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A superposition free method for protein conformational ensemble analyses and local clustering based on a differential geometry representation of backbone.

Antonio Marinho da Silva NetoSamuel Reghim SilvaMichele VendruscoloCarlo CamilloniRinaldo Wander Montalvão
Published in: Proteins (2019)
Here a differential geometry (DG) representation of protein backbone is explored on the analyses of protein conformational ensembles. The protein backbone is described by curvature, κ, and torsion, τ, values per residue and we propose 1) a new dissimilarity and protein flexibility measurement and 2) a local conformational clustering method. The methods were applied to Ubiquitin and c-Myb-KIX protein conformational ensembles and results show that κ\τ metric space allows to properly judge protein flexibility by avoiding the superposition problem. The dmax measurement presents equally good or superior results when compared to RMSF, especially for the intrinsically unstructured protein. The clustering method is unique as it relates protein global to local dynamics by providing a global clustering solutions per residue. The methods proposed can be especially useful to the analyses of highly flexible proteins. The software written for the analyses presented here is available at https://github.com/AMarinhoSN/FleXgeo for academic usage only.
Keyphrases
  • protein protein
  • amino acid
  • single molecule
  • molecular dynamics simulations
  • small molecule
  • rna seq
  • convolutional neural network
  • solid state