Unneberg P, Merelo J J, Chacón P, Morán F
Department of Biotechnology, Royal Institute of Technology (KTH), Stockholm, Sweden.
Proteins. 2001 Mar 1;42(4):460-70. doi: 10.1002/1097-0134(20010301)42:4<460::aid-prot50>3.0.co;2-u.
This article presents SOMCD, an improved method for the evaluation of protein secondary structure from circular dichroism spectra, based on Kohonen's self-organizing maps (SOM). Protein circular dichroism (CD) spectra are used to train a SOM, which arranges the spectra on a two-dimensional map. Location in the map reflects the secondary structure composition of a protein. With SOMCD, the prediction of beta-turn has been included. The number of spectra in the training set has been increased, and it now includes 39 protein spectra and 6 reference spectra. Finally, SOM parameters have been chosen to minimize distortion and make the network produce clusters with known properties. Estimation results show improvements compared with the previous version, K2D, which, in addition, estimated only three secondary structure components; the accuracy of the method is more uniform over the different secondary structures.
本文介绍了SOMCD，一种基于Kohonen自组织映射（SOM）从圆二色光谱评估蛋白质二级结构的改进方法。蛋白质圆二色（CD）光谱用于训练SOM，它将光谱排列在二维图上。图中的位置反映了蛋白质的二级结构组成。使用SOMCD时，已将β-转角的预测包括在内。训练集中的光谱数量有所增加，现在包括39个蛋白质光谱和6个参考光谱。最后，选择了SOM参数以最小化失真并使网络产生具有已知特性的聚类。估计结果表明与先前版本K2D相比有所改进，K2D仅估计了三个二级结构成分；该方法在不同二级结构上的准确性更加均匀。
