title: Affinity-based ranking of ligands for DPP-4 from mixtures.
abstract: Affinity-based selection strategies have recently emerged as a complement to traditional high throughput screening for the rapid discovery of lead compounds for the large number of protein targets emerging from--omics technologies. Herein, we describe a method for the ranking of mixtures of ligands by affinity selection and apply it to rank order a set of inhibitors for the enzyme dipeptidyl peptidase IV.
authors.affiliation: Department of Target Validation, Merck & Co., Inc., PO Box 2000, Rahway, NJ 07065, USA. gregory_adam@merck.com
authors.forename: Gregory C
authors.initials: GC
authors.lastname: Adam
authors.forename: Juncai
authors.initials: J
authors.lastname: Meng
authors.forename: John
authors.initials: J
authors.lastname: Athanasopoulos
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Zhang
authors.forename: Kevin T
authors.initials: KT
authors.lastname: Chapman
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000379:methods*; D003920:Diabetes Mellitus / Q000188:drug therapy; D018819:Dipeptidyl Peptidase 4 / Q000737:chemistry*; D004305:Dose-Response Relationship, Drug; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000138:chemical synthesis* / Q000737:chemistry; D006801:Humans; D020128:Inhibitory Concentration 50; D008024:Ligands; D008956:Models, Chemical
chemical_list: D004791:Enzyme Inhibitors; D008024:Ligands; D018819:Dipeptidyl Peptidase 4