Open AccessA pair-conformation-dependent scoring function for evaluating 3D RNA-protein complex structures
Author(s) -
Haotian Li,
Yangyu Huang,
Yi Xiao
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0174662
Subject(s) - benchmarking , protein structure prediction , rna , computer science , computational biology , scoring system , function (biology) , protein structure , score , artificial intelligence , bioinformatics , algorithm , data mining , biology , machine learning , genetics , medicine , biochemistry , marketing , surgery , gene , business
Computational prediction of RNA-protein complex 3D structures includes two basic steps: one is sampling possible structures and another is scoring the sampled structures to pick out the correct one. At present, constructing accurate scoring functions is still not well solved and the performances of the scoring functions usually depend on used benchmarks. Here we propose a pair-conformation-dependent scoring function, 3dRPC-Score, for 3D RNA-protein complex structure prediction by considering the nucleotide-residue pairs having the same energy if their conformations are similar, instead of the distance-only dependence of the most existing scoring functions. Benchmarking shows that 3dRPC-Score has a consistent performance in three test sets.