title: Computational medicinal chemistry in fragment-based drug discovery: what, how and when.
abstract: The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure-activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario - what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.
authors.affiliation: Experimental Therapeutics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
authors.forename: Obdulia
authors.initials: O
authors.lastname: Rabal
authors.forename: Manuel
authors.initials: M
authors.lastname: Urbano-Cuadrado
authors.forename: Julen
authors.initials: J
authors.lastname: Oyarzabal
mesh_terms: D000818:Animals; D002626:Chemistry, Pharmaceutical / Q000379:methods; D019295:Computational Biology / Q000379:methods; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D021281:Quantitative Structure-Activity Relationship