• Corpus ID: 218486914

Customised fragment libraries for ab initio protein structure prediction using a structural alphabet

@article{Dhingra2020CustomisedFL,
  title={Customised fragment libraries for ab initio protein structure prediction using a structural alphabet},
  author={Surbhi Dhingra and Ramanathan Sowdhamini and Yves‐Henri Sanejouand and Fr{\'e}d{\'e}ric Cadet and Bernard O. Offmann},
  journal={arXiv: Quantitative Methods},
  year={2020}
}
Motivation: Computational protein structure prediction has taken over the structural community in past few decades, mostly focusing on the development of Template-Free modelling (TFM) or ab initio modelling protocols. Fragment-based assembly (FBA), falls under this category and is by far the most popular approach to solve the spatial arrangements of proteins. FBA approaches usually rely on sequence based profile comparison to generate fragments from a representative structural database. Here we… 
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