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computional chemistry

Risk assesment


One of the important issues in drug discovery is the occurrence of undesired pharmacological effects and the weak metabolic stability of the drug molecule. In silico or computational tools can be used effectively in prediction of various physicochemical properties for a newly designed compound.

Selvita Computational Chemistry Team possess an extensive expertise in the field of in silico ADME profiling of compounds and can assist customers with the following type of projects:

  • In silico lead optimization and molecular properties prediction
  • Physicochemical parameters: solubility (pH profile, intrinsic), pKa, logP
  • Permeability: PAMPA, Cellular models (MDCK)
  • Drug/Drug Interaction potential: CYP450 inhibition, time dependant CYP inhibition
  • Prediction of IC50 value for blockage of HERG K+ channels
  • Predictive QSAR models
  • Machine learning methods

risk assesment 2