title: Conformational sampling and structure prediction of multiple interacting loops in soluble and β-barrel membrane proteins using multi-loop distance-guided chain-growth Monte Carlo method.
abstract: BACKGROUND
  Loops in proteins are often involved in biochemical functions. Their irregularity and flexibility make experimental structure determination and computational modeling challenging. Most current loop modeling methods focus on modeling single loops. In protein structure prediction, multiple loops often need to be modeled simultaneously. As interactions among loops in spatial proximity can be rather complex, sampling the conformations of multiple interacting loops is a challenging task.
  
  
  RESULTS
  In this study, we report a new method called multi-loop Distance-guided Sequential chain-Growth Monte Carlo (M-DiSGro) for prediction of the conformations of multiple interacting loops in proteins. Our method achieves an average RMSD of 1.93 Å for lowest energy conformations of 36 pairs of interacting protein loops with the total length ranging from 12 to 24 residues. We further constructed a data set containing proteins with 2, 3 and 4 interacting loops. For the most challenging target proteins with four loops, the average RMSD of the lowest energy conformations is 2.35 Å. Our method is also tested for predicting multiple loops in β-barrel membrane proteins. For outer-membrane protein G, the lowest energy conformation has a RMSD of 2.62 Å for the three extracellular interacting loops with a total length of 34 residues (12, 12 and 10 residues in each loop).
  
  
  METHODS
  The software is freely available at: tanto.bioe.uic.edu/m-DiSGro.
  
  
  BACKGROUND
  jinfeng@stat.fsu.edu or jliang@uic.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL.
authors: Ke
authors: K
authors: Tang
authors: Department of Statistics, University of Florida, Gainesville, FL.
authors: Samuel W K
authors: SW
authors: Wong
authors: Department of Statistics, Harvard University, Science Center, Cambridge, MA and.
authors: Jun S
authors: JS
authors: Liu
authors: Department of Statistics, Florida State University, Tallahassee, FL, USA.
authors: Jinfeng
authors: J
authors: Zhang
authors: Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL.
authors: Jie
authors: J
authors: Liang
mesh_terms: D003198:Computer Simulation; D006801:Humans; D008565:Membrane Proteins / Q000737:chemistry*; D008958:Models, Molecular; D009010:Monte Carlo Method; D011487:Protein Conformation; D012984:Software
chemical_list: D008565:Membrane Proteins