Structure-assisted drug design

(Vicki Nienaber, Zenobia Therapeutics, Inc.)

Definitions and Concepts:

  • Fragment

Structural biology and Fragment-based lead discovery can make the drug discovery process more efficient.

  • Structure-based design allows the visualization of binding and a pathway to optimization.
  • On the other hand, potency-based design with little focus on chemical properties often leads to big non-drug-like molecules. Multiple properties need to be optimized early on, not just potency.

Structural information can be used to improve compound in multiple ways.

  • Improve potency by adding interaction functionality (e.g. via hydrogen bonding, van der Waals forces).
  • Change the chemical properties (e.g. add solubilizing groups, peptidic to non-peptidic).
    • Cut and paste strategy between different compounds to improve chemical properties.
  • Engineer in/out off-target binding (e.g. remove albumin binding).

Fragment-based lead discovery (FBLD)

  • Small simple molecules are more likely to bind to a target.
    • Fifteen atoms (non-hydrogen) are sufficient for ligand binding efficiency.
  • Fragment libraries can cover more chemical space than HTS libraries.
  • Low MW (<400-500) increases the likelihood of clinical success (see FIG. 3)
  • FBLD is ideally suited to CNS drug discovery; low MW candidates have better BBB penetration. In contrast, HTS-derived candidates often have MWs that are too high for CNS penetrance, especially as another 100 is typically added to the MW during lead optimization.
  • There are currently 10 compounds in the clinic that were derived from fragment screening.

Fragment libraries

  • There are 26 million possible fragments. Commercially available fragments represent natural products and metabolites. Most theoretically possible fragment cores are not prepared/available.
  • When picking a fragment library, there are multiple factors to consider to ensure diversity.
    • saturated vs. unsaturated
    • number of chiral centers
    • number of analogues available for purchase
    • number of rotatable bonds
    • removal of “problem compounds”
  • Example: The Zenobia fragment Library 1 (of 352 compounds) has chemical properties consistent with currently marketed drugs. The compounds are predominantly rigid, low complexity, single-core molecules with simple functionality for follow-up chemistry.

FBLD screening approach - starting small and staying small; see FIG. 4

  • Fragments bind more weakly, so this should be taken into account in assay development
  • The general goal is to produce multiple low MW starting points for lead optimization to ultimately increase success in the clinic.
  • Prescreen with NMR, SPR, biochemistry, calorimetry.
  • Secondary screen with X-ray crystallography.
  • Monitor chemical properties and ligand efficiency throughout the iterative optimization process.
  • Parallel processing of multiple fragment hits provides the best likelihood of achieving good drug candidates.
  • Improvements in computational processors and access to synchrotron sources have greatly improved throughput permitting “real-time” feedback.

Examples:

  • X-ray crystallographic screening for inhibitors of dihydroneopterin aldolase (Sanders 2004 J Med Chem)
  • X-ray crystallographic screening and optimization to improve ADME/PK (Nienaber 2000 Nature Biotechnology)
  • Structure-based screen for inhibitors of oncogenic B-Raf kinase (Tsai 2008 PNAS)

Challenges: cost and resources needed may be higher than with other approaches

Basics of high throughput screening (HTS): Bridging chemistry and biology >