SHREC 2021: Surface-based Protein Domains Retrieval

Florent Langenfeld, Tunde Aderinwale, Charles W Christoffer, Woong-Hee Shin, Genki Terashi, Xiao Wang, D. Kihara, H. Benhabiles, K. Hammoudi, A. Cabani, Féryal Windal, Mahmoud Melkemi, Ekpo Otu, R. Zwiggelaar, David Hunter, Yonghuai Liu, Léa Sirugue, Huu-Nghia H. Nguyen, Tuan-Duy H. Nguyen, Vinh-Thuyen Nguyen-Truong, D. Le, Hai-Dang Nguyen, M. Tran, M. Montès
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Abstract

Proteins are essential to nearly all cellular mechanism, and often interact through their surface with other cell molecules, such as proteins and ligands. The evolution generates plenty of different proteins, with unique abilities, but also proteins with related functions hence surface, which is therefore of primary importance for their activity. In the present work, we assess the ability of five methods to retrieve similar protein surfaces, using either their shape only (3D meshes), or their shape and the electrostatic potential at their surface, an important surface property. Five different groups participated in this challenge using the shape only, and one group extended its pre-existing algorithm to handle the electrostatic potential. The results reveal both the ability of the methods to detect related proteins and their difficulties to distinguish between topologically related proteins. CCS Concepts • Applied computing → Computational biology; • General and reference → Evaluation;
SHREC 2021:基于表面的蛋白质结构域检索
蛋白质对几乎所有的细胞机制都是必不可少的,并且经常通过它们的表面与其他细胞分子(如蛋白质和配体)相互作用。这种进化产生了许多不同的蛋白质,具有独特的能力,但也产生了具有相关功能的蛋白质,因此表面对它们的活性至关重要。在目前的工作中,我们评估了五种方法检索相似蛋白质表面的能力,要么只使用它们的形状(3D网格),要么使用它们的形状和表面的静电势(一个重要的表面特性)。五个不同的小组参加了这个挑战,只使用形状,一个小组扩展了其已有的算法来处理静电势。结果揭示了方法检测相关蛋白的能力和区分拓扑相关蛋白的困难。•应用计算→计算生物学;•一般与参考→评价;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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