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Cleavage site analysis in picornaviral polyproteins: discovering cellular targets by neural networks.

機譯：微小病毒蛋白的切割位點分析：通過神經(jīng)網(wǎng)絡(luò)發(fā)現(xiàn)細胞靶標。

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Picornaviral proteinases are responsible for maturation cleavages of the viral polyprotein, but also catalyze the degradation of cellular targets. Using graphical visualization techniques and neural network algorithms, we have investigated the sequence specificity of the two proteinases 2Apro and 3Cpro. The cleavage of VP0 (giving rise to VP2 and VP4), which is carried out by a so-far unknown proteinase, was also examined. In combination with a novel surface exposure prediction algorithm, our neural network approach successfully distinguishes known cleavage sites from noncleavage sites and yields a more consistent definition of features common to these sites. The method is able to predict experimentally determined cleavage sites in cellular proteins. We present a list of mammalian and other proteins that are predicted to be possible targets for the viral proteinases. Whether these proteins are indeed cleaved awaits experimental verification. Additionally, we report several errors detected in the protein databases. A computer server for prediction of cleavage sites by picornaviral proteinases is publicly available at the e-mail address NetPicoRNA@cbs.dtu.dk or via WWW at http:@www.cbs.dtu.dk/services/NetPicoRNA/.

機譯：Picornaviral蛋白酶負責病毒多蛋白的成熟裂解，但也可催化細胞靶標的降解。使用圖形化可視化技術(shù)和神經(jīng)網(wǎng)絡(luò)算法，我們研究了兩種蛋白酶2Apro和3Cpro的序列特異性。還檢查了VP0的裂解（產(chǎn)生VP2和VP4），這種裂解是由一種迄今未知的蛋白酶完成的。結(jié)合新穎的表面暴露預(yù)測算法，我們的神經(jīng)網(wǎng)絡(luò)方法成功地將已知的切割位點與非切割位點區(qū)分開，并產(chǎn)生了這些位點共有特征的更一致定義。該方法能夠預(yù)測細胞蛋白中實驗確定的切割位點。我們提出了哺乳動物和其他蛋白質(zhì)的列表，預(yù)計它們可能是病毒蛋白酶的靶標。這些蛋白質(zhì)是否確實被切割等待實驗驗證。此外，我們報告了蛋白質(zhì)數(shù)據(jù)庫中檢測到的一些錯誤。可以通過電子郵件地址NetPicoRNA@cbs.dtu.dk或通過WWW，網(wǎng)址為http：//@www.cbs.dtu.dk/services/NetPicoRNA/公開獲得用于預(yù)測皮甲病毒的蛋白酶切割位點的計算機服務(wù)器。

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Blom, N.; Hansen, J.; Blaas, D.; Brunak, S.;
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年度 1996
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正文語種 en
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Cleavage site analysis in picornaviral polyproteins: discovering cellular targets by neural networks.

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