title: DARS-RNP and QUASI-RNP: new statistical potentials for protein-RNA docking.
abstract: BACKGROUND
  Protein-RNA interactions play fundamental roles in many biological processes. Understanding the molecular mechanism of protein-RNA recognition and formation of protein-RNA complexes is a major challenge in structural biology. Unfortunately, the experimental determination of protein-RNA complexes is tedious and difficult, both by X-ray crystallography and NMR. For many interacting proteins and RNAs the individual structures are available, enabling computational prediction of complex structures by computational docking. However, methods for protein-RNA docking remain scarce, in particular in comparison to the numerous methods for protein-protein docking.
  
  
  RESULTS
  We developed two medium-resolution, knowledge-based potentials for scoring protein-RNA models obtained by docking: the quasi-chemical potential (QUASI-RNP) and the Decoys As the Reference State potential (DARS-RNP). Both potentials use a coarse-grained representation for both RNA and protein molecules and are capable of dealing with RNA structures with posttranscriptionally modified residues. We compared the discriminative power of DARS-RNP and QUASI-RNP for selecting rigid-body docking poses with the potentials previously developed by the Varani and Fernandez groups.
  
  
  CONCLUSIONS
  In both bound and unbound docking tests, DARS-RNP showed the highest ability to identify native-like structures. Python implementations of DARS-RNP and QUASI-RNP are freely available for download at http://iimcb.genesilico.pl/RNP/
authors.affiliation: Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Ul, Ks. Trojdena 4, PL-02-109 Warsaw, Poland.
authors.forename: Irina
authors.initials: I
authors.lastname: Tuszynska
authors.forename: Janusz M
authors.initials: JM
authors.lastname: Bujnicki
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D051188:Knowledge Bases; D008958:Models, Molecular; D015233:Models, Statistical; D012313:RNA / Q000737:chemistry* / Q000378:metabolism*; D016601:RNA-Binding Proteins / Q000737:chemistry* / Q000378:metabolism*; D012261:Ribonucleoproteins / Q000737:chemistry / Q000378:metabolism
chemical_list: D016601:RNA-Binding Proteins; D012261:Ribonucleoproteins; D012313:RNA