Langenfeld, FlorentAderinwale, TundeChristoffer, CharlesShin, Woong-HeeTerashi, GenkiWang, XiaoKihara, DaisukeBenhabiles, HalimHammoudi, KarimCabani, AdnaneWindal, FeryalMelkemi, MahmoudOtu, EkpoZwiggelaar, ReyerHunter, DavidLiu, YonghuaiSirugue, LéaNguyen, Huu-Nghia H.Nguyen, Tuan-Duy H.Nguyen–Truong, Vinh-ThuyenLe, DanhNguyen, Hai-DangTran, Minh-TrietMontès, MatthieuBiasotti, Silvia and Dyke, Roberto M. and Lai, Yukun and Rosin, Paul L. and Veltkamp, Remco C.2021-09-012021-09-012021978-3-03868-137-31997-0471https://doi.org/10.2312/3dor.20211308https://diglib.eg.org:443/handle/10.2312/3dor20211308Proteins 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.Applied computingComputational biologyGeneral and referenceEvaluation10.2312/3dor.2021130819-26