggregation properties of different proteins or protein sets. Results: AGGRESCAN is based on an aggregation-propensity scale for natural amino acids derived from in vivo experiments and on the assumption that short and specific sequence stretches modulate protein aggregation. The algorithm is shown to identify a series of protein fragments involved in the aggregation of disease-related proteins and to predict the effect of genetic mutations on their deposition propensities. It also provides new insights into the differential aggregation properties displayed by globular proteins, natively unfolded polypeptides, amyloidogenic proteins and proteins found in bacterial inclusion bodies. Conclusion: By identifying aggregation-prone segments in proteins, AGGRESCAN http://bioinf. uab. es/aggrescan/ webcite shall facilitate (i) the identification of possible therapeutic targets for anti-depositional strategies in conformational diseases and (ii) the anticipation of aggregation phenomena during storage or recombinant production of bioactive polypeptides or polypeptide sets.
Ajuts:	Ministerio de Educación y Ciencia BIO2003-02848 Ministerio de Educación y Ciencia BIO2004-05879 Agència de Gestió d'Ajuts Universitaris i de Recerca 2005/SGR-00037 Agència de Gestió d'Ajuts Universitaris i de Recerca 2005/SGR-01037
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; Versió publicada
Publicat a:	BMC bioinformatics, Vol. 8, N. 65 (February 2007) , p. 1-17, ISSN 1471-2105