4月26日,，德國杜伊斯堡－埃森大學(xué)發(fā)表公報(bào)說，該校研究人員開發(fā)出一種能快速,、準(zhǔn)確判斷I型艾滋病病毒（HIV－1）感染情況的電腦程序,，這一成果將有助于提高治療艾滋病的水平,。
公報(bào)說，HIV－1侵入受體細(xì)胞是通過病毒殼膜蛋白gp120和受體細(xì)胞CD4之間的相互作用來實(shí)現(xiàn)的,，此外還會(huì)根據(jù)不同病況而利用CCR5和CXCR4這兩種輔受體細(xì)胞中的一種,。通常而言，在HIV－1早期感染階段,，CCR5受感染數(shù)量較多,，而CXCR4受感染則標(biāo)志著HIV－1感染進(jìn)入晚期。因此,，能夠確認(rèn)被感染的輔受體細(xì)胞類型對(duì)于監(jiān)測病情進(jìn)展和對(duì)癥下藥有重要意義,。
杜伊斯堡－埃森大學(xué)醫(yī)學(xué)生物技術(shù)中心研究人員開發(fā)出的電腦程序能在數(shù)秒內(nèi)判斷出輔受體的受感染情況，其結(jié)果準(zhǔn)確率達(dá)95％以上,，可與傳統(tǒng)檢測法媲美,，但速度要快得多。
這一成果發(fā)表在美國《公共科學(xué)圖書館·計(jì)算生物學(xué)》雜志上,。(生物谷Bioon.com)
生物谷推薦原文出處：
PLoS Comput Biol doi:10.1371/journal.pcbi.1000743
Prediction of Co-Receptor Usage of HIV-1 from Genotype
J. Nikolaj Dybowski#, Dominik Heider#, Daniel Hoffmann*
Department of Bioinformatics, Center for Medical Biotechnology, University of Duisburg-Essen, Essen, Germany
Human Immunodeficiency Virus 1 uses for entry into host cells a receptor (CD4) and one of two co-receptors (CCR5 or CXCR4). Recently, a new class of antiretroviral drugs has entered clinical practice that specifically bind to the co-receptor CCR5, and thus inhibit virus entry. Accurate prediction of the co-receptor used by the virus in the patient is important as it allows for personalized selection of effective drugs and prognosis of disease progression. We have investigated whether it is possible to predict co-receptor usage accurately by analyzing the amino acid sequence of the main determinant of co-receptor usage, i.e., the third variable loop V3 of the gp120 protein. We developed a two-level machine learning approach that in the first level considers two different properties important for protein-protein binding derived from structural models of V3 and V3 sequences. The second level combines the two predictions of the first level. The two-level method predicts usage of CXCR4 co-receptor for new V3 sequences within seconds, with an area under the ROC curve of 0.937±0.004. Moreover, it is relatively robust against insertions and deletions, which frequently occur in V3. The approach could help clinicians to find optimal personalized treatments, and it offers new insights into the molecular basis of co-receptor usage. For instance, it quantifies the importance for co-receptor usage of a pocket that probably is responsible for binding sulfated tyrosine.
