title: Maximizing computational tools for successful drug discovery.
abstract: Drug discovery is an iterative cycle of identifying promising hits followed by lead optimization via bioisosteric replacements. In the search for compounds affording good bioactivity, equal importance should also be placed on achieving those with favorable pharmacokinetic properties. Thus, the balance and realization of both key properties is an intricate problem that requires great caution. In this editorial, the authors explore the available computational tools in the context of the extant of big data that has borne out via advents of the Omics revolution. As such, the selection of appropriate computational tools for analyzing the vast number of chemical libraries, target proteins and interactomes is the first step toward maximizing the chance for success. However, in order to realize this, it is also necessary to have a solid foundation on the big concepts of drug discovery as well as knowing which tools are available in order to give drug discovery scientists the best opportunity.
authors.affiliation: Mahidol University, Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology , 10700 Bangkok , Thailand chanin.nan@mahidol.ac.th.
authors.forename: Chanin
authors.initials: C
authors.lastname: Nantasenamat
authors.forename: Virapong
authors.initials: V
authors.lastname: Prachayasittikul
mesh_terms: D017076:Computer-Aided Design; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D010599:Pharmacokinetics; D054852:Small Molecule Libraries / Q000737:chemistry
chemical_list: D054852:Small Molecule Libraries
keywords: bioinformatics; cheminformatics; chemogenomics; computational tools; data mining; drug discovery