title: A new graph-based molecular descriptor using the canonical representation of the molecule.
abstract: Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD) is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE) using the Tanimoto coefficient (TAN) and the basic local alignment search tool (BLAST) when searches were carried.
authors.affiliation: Faculty of Computing, University Technology of Malaysia, 81310 Skudai, Johor, Malaysia.
authors.forename: Hamza
authors.initials: H
authors.lastname: Hentabli
authors.affiliation: Faculty of Computing, University Technology of Malaysia, 81310 Skudai, Johor, Malaysia ; Information Technology Department, Sanhan Community College, Sana'a, Yemen.
authors.forename: Faisal
authors.identifier: 0000-0002-2822-1708
authors.initials: F
authors.lastname: Saeed
authors.affiliation: Computer Science Department, Hodeidah University, Hodeidah, Yemen.
authors.forename: Ammar
authors.initials: A
authors.lastname: Abdo
authors.affiliation: Faculty of Computing, University Technology of Malaysia, 81310 Skudai, Johor, Malaysia.
authors.forename: Naomie
authors.initials: N
authors.lastname: Salim
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D062126:Databases, Chemical; D015195:Drug Design; D008958:Models, Molecular; D015394:Molecular Structure; D012984:Software