SHREC 2021: Retrieval and classification of protein surfaces equipped with physical and chemical properties. (October 2021) - Raffo, Andrea; Fugacci, Ulderico; Biasotti, Silvia; Rocchia, Walter; Liu, Yonghuai; Otu, Ekpo; Zwiggelaar, Reyer; Hunter, David; Zacharaki, Evangelia I.; Psatha, Eleftheria; Laskos, Dimitrios; Arvanitis, Gerasimos; et al.
Highlights: A new benchmark of protein surfaces equipped with three physicochemical properties. Protein surfaces are retrieved and classified with respect to different ground truths. Analysis of the retrieval and classification performances of the methods that participated in SHREC 2021. A thorough Investigation of how different physicochemical properties impact the performance of retrieval methods. Graphical abstract: Abstract: 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.