Graul R C, Sadée W
Department of Biopharmaceutical Sciences, University of California San Francisco 94143-0446, USA.
Pharm Res. 1997 Nov;14(11):1533-41. doi: 10.1023/a:1012166015402.
Searching the existing databases for homologous sequences is essential to understanding a protein's structure and function. For a query sequence, its nearest neighbors can be identified by BLAST (basic local alignment search tool). However, a single query sequence is sufficient to define the entire neighborhood of related sequences, and multiple BLAST queries are needed. We describe here a program which permits automated and iterative BLAST analysis of an entire neighborhood of sequences and apply this to search for homologs of the bacteriorhodopsins outside the archaea phylum.
We have developed a Java program, 'Iterative Neighborhood Cluster Analysis' (INCA), which performs iterative BLAST searches, beginning with a single starter sequence, and proceeding with any other sequence achieving a predefined minimum alignment score. This results in a cluster of sequences where each sequence is related to at least one other sequence by the cutoff score, additional lists of more distantly related sequences for each member of cluster.
Bacteriorhodopsins had not been previously aligned with any other protein family with scores indicative of probable homology. Using INCA, we identified a probable homolog in yeast, YRO2_YEAST, also containing seven putative transmembrane domains. A finding of probable homology was supported by additional alignment strategies.
INCA is a useful tool to assess complete protein neighborhoods. With an increasing database, INCA can serve to detect the emergence of evolutionary links between even the most distantly related protein families. Identifying a homolog of the bacteriorhodopsins in yeast illustrates this approach but at the same time highlights the vast evolutionary distances between polytopic membrane proteins, such as the bacteriorhodopsins.
在现有数据库中搜索同源序列对于理解蛋白质的结构和功能至关重要。对于一个查询序列，可以通过BLAST（基本局部比对搜索工具）来识别其最接近的邻居。然而，单个查询序列不足以定义整个相关序列邻域，需要进行多次BLAST查询。我们在此描述一个程序，它允许对整个序列邻域进行自动迭代的BLAST分析，并将其应用于搜索古菌门以外的细菌视紫红质同源物。
我们开发了一个Java程序“迭代邻域聚类分析”（INCA），它从单个起始序列开始进行迭代BLAST搜索，并对任何达到预定义最小比对分数的其他序列继续进行搜索。这会产生一个序列簇，其中每个序列通过截止分数与至少一个其他序列相关，为簇中的每个成员生成更远相关序列的附加列表。
以前细菌视紫红质尚未与任何其他蛋白质家族进行比对，其分数表明可能存在同源性。使用INCA，我们在酵母中鉴定出一个可能的同源物YRO2_YEAST，它也包含七个推定的跨膜结构域。其他比对策略支持了可能同源性的发现。
INCA是评估完整蛋白质邻域的有用工具。随着数据库的不断增加，INCA可用于检测即使是最远距离相关的蛋白质家族之间进化联系的出现。在酵母中鉴定细菌视紫红质的同源物说明了这种方法，但同时也突出了多跨膜蛋白（如细菌视紫红质）之间巨大的进化距离。
