Method for effective virtual screening and scaffold-hopping in chemical compounds.
Methods that can screen large databases to retrieve a structurally diverse set of compounds with desirable bioactivity properties are critical in the drug discovery and development process. This paper presents a set of such methods, which are designed to find compounds that are structurally different to a certain query compound while retaining its bioactivity properties (scaffold hops). These methods utilize various indirect ways of measuring the similarity between the query and a compound that take into account additional information beyond their structure-based similarities. Two sets of techniques are presented that capture these indirect similarities using approaches based on automatic relevance feedback and on analyzing the similarity network formed by the query and the database compounds. Experimental evaluation shows that many of these methods substantially outperform previously developed approaches both in terms of their ability to identify structurally diverse active compounds as well as active compounds in general.
Wale
Nikil
N
Department of Computer Science, University of Minnesota, Twin Cities, USA. nwale@cs.umn.edu
Karypis
George
G
Watson
Ian A
IA
D000465:Algorithms; D001185:Artificial Intelligence; D002626:Chemistry, Pharmaceutical / Q000145:classification* / Q000379:methods*; D015195:Drug Design; D010363:Pattern Recognition, Automated; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000145:classification*; D014584:User-Computer Interface
D004364:Pharmaceutical Preparations