Structural and energy determinants in protein-RNA docking.
Deciphering the structural and energetic determinants of protein-RNA interactions harbors the potential to understand key cell processes at molecular level, such as gene expression and regulation. With this purpose, computational methods like docking aim to complement current biophysical and structural biology efforts. However, the few reported docking algorithms for protein-RNA interactions show limited predictive success rates, mainly due to incomplete sampling of the conformational space of both the protein and the RNA molecules, as well as to the difficulties of the scoring function in identifying the correct docking models. Here, we have tested the predictive value of a variety of knowledge-based and energetic scoring functions on a recently published protein-RNA docking benchmark and developed a scoring function able to efficiently discriminate docking decoys. We first performed docking calculations with the bound conformation, which allowed us to analyze the problem in optimal conditions. We found that geometry-based terms and electrostatics were the most important scoring terms, while binding propensities and desolvation were much less relevant for the scoring of protein-RNA models. This is in contrast with what we observed for protein-protein docking. The results also showed an interesting dependence of the predictive rates on the flexibility of the protein molecule, which arises from the observed higher positive charge of flexible interfaces and provides hints for future development of more efficient protein-RNA docking methods.
Joint BSC-CRG-IRB Research Program in Computational Biology, Life Sciences Department, Barcelona Supercomputing Center (BSC), Jordi Girona 29, Barcelona 08034, Spain; Center for Neurobehavioral Genetics and Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
Laura
L
Pérez-Cano
Joint BSC-CRG-IRB Research Program in Computational Biology, Life Sciences Department, Barcelona Supercomputing Center (BSC), Jordi Girona 29, Barcelona 08034, Spain.
Miguel
M
Romero-Durana
Joint BSC-CRG-IRB Research Program in Computational Biology, Life Sciences Department, Barcelona Supercomputing Center (BSC), Jordi Girona 29, Barcelona 08034, Spain. Electronic address: juanf@bsc.es.
Juan
J
Fernández-Recio
D000465:Algorithms; D019985:Benchmarking; D001665:Binding Sites; D019295:Computational Biology / Q000706:statistics & numerical data*; D015233:Models, Statistical; D062105:Molecular Docking Simulation / Q000706:statistics & numerical data*; D009690:Nucleic Acid Conformation; D011485:Protein Binding; D011487:Protein Conformation; D012313:RNA / Q000737:chemistry*; D016601:RNA-Binding Proteins / Q000737:chemistry*; D012107:Research Design; D055672:Static Electricity; D013816:Thermodynamics
D016601:RNA-Binding Proteins; D012313:RNA
Computational docking; Protein-RNA interactions; Residue-ribonucleotide potentials; Scoring functions; Structural modelling