TY - JOUR
T1 - SHREC 2021 Track
T2 - Retrieval and classification of protein surfaces equipped with physical and chemical properties
AU - Raffo, Andrea
AU - Fugacci, Ulderico
AU - Biasotti, Silvia
AU - Rocchia, Walter
AU - Liu, Yonghuai
AU - Otu, Ekpo
AU - Zwiggelaar, Reyer
AU - Hunter, David
AU - Zacharaki, Evangelia I.
AU - Psatha, Eleftheria
AU - Laskos, Dimitrios
AU - Arvanitis, Gerasimos
AU - Moustakas, Konstantinos
AU - Aderinwale, Tunde
AU - Christoffer, Charles
AU - Shin, Woong Hee
AU - Kihara, Daisuke
AU - Giachetti, Andrea
AU - Nguyen, Huu Nghia
AU - Nguyen, Tuan Duy
AU - Nguyen-Truong, Vinh Thuyen
AU - Le-Thanh, Danh
AU - Nguyen, Hai Dang
AU - Tran, Minh Triet
N1 - Funding Information:
This project is co-funded by the project “TEACUP: Metodi e TEcniche innovative per lo sviluppo di librerie per la modellazione, l’Analisi e il confronto CompUtazionale di Proteine”, POR FSE, Programma Operativo Regione Liguria 2014–2020, No RLOF18ASSRIC/68/1. The CNR-IMATI research is partially developed in the activities DIT.AD021.080.001 and DIT.AD009.091.001. This research was partially supported by TAILOR, a project funded by EU Horizon 2020 research and innovation programme under GA No 952215, and by Vietnam National University Ho Chi Minh City (VNU-HCM) under grant number DS2020-42-01.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/10/1
Y1 - 2021/10/1
N2 - 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.
AB - 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.
KW - 3D Shape analysis
KW - 3D Shape descriptor
KW - Protein classification
KW - Protein retrieval
KW - Protein surfaces
KW - SHREC
UR - http://www.scopus.com/inward/record.url?scp=85110100156&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85110100156&partnerID=8YFLogxK
U2 - 10.1016/j.cag.2021.06.010
DO - 10.1016/j.cag.2021.06.010
M3 - Article (journal)
AN - SCOPUS:85110100156
SN - 0097-8493
VL - 99
SP - 1
EP - 21
JO - Computers and Graphics (Pergamon)
JF - Computers and Graphics (Pergamon)
ER -