Premium
An all‐atom knowledge‐based energy function for protein‐DNA threading, docking decoy discrimination, and prediction of transcription‐factor binding profiles
Author(s) -
Xu Beisi,
Yang Yuedong,
Liang Haojun,
Zhou Yaoqi
Publication year - 2009
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.22384
Subject(s) - decoy , dna , docking (animal) , macromolecular docking , threading (protein sequence) , computational biology , transcription factor , dna binding site , hmg box , dna binding protein , biophysics , physics , biology , protein structure , genetics , gene , biochemistry , promoter , medicine , gene expression , receptor , nursing
How to make an accurate representation of protein-DNA interaction by an energy function is a long-standing unsolved problem in structural biology. Here, we modified a statistical potential based on the distance-scaled, finite ideal-gas reference state so that it is optimized for protein-DNA interactions. The changes include a volume-fraction correction to account for unmixable atom types in proteins and DNA in addition to the usage of a low-count correction, residue/base-specific atom types, and a shorter cutoff distance for protein-DNA interactions. The new statistical energy functions are tested in threading and docking decoy discriminations and prediction of protein-DNA binding affinities and transcription-factor binding profiles. The results indicate that new proposed energy functions are among the best in existing energy functions for protein-DNA interactions. The new energy functions are available as a web-server called DDNA 2.0 at http://sparks.informatics.iupui.edu. The server version was trained by the entire 212 protein-DNA complexes.