Structure-Based Design




Structure-Based Design (SBD) and the related Fragment-Based Design (FBD) are well established strategies in the rational development of small molecule drugs. Knowledge of how a small molecule binds into a protein affords considerable advantages, both in terms of prioritizing compounds for early stage screening, through to optimizing potency and selectivity. Discovery Studio delivers a comprehensive, scalable portfolio of scientific tools, tailored to support and assist SBD and FBD strategies from hit discovery through to late-stage lead optimization.

  • Analyze and prepare 3D structures (e.g., PDB, X-ray structure, homology model) for SBD
  • Automatically build neighboring molecules based on crystal packing and analyze their interactions
  • Predict residue ionization states at chosen pH
  • Identify and study putative ligand binding sites
  • Prepare ligands with extensive set of characteristics and calculate 3D coordinates
  • Generate ligand conformations
  • Filter ligands based on drug-likeness, molecular properties, or to remove undesirable groups or features
  • Hit Identification and optimization
  • Perform virtual screening on ligands and fragments using either the CATALYST pharmacophore engine, or the LibDock or CDOCKER docking approaches
  • Perform docking with GOLD §
  • Perform in situ lead optimization using classical medicinal chemistry reaction transformations and commercially-available reagents
  • Scaffold-hop or perform R-group substitutions in situ using molecular fragments derived from commercially-available compounds

§ Requires license from Cambridge Crystallographic Data Centre

  • Calculate binding energies with MM-PBSA or MM-GBSA CHARMm-based methods
  • Accurately predict relative ligand binding energy for a congeneric ligand series using the free energy perturbation (FEP) method
  • Calculate the relative free energy of binding for a combinatorial library of ligands modeled by Multi-Site Lambda Dynamics (MSLD)
  • Identify critical interacting residues using a comprehensive set of favorable, unfavorable and unsatisfied non-bond monitors
  • Profile and prioritize screening hits, optimizing potency and target specificity
  • Design and optimize combinatorial libraries as new starting points for further screening.
  • Combine your scores with classical QSAR, fingerprints, and Quantum Mechanics based descriptors and create advanced predictive models
  • Minimize toxicity using TOPKAT and optimize the pharmacokinetic profile.