A computational model for predicting transmembrane regions of retroviruses
A computational model for predicting transmembrane regions of retroviruses
复制标题
预测逆转录病毒跨膜区域的计算模型
DOI：
10.1142/s021972001750010x
复制
发表时间：
2017-06-01
影响因子：
1
通讯作者：
Liu，Ruiling
中科院分区：
文献类型：
--
作者：
Liu，Ze;Lv，Hongqiang;Liu，Ruiling
Transmembrane region (TR) is a conserved region of transmembrane (TM) subunit in envelope (env) glycoprotein of retrovirus. Evidences have shown that TR is responsible for anchoring the env glycoprotein on the lipid bilayer and substitution of the TR for a covalently linked lipid anchor abrogates fusion. However, universal software could not achieve sufficient accuracy as TM in env also has several motifs such as signal peptide, fusion peptide and immunosuppressive domain composed largely of hydrophobic residues. In this paper, a support vector machine-based (SVM) model is proposed to identify TRs in retroviruses. Firstly, physicochemical and evolutionary information properties were extracted as original features. And then, the feature importance was analyzed by minimum Redundancy Maximum Relevance (mRMR) feature selection criterion. Our model achieved an Sn of 0.955, Sp of 0.998, ACC of 0.995, MCC of 0.954 using 10-fold cross-validation on the training dataset. These results suggest that the proposed model can be used to predict TRs in non-annotation retroviruses and 11917, 3344, 2, 289 and 6 new putative TRs were found in HERV, HIV, HTLV, SIV, MLV, respectively.
