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Computer-assisted engineering of hyperstable fibroblast growth factor 2.

Pavel DvorakDavid BednarPavel VanacekLukas BalekLivia EiselleovaVeronika StepankovaEva SebestovaMichaela Kunova BosakovaZaneta KonecnaStanislav MazurenkoAntonin KunkaTereza VanovaKarolina ZoufalovaRadka ChaloupkovaJan BrezovskyPavel KrejciZbynek ProkopPetr DvorakJiří Damborský
Published in: Biotechnology and bioengineering (2018)
Fibroblast growth factors (FGFs) serve numerous regulatory functions in complex organisms, and their corresponding therapeutic potential is of growing interest to academics and industrial researchers alike. However, applications of these proteins are limited due to their low stability. Here we tackle this problem using a generalizable computer-assisted protein engineering strategy to create a unique modified FGF2 with nine mutations displaying unprecedented stability and uncompromised biological function. The data from the characterization of stabilized FGF2 showed a remarkable prediction potential of in silico methods and provided insight into the unfolding mechanism of the protein. The molecule holds a considerable promise for stem cell research and medical or pharmaceutical applications.
Keyphrases
  • stem cells
  • big data
  • protein protein
  • healthcare
  • amino acid
  • binding protein
  • heavy metals
  • wastewater treatment
  • molecular docking
  • multidrug resistant
  • human health
  • deep learning