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首页> 外文期刊>BMC Genomics >SCMMTP: identifying and characterizing membrane transport proteins using propensity scores of dipeptides
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SCMMTP: identifying and characterizing membrane transport proteins using propensity scores of dipeptides

机译：SCMMTP：使用二肽倾向得分鉴定和表征膜转运蛋白

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Background Identifying putative membrane transport proteins (MTPs) and understanding the transport mechanisms involved remain important challenges for the advancement of structural and functional genomics. However, the transporter characters are mainly acquired from MTP crystal structures which are hard to crystalize. Therefore, it is desirable to develop bioinformatics tools for the effective large-scale analysis of available sequences to identify novel transporters and characterize such transporters. Results This work proposes a novel method (SCMMTP) based on the scoring card method (SCM) using dipeptide composition to identify and characterize MTPs from an existing dataset containing 900 MTPs and 660 non-MTPs which are separated into a training dataset consisting 1,380 proteins and an independent dataset consisting 180 proteins. The SCMMTP produced estimating propensity scores for amino acids and dipeptides as MTPs. The SCMMTP training and test accuracy levels respectively reached 83.81% and 76.11%. The test accuracy of support vector machine (SVM) using a complicated classification method with a low possibility for biological interpretation and position-specific substitution matrix (PSSM) as a protein feature is 80.56%, thus SCMMTP is comparable to SVM-PSSM. To identify MTPs, SCMMTP is applied to three datasets including: 1) human transmembrane proteins, 2) a photosynthetic protein dataset, and 3) a human protein database. MTPs showing α-helix rich structure is agreed with previous studies. The MTPs used residues with low hydration energy. It is hypothesized that, after filtering substrates, the hydrated water molecules need to be released from the pore regions. Conclusions SCMMTP yields estimating propensity scores for amino acids and dipeptides as MTPs, which can be used to identify novel MTPs and characterize transport mechanisms for use in further experiments. Availability http://iclab.life.nctu.edu.tw/iclab_webtools/SCMMTP/
机译：背景技术鉴定假定的膜转运蛋白（MTP）并了解所涉及的转运机制仍然是结构和功能基因组学发展的重要挑战。但是，转运子性状主要来自难以结晶的MTP晶体结构。因此，期望开发生物信息学工具，以对可用序列进行有效的大规模分析，以鉴定新的转运蛋白并表征这些转运蛋白。结果这项工作提出了一种基于评分卡方法（SCM）的新方法（SCMMTP），该方法使用二肽组成从包含900个MTP和660个非MTP的现有数据集中识别和表征MTP，现有数据集中分为由1,380种蛋白质和一个包含180种蛋白质的独立数据集。 SCMMTP产生了氨基酸和二肽作为MTP的倾向得分。 SCMMTP培训和测试准确性水平分别达到83.81％和76.11％。支持向量机（SVM）使用复杂分类方法进行生物学解释的可能性很小，并且位置特异性取代矩阵（PSSM）作为蛋白质特征，其测试准确性为80.56％，因​​此SCMMTP可与SVM-PSSM媲美。为了识别MTP，将SCMMTP应用于三个数据集，包括：1）人跨膜蛋白，2）光合蛋白数据集，和3）人蛋白数据库。显示出富含α-螺旋结构的MTP与先前的研究一致。 MTP使用了低水合能量的残留物。假设在过滤基质之后，需要从孔区域释放水合水分子。结论SCMMTP可以估算出氨基酸和二肽作为MTP的倾向得分，可用于鉴定新型MTP并表征转运机制，以用于进一步的实验。可用性http://iclab.life.nctu.edu.tw/iclab_webtools/SCMMTP/

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