Geometricus represents protein structures as shape-mers derived from moment invariants
Geometricus represents protein structures as shape-mers derived from moment invariants
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DOI：
10.1093/bioinformatics/btaa839
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发表时间：
2020-12-01
期刊：
影响因子：
5.8
通讯作者：
van Dijk, Aalt D. J.
中科院分区：
文献类型：
--
作者：
Durairaj, Janani;Akdel, Mehmet;van Dijk, Aalt D. J.
动机：随着实验解决的蛋白质结构数量的增加，使用结构信息进行涉及蛋白质的预测任务变得越来越有吸引力。由于蛋白质大小、折叠和拓扑结构的巨大变化，一种有吸引力的方法是将蛋白质结构嵌入固定长度的向量中，这可以用于旨在预测和理解功能和物理性质的机器学习算法。现有的许多嵌入方法都是基于排列的，这种方法既耗时又无效。另一方面，基于库或基于模型的方法依赖于小的片段库或需要使用经过训练的模型，这两种方法可能都不能很好地泛化。结果：我们提出了Geometricus，一种新颖且普遍适用的方法来在固定维空间中嵌入蛋白质。该方法快速、准确且可解释。Geometricus使用一组3D矩不变量将蛋白质结构片段离散成形状聚合物，然后将其计数以计数向量的形式描述完整的结构。我们证明了这种方法在各种任务中的适用性，包括快速结构相似性搜索，无监督聚类和跨不同超家族以及同一家族内蛋白质的结构分类。
Motivation: As the number of experimentally solved protein structures rises, it becomes increasingly appealing to use structural information for predictive tasks involving proteins. Due to the large variation in protein sizes, folds and topologies, an attractive approach is to embed protein structures into fixed-length vectors, which can be used in machine learning algorithms aimed at predicting and understanding functional and physical properties. Many existing embedding approaches are alignment based, which is both time-consuming and ineffective for distantly related proteins. On the other hand, library- or model-based approaches depend on a small library of fragments or require the use of a trained model, both of which may not generalize well.Results: We present Geometricus, a novel and universally applicable approach to embedding proteins in a fixed-dimensional space. The approach is fast, accurate, and interpretable. Geometricus uses a set of 3D moment invariants to discretize fragments of protein structures into shape-mers, which are then counted to describe the full structure as a vector of counts. We demonstrate the applicability of this approach in various tasks, ranging from fast structure similarity search, unsupervised clustering and structure classification across proteins from different superfamilies as well as within the same family.