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AGGRESCAN3D(A3D):用于预测蛋白质结构聚集特性的服务器。

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

作者信息

Zambrano Rafael, Jamroz Michal, Szczasiuk Agata, Pujols Jordi, Kmiecik Sebastian, Ventura Salvador

机构信息

Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, 08193, Spain.

University of Warsaw, Faculty of Chemistry, Pasteura 1, Warsaw, Poland.

出版信息

Nucleic Acids Res. 2015 Jul 1;43(W1):W306-13. doi: 10.1093/nar/gkv359. Epub 2015 Apr 16.

DOI:10.1093/nar/gkv359
PMID:25883144
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4489226/
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/.

摘要

蛋白质聚集是越来越多疾病的基础,也是治疗性蛋白质开发的主要瓶颈。我们目前对蛋白质聚集分子决定因素的理解已体现在一系列用于识别易聚集位点的预测算法中。这些方法大多数仅依赖于序列。因此,它们难以预测折叠球状蛋白质的聚集特性,因为易聚集位点在序列上通常不连续或埋藏在天然结构内部。AGGRESCAN3D(A3D)服务器通过考虑蛋白质结构和来自成熟的AGGRESCAN方法的实验聚集倾向量表,克服了这些局限性。使用A3D服务器,可以对已识别的易聚集残基进行虚拟突变,以设计溶解度更高的变体,或测试致病突变的影响。此外,A3D服务器能够考虑溶液中蛋白质结构的动态波动,这可能会影响聚集倾向。这在A3D动态模式下是可行的,该模式利用CABS-flex方法对球状蛋白质的灵活性进行快速模拟。可通过http://biocomp.chem.uw.edu.pl/A3D/访问A3D服务器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/2f6e23ef34ca/gkv359fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/c1fafd16b112/gkv359fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/eebe0569d762/gkv359fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/c17c49ac4494/gkv359fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/2f6e23ef34ca/gkv359fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/c1fafd16b112/gkv359fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/eebe0569d762/gkv359fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/c17c49ac4494/gkv359fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/4489226/2f6e23ef34ca/gkv359fig4.jpg

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