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IRBM’s Computational Chemistry Team is committed to accelerating the drug discovery process by designing compounds able to address the most critical challenges during all the stages of the discovery journey.

Our team encompasses experts with different backgrounds in molecular modeling, cheminformatics and data science. This expertise allows us to creatively apply a broad range of structure-based and ligand-based techniques according to project needs.

IRBM’s computational scientists work closely with medicinal chemists, DMPK and NMR scientists in a fully integrated environment aiming to rationalize results and speed up the design of effective compounds. Indeed, the team can support the projects during target analysis, hit identification, hit-to-lead and lead optimization stages.

To ensure the best support, our Computational Chemistry Team will apply a full range of state-of-the-art ligand and structure-based in silico approaches and develop ad hoc solutions tailored to the project with the objective of finding the best candidate as quickly as possible.

CHEMINFORMATICS

Chemical data manipulation plays a central role in drug discovery. Our team is able to exploit this information using efficient algorithms and approaches in order to identify the best candidate.

  • Focused library design for in silico screening
  • Library analysis
  • ADMET prediction
  • Machine learning and deep learning-based property prediction (QSPR)
  • Similarity screening

STRUCTURE-BASED DRUG DISCOVERY

Once a three-dimensional structure of protein has been determined, we can apply several structure-based drug discovery tools for the design of new potent compounds. Also, we have experience in generating homology models when structural data are not available.

  • Molecular docking
  • Molecular dynamics simulations
  • Binding free energy calculations
  • Water assessment
  • Pocket detection

LIGAND-BASED APPROACHESS

When structural data is lacking or to complement the structure-based tools, we apply a series of ligand-based tools across the discovery process.

  • Scaffold hopping and fragment replacement
  • Pharmacophore modeling
  • Shape and electrostatic similarity
  • Training and development of QSAR models
  • QM-based geometry optimization and conformational analysis
FIND OUT MORE ABOUT OUR CROSS FUNCTIONAL DRUG DISCOVERY SERVICES

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