dc.creator | Axenopoulos A., Rafailidis D., Papadopoulos G., Houstis E.N., Daras P. | en |
dc.date.accessioned | 2023-01-31T07:34:51Z | |
dc.date.available | 2023-01-31T07:34:51Z | |
dc.date.issued | 2016 | |
dc.identifier | 10.1109/TCBB.2015.2498553 | |
dc.identifier.issn | 15455963 | |
dc.identifier.uri | http://hdl.handle.net/11615/71016 | |
dc.description.abstract | In this paper, a framework for shape-based similarity search of 3D molecular structures is presented. The proposed framework exploits simultaneously the discriminative capabilities of a global, a local, and a hybrid local-global shape feature to produce a geometric descriptor that achieves higher retrieval accuracy than each feature does separately. Global and hybrid features are extracted using pairwise computations of diffusion distances between the points of the molecular surface, while the local feature is based on accumulating pairwise relations among oriented surface points into local histograms. The local features are integrated into a global descriptor vector using the bag-of-features approach. Due to the intrinsic property of its constituting shape features to be invariant to articulations of the 3D objects, the framework is appropriate for similarity search of flexible 3D molecules, while at the same time it is also accurate in retrieving rigid 3D molecules. The proposed framework is evaluated in flexible and rigid shape matching of 3D protein structures as well as in shape-based virtual screening of large ligand databases with quite promising results. © 2015 IEEE. | en |
dc.language.iso | en | en |
dc.source | IEEE/ACM Transactions on Computational Biology and Bioinformatics | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84990935011&doi=10.1109%2fTCBB.2015.2498553&partnerID=40&md5=6495fda52dff9097d62d969ee6849c6a | |
dc.subject | Bioinformatics | en |
dc.subject | Proteins | en |
dc.subject | Bioinformatics (genome or protein) database | en |
dc.subject | Diffusion distance | en |
dc.subject | Geometric descriptor | en |
dc.subject | Global shape feature | en |
dc.subject | Molecular shapes | en |
dc.subject | Molecular surfaces | en |
dc.subject | Shape based similarities | en |
dc.subject | Virtual Screening | en |
dc.subject | Molecules | en |
dc.subject | protein | en |
dc.subject | solvent | en |
dc.subject | algorithm | en |
dc.subject | chemical model | en |
dc.subject | chemistry | en |
dc.subject | computer simulation | en |
dc.subject | crystallography | en |
dc.subject | molecular model | en |
dc.subject | procedures | en |
dc.subject | protein conformation | en |
dc.subject | sequence alignment | en |
dc.subject | sequence analysis | en |
dc.subject | ultrastructure | en |
dc.subject | Algorithms | en |
dc.subject | Computer Simulation | en |
dc.subject | Crystallography | en |
dc.subject | Models, Chemical | en |
dc.subject | Models, Molecular | en |
dc.subject | Protein Conformation | en |
dc.subject | Proteins | en |
dc.subject | Sequence Alignment | en |
dc.subject | Sequence Analysis, Protein | en |
dc.subject | Solvents | en |
dc.subject | Institute of Electrical and Electronics Engineers Inc. | en |
dc.title | Similarity search of flexible 3d molecules combining local and global shape descriptors | en |
dc.type | journalArticle | en |