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Principles and Methods in Computational Membrane Protein Design
Affiliation:1. Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, USA;2. UC Berkeley – UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, California, USA;3. Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, California, USA;1. Institute for Protein Innovation, Boston, MA 02115, USA;2. Division of Hematology/Oncology, Boston Children''s Hospital, Boston, MA, USA;3. Department of Pediatrics, Harvard Medical School, Boston, MA, USA
Abstract:After decades of progress in computational protein design, the design of proteins folding and functioning in lipid membranes appears today as the next frontier. Some notable successes in the de novo design of simplified model membrane protein systems have helped articulate fundamental principles of protein folding, architecture and interaction in the hydrophobic lipid environment. These principles are reviewed here, together with the computational methods and approaches that were used to identify them. We provide an overview of the methodological innovations in the generation of new protein structures and functions and in the development of membrane-specific energy functions. We highlight the opportunities offered by new machine learning approaches applied to protein design, and by new experimental characterization techniques applied to membrane proteins. Although membrane protein design is in its infancy, it appears more reachable than previously thought.
Keywords:computational protein design  membrane proteins folding  protein structure  protein function  CHAMP"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0035"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Computed Helical Anti-Membrane Protein  DL"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0045"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Deep learning  GAN"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0055"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Generative Adversarial Networks  GPCR"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0065"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  G Protein Coupled Receptor  MCMC"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0075"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Markov Chain Monte Carlo  MP"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0085"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Membrane proteins  MSA"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0095"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Multiple Sequence Alignment  NLP"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k009598"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  natural language processing  NMR"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0105"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Nuclear Magnetic Resonance  PDB"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0115"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Protein Data Bank  REAMP"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0125"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Recombinantly Expressed Artificial Membrane Protein  RNN"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0135"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Recurrent Neural Networks  TM"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0145"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  transmembrane  TMB"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0155"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  transmembrane beta-barrel  TMD"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0165"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Transmembrane Domain  TR-Rosetta"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0175"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  transform-restrained Rosetta  VAE"  },{"  #name"  :"  keyword"  ,"  $"  :{"  id"  :"  k0185"  },"  $$"  :[{"  #name"  :"  text"  ,"  _"  :"  Variational AutoEncoders
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