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Fragment‐based similarity searching with infinite color space
Author(s) -
Gunera Jakub,
Kolb Peter
Publication year - 2015
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.23974
Subject(s) - fragment (logic) , computer science , graph , similarity (geometry) , chemical similarity , representation (politics) , virtual screening , algorithm , theoretical computer science , data mining , structural similarity , artificial intelligence , chemistry , drug discovery , image (mathematics) , biochemistry , politics , political science , law
Fragment‐based searching and abstract representation of molecular features through reduced graphs have separately been used for virtual screening. Here, we combine these two approaches and apply the algorithm RedFrag to virtual screens retrospectively and prospectively. It uses a new type of reduced graph that does not suffer from information loss during its construction and bypasses the necessity of feature definitions. Built upon chemical epitopes resulting from molecule fragmentation, the reduced graph embodies physico‐chemical and 2D‐structural properties of a molecule. Reduced graphs are compared with a continuous‐similarity‐distance‐driven maximal common subgraph algorithm, which calculates similarity at the fragmental and topological levels. The performance of the algorithm is evaluated by retrieval experiments utilizing precompiled validation sets. By predicting and experimentally testing ligands for endothiapepsin, a challenging model protease, the method is assessed in a prospective setting. Here, we identified five novel ligands with affinities as low as 2.08 μM. © 2015 Wiley Periodicals, Inc.