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首页> 外文期刊>IEEE Transactions on Knowledge and Data Engineering >CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites
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CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites

机译：CavSimBase：一个用于蛋白质结合位点大规模比较的数据库

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摘要

CavBase is a database containing information about the three-dimensional geometry and the physicochemical properties of putative protein binding sites. Analyzing CavBase data typically involves computing the similarity of pairs of binding sites. In contrast to sequence alignment, however, a structural comparison of protein binding sites is a computationally challenging problem, making large scale studies difficult or even infeasible. One possibility to overcome this obstacle is to precompute pairwise similarities in an all-against-all comparison, and to make these similarities subsequently accessible to data analysis methods. Pairwise similarities, once being computed, can also be used to equip CavBase with a neighborhood structure. Taking advantage of this structure, methods for problems such as similarity retrieval can be implemented efficiently. In this paper, we tackle the problem of performing an all-against-all comparison using CavBase, consisting of more than 200,000 protein cavities, by means of parallel computation and cloud computing techniques. We present the conceptual design and technical realization of a large-scale study to create a similarity database called CavSimBase. We illustrate how CavSimBase is constructed, is accessed, and is used to answer biological questions by data analysis and similarity retrieval.
机译：CavBase是一个数据库，其中包含有关三维几何结构和推定蛋白质结合位点的理化特性的信息。分析CavBase数据通常涉及计算结合位点对的相似性。然而，与序列比对相反，蛋白质结合位点的结构比较是计算上的难题，这使得大规模研究困难甚至不可行。克服这一障碍的一种可能性是，在所有对所有比较中预先计算成对相似性，并使这些相似性随后可用于数据分析方法。成对相似度一旦被计算，也可用于为CavBase配备邻域结构。利用这种结构，可以有效地实现用于诸如相似度检索的问题的方法。在本文中，我们通过并行计算和云计算技术解决了使用由200,000多个蛋白质腔组成的CavBase进行全面对比的问题。我们介绍了一项大规模研究的概念设计和技术实现，以创建一个称为CavSimBase的相似性数据库。我们将说明CavSimBase的构造，访问方式以及如何通过数据分析和相似性检索来回答生物学问题。

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