Structure-Based Design

SUPPORTS PHARMACEUTICAL R&D FROM HIT DISCOVERY THROUGH TO LATE-STAGE LEAD OPTIMIZATION

 

 

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.

    Prepare
    • 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
    Screen
    • 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

    Score
    • 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
    Extend
    • 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.

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