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Metadynamics for Perspective Drug Design: Computationally Driven Synthesis of New Protein-Protein Interaction Inhibitors Targeting the EphA2 Receptor.

Matteo IncertiSimonetta RussoDonatella CallegariDaniele PalaCarmine GiorgioIlaria ZanottiElisabetta BarocelliPaola ViciniFederica VacondioSilvia RivaraRiccardo CastelliMassimiliano TognoliniAlessio Lodola
Published in: Journal of medicinal chemistry (2017)
Metadynamics (META-D) is emerging as a powerful method for the computation of the multidimensional free-energy surface (FES) describing the protein-ligand binding process. Herein, the FES of unbinding of the antagonist N-(3α-hydroxy-5β-cholan-24-oyl)-l-β-homotryptophan (UniPR129) from its EphA2 receptor was reconstructed by META-D simulations. The characterization of the free-energy minima identified on this FES proposes a binding mode fully consistent with previously reported and new structure-activity relationship data. To validate this binding mode, new N-(3α-hydroxy-5β-cholan-24-oyl)-l-β-homotryptophan derivatives were designed, synthesized, and tested for their ability to displace ephrin-A1 from the EphA2 receptor. Among them, two antagonists, namely compounds 21 and 22, displayed high affinity versus the EphA2 receptor and resulted endowed with better physicochemical and pharmacokinetic properties than the parent compound. These findings highlight the importance of free-energy calculations in drug design, confirming that META-D simulations can be used to successfully design novel bioactive compounds.
Keyphrases
  • protein protein
  • binding protein
  • molecular dynamics
  • structure activity relationship
  • small molecule
  • monte carlo
  • machine learning
  • electronic health record
  • cancer therapy
  • big data
  • dna binding
  • amino acid
  • drug delivery