Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens, Greece.
PLoS One. 2013;8(1):e54175. doi: 10.1371/journal.pone.0054175. Epub 2013 Jan 10.
The purpose of this work was to construct a consensus prediction algorithm of 'aggregation-prone' peptides in globular proteins, combining existing tools. This allows comparison of the different algorithms and the production of more objective and accurate results. Eleven (11) individual methods are combined and produce AMYLPRED2, a publicly, freely available web tool to academic users (http://biophysics.biol.uoa.gr/AMYLPRED2), for the consensus prediction of amyloidogenic determinants/'aggregation-prone' peptides in proteins, from sequence alone. The performance of AMYLPRED2 indicates that it functions better than individual aggregation-prediction algorithms, as perhaps expected. AMYLPRED2 is a useful tool for identifying amyloid-forming regions in proteins that are associated with several conformational diseases, called amyloidoses, such as Altzheimer's, Parkinson's, prion diseases and type II diabetes. It may also be useful for understanding the properties of protein folding and misfolding and for helping to the control of protein aggregation/solubility in biotechnology (recombinant proteins forming bacterial inclusion bodies) and biotherapeutics (monoclonal antibodies and biopharmaceutical proteins).
这项工作的目的是构建一个组合现有的工具来预测球状蛋白中“易于聚集”肽的共识预测算法。这允许比较不同的算法，并产生更客观和准确的结果。将 11 种（11）个单独的方法进行组合，产生了 AMYLPRED2，这是一个可公开获取的免费学术网络工具（http://biophysics.biol.uoa.gr/AMYLPRED2），用于仅从序列预测蛋白质中的淀粉样决定簇/“易于聚集”肽的共识预测。AMYLPRED2 的性能表明，它的功能优于单个聚集预测算法，这可能是预期的。AMYLPRED2 是一种有用的工具，可用于识别与几种构象疾病（称为淀粉样变性）相关的蛋白质中的淀粉样形成区域，如阿尔茨海默病、帕金森病、朊病毒病和 2 型糖尿病。它也可能有助于了解蛋白质折叠和错误折叠的性质，并有助于控制生物技术（重组蛋白形成细菌包含体）和生物治疗学（单克隆抗体和生物制药蛋白）中的蛋白质聚集/溶解度。
