Predicting Off-Target Liabilities for a PROTAC Molecule

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Case Study 12

Predicting Off-Target Liabilities for a PROTAC Molecule

MegaPredict BindingDB, a GraphSage model trained on 475 human kinases, and models for several immunology targets were used to assess a client-provided PROTAC structure.

  • PROTAC
  • Off-target assessment
  • BindingDB
  • GraphSage
  • Kinases

Challenge

The client provided the structure of a PROTAC molecule for off-target assessment.

What We Did

  1. 1
    Queried MegaPredict BindingDB

    CPI queried the similarity of the client molecule to millions of molecules in MegaPredict BindingDB and assessed the top-scoring targets.

  2. 2
    Assessed kinase hits

    Because several top-scoring hits were kinases, CPI applied a GraphSage kinase model trained on 475 human kinases to score the client molecule.

  3. 3
    Developed models for immunology targets

    Built additional models for several immunology targets and used them to score the client's molecule.

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Improving hERG and Solubility for PROTACs

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Developing an Algorithm to Predict Ocular Bioavailability