SHREC 2021 Track: Retrieval and classification of protein surfaces equipped with physical and chemical properties

Andrea Raffo*, Ulderico Fugacci, Silvia Biasotti, Walter Rocchia, Yonghuai Liu, Ekpo Otu, Reyer Zwiggelaar, David Hunter, Evangelia I. Zacharaki, Eleftheria Psatha, Dimitrios Laskos, Gerasimos Arvanitis, Konstantinos Moustakas, Tunde Aderinwale, Charles Christoffer, Woong Hee Shin, Daisuke Kihara, Andrea Giachetti, Huu Nghia Nguyen, Tuan Duy NguyenVinh Thuyen Nguyen-Truong, Danh Le-Thanh, Hai Dang Nguyen, Minh Triet Tran

*Corresponding author for this work

Research output: Contribution to journalArticle (journal)peer-review

10 Citations (Scopus)
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This paper presents the methods that have participated in the SHREC 2021 contest on retrieval and classification of protein surfaces on the basis of their geometry and physicochemical properties. The goal of the contest is to assess the capability of different computational approaches to identify different conformations of the same protein, or the presence of common sub-parts, starting from a set of molecular surfaces. We addressed two problems: defining the similarity solely based on the surface geometry or with the inclusion of physicochemical information, such as electrostatic potential, amino acid hydrophobicity, and the presence of hydrogen bond donors and acceptors. Retrieval and classification performances, with respect to the single protein or the existence of common sub-sequences, are analysed according to a number of information retrieval indicators.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalComputers and Graphics (Pergamon)
Early online date25 Jun 2021
Publication statusPublished - 1 Oct 2021


  • 3D Shape analysis
  • 3D Shape descriptor
  • Protein classification
  • Protein retrieval
  • Protein surfaces


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