Abstract
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.
Highlights
RNA-Protein interactions are widespread in cells [1,2,3,4,5,6,7]
To compare the performance with other scoring functions, we give the results of DECK-RP[15] and ITScore-PR [18] since these two scoring functions have compared with other existing scoring functions and performed better than the latter
A nearnative structure is defined as a decoy structure who has a ligand RMSD (LRMSD) less than 10 Å from the native structure
Summary
RNA-Protein interactions are widespread in cells [1,2,3,4,5,6,7]. For understanding these interactions, 3D structures of RNA-protein complexes are necessary. Some computational methods to predict the 3D structures of RNA-protein complexes from protein and RNA monomer structures have been developed [11,12,13,14,15,16,17]. Prediction of 3D RNA-protein complex structures includes two key steps: sampling and scoring. For RNA-protein complex structure prediction, some scoring functions have been proposed, such as DARS-RNP and QUASI-RNP [12], DECK-RP[15], ITScore-PR [18] and so on [14, 19,20,21,22,23,24,25]. The scoring function DECK-RP is a distance-dependent statistical potential and is included in our program of 3D RNAprotein complex structure prediction 3dRPC [15].
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