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Advanced Modeling Reconciles Counterintuitive Decisions in Lead Optimization.

Ariel Fernández1, L Ridgway Scott2

  • 1Argentine Institute of Mathematics, National Research Council, CONICET, Buenos Aires 1083, Argentina; AF Innovation, GmbH, a pharmaceutical consultancy, Avenida del Libertador 1092, Buenos Aires 1112, Argentina.

Trends in Biotechnology
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Summary

Lead optimization (LO) decisions in drug design are improved by accounting for water removal and target electrostatics. New biophysical methods reconcile counterintuitive drug-target interactions for better drug discovery.

Keywords:
drug designdrug–target mismatcheslead optimizationprotein–water interfacethree-body effects

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Area of Science:

  • Biophysics
  • Computational Chemistry
  • Drug Discovery

Background:

  • Lead optimization (LO) is critical for developing effective and safe targeted therapies.
  • Understanding water displacement at the drug-target interface is key to LO.
  • Counterintuitive binding site inferences often complicate LO decisions.

Purpose of the Study:

  • To reconcile apparent mismatches between drug properties and target binding sites during LO.
  • To introduce novel biophysical methods for improving computational accuracy in drug design.
  • To enhance the understanding of drug-induced environmental changes on target electrostatics.

Main Methods:

  • Incorporation of three-body energy terms to model target structure stabilization.
  • Accounting for the net stabilization upon removal of interfacial water during drug binding.
  • Validation against experimental drug-target affinity data.

Main Results:

  • Successfully reconciled counterintuitive drug-target interactions.
  • Demonstrated superior computational accuracy by incorporating three-body energy terms.
  • Validated the enhancement of target electrostatics due to drug-induced environmental changes.

Conclusions:

  • The developed biophysical approach improves the accuracy of computational predictions in drug design.
  • Understanding interfacial water dynamics and target electrostatics is crucial for effective lead optimization.
  • This method offers a pathway to more intuitive and successful drug-target interaction design.