Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study analyzing the neurotransmitter/Na+ symporter family.
Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study analyzing the neurotransmitter/Na+ symporter family.
复制标题
评估基于序列的方法在膜积分蛋白中提供功能见解的能力：分析神经递质/Na+共孢子家族的案例研究。
DOI：
10.1186/1471-2105-8-397
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发表时间：
2007-10-17
影响因子：
3
通讯作者：
Roshan, Usman
中科院分区：
文献类型：
--
作者：
Livesay, Dennis R;Kidd, Patrick D;Eskandari, Sepehr;Roshan, Usman
从球状蛋白预测功能位点的努力越来越普遍；然而，这些方法中最成功的通常需要结构洞察力。不幸的是，尽管最近的一些技术进步，膜整合蛋白的结构覆盖仍然很稀疏。因此，基于序列的方法是阐明功能角色的重要替代方法。在本报告中，我们批判性地考察了几种计算方法在两个特定领域提供功能洞察力的能力。首先，系统基因组学方法能否准确描述跨膜整合蛋白家族的功能多样性？第二，基于序列的策略能否准确预测关键功能位点？由于最近解决的结构和大量的实验诱变数据的存在，神经递质/Na+同调蛋白（NSS）家族是一个理想的模型系统来评估我们的预测质量。原始NSS序列数据集包含181个序列，这些序列通过各种方法进行了对齐。由此产生的系统发育树总是包含六个主要的亚科，这与整个家族的功能多样性是一致的。此外，在代表性良好的亚家族中，系统发育聚类概括了几个细微的功能差异。功能位点的预测使用了六种不同的方法（系统发育基序，两种识别亚家族特定位置的方法，以及三种不同的保护分数）。Yamashita等人在最近解决的LeuTAa结构中确定了34个功能位点的规范集，用于评估预测的质量，其中大部分是通过生物信息学方法预测的。值得注意的是，这些位点的重要性在很大程度上被实验诱变所证实。此外，功能站点预测的集合定性地沿着提出的运输路径聚集，进一步证明了它们的实用性。有趣的是，各种预测方案提供的结果主要是相互正交的。然而，当这些方法确实提供重叠的结果时，特异性被证明显著增加（例如，任何三种方法预测的位点的准确性和覆盖率都大于50%）。本文提出的结果清楚地建立了基于序列的生物信息学策略的可行性，以提供NSS家族的功能洞察。因此，我们期望类似的生物信息学研究将在缺乏结构的情况下简化膜积分家族的功能研究。
Efforts to predict functional sites from globular proteins is increasingly common; however, the most successful of these methods generally require structural insight. Unfortunately, despite several recent technological advances, structural coverage of membrane integral proteins continues to be sparse. ConSequently, sequence-based methods represent an important alternative to illuminate functional roles. In this report, we critically examine the ability of several computational methods to provide functional insight within two specific areas. First, can phylogenomic methods accurately describe the functional diversity across a membrane integral protein family? And second, can sequence-based strategies accurately predict key functional sites? Due to the presence of a recently solved structure and a vast amount of experimental mutagenesis data, the neurotransmitter/Na+ symporter (NSS) family is an ideal model system to assess the quality of our predictions. The raw NSS sequence dataset contains 181 sequences, which have been aligned by various methods. The resultant phylogenetic trees always contain six major subfamilies are consistent with the functional diversity across the family. Moreover, in well-represented subfamilies, phylogenetic clustering recapitulates several nuanced functional distinctions. Functional sites are predicted using six different methods (phylogenetic motifs, two methods that identify subfamily-specific positions, and three different conservation scores). A canonical set of 34 functional sites identified by Yamashita et al. within the recently solved LeuTAa structure is used to assess the quality of the predictions, most of which are predicted by the bioinformatic methods. Remarkably, the importance of these sites is largely confirmed by experimental mutagenesis. Furthermore, the collective set of functional site predictions qualitatively clusters along the proposed transport pathway, further demonstrating their utility. Interestingly, the various prediction schemes provide results that are predominantly orthogonal to each other. However, when the methods do provide overlapping results, specificity is shown to increase dramatically (e.g., sites predicted by any three methods have both accuracy and coverage greater than 50%). The results presented herein clearly establish the viability of sequence-based bioinformatic strategies to provide functional insight within the NSS family. As such, we expect similar bioinformatic investigations will streamline functional investigations within membrane integral families in the absence of structure.