title: Library design practices for success in lead generation with small molecule libraries.
abstract: The generation of novel structures amenable to rapid and efficient lead optimization comprises an emerging strategy for success in modern drug discovery. Small molecule libraries of sufficient size and diversity to increase the chances of discovery of novel structures make the high throughput synthesis approach the method of choice for lead generation. Despite an industry trend for smaller, more focused libraries, the need to generate novel lead structures makes larger libraries a necessary strategy. For libraries of a several thousand or more members, solid phase synthesis approaches are the most suitable. While the technology and chemistry necessary for small molecule library synthesis continue to advance, success in lead generation requires rigorous consideration in the library design process to ensure the synthesis of molecules possessing the proper characteristics for subsequent lead optimization. Without proper selection of library templates and building blocks, solid phase synthesis methods often generate molecules which are too heavy, too lipophilic and too complex to be useful for lead optimization. The appropriate filtering of virtual library designs with multiple computational tools allows the generation of information-rich libraries within a drug-like molecular property space. An understanding of the hit-to-lead process provides a practical guide to molecular design characteristics. Examples of leads generated from library approaches also provide a benchmarking of successes as well as aspects for continued development of library design practices.
authors.affiliation: Roche Research Center, Hoffmann-La Roche Inc. Nutley, New Jersey, USA.
authors.forename: R A
authors.initials: RA
authors.lastname: Goodnow
authors.forename: W
authors.initials: W
authors.lastname: Guba
authors.forename: W
authors.initials: W
authors.lastname: Haap
mesh_terms: D020650:Combinatorial Chemistry Techniques; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D008958:Models, Molecular