DOCK 6: combining techniques to model RNA-small molecule complexes.
With an increasing interest in RNA therapeutics and for targeting RNA to treat disease, there is a need for the tools used in protein-based drug design, particularly DOCKing algorithms, to be extended or adapted for nucleic acids. Here, we have compiled a test set of RNA-ligand complexes to validate the ability of the DOCK suite of programs to successfully recreate experimentally determined binding poses. With the optimized parameters and a minimal scoring function, 70% of the test set with less than seven rotatable ligand bonds and 26% of the test set with less than 13 rotatable bonds can be successfully recreated within 2 A heavy-atom RMSD. When DOCKed conformations are rescored with the implicit solvent models AMBER generalized Born with solvent-accessible surface area (GB/SA) and Poisson-Boltzmann with solvent-accessible surface area (PB/SA) in combination with explicit water molecules and sodium counterions, the success rate increases to 80% with PB/SA for less than seven rotatable bonds and 58% with AMBER GB/SA and 47% with PB/SA for less than 13 rotatable bonds. These results indicate that DOCK can indeed be useful for structure-based drug design aimed at RNA. Our studies also suggest that RNA-directed ligands often differ from typical protein-ligand complexes in their electrostatic properties, but these differences can be accommodated through the choice of potential function. In addition, in the course of the study, we explore a variety of newly added DOCK functions, demonstrating the ease with which new functions can be added to address new scientific questions.
Lang
P Therese
PT
Graduate Program in Chemistry and Chemical Biology, University of California, San Francisco, California 94143, USA.
Brozell
Scott R
SR
Mukherjee
Sudipto
S
Pettersen
Eric F
EF
Meng
Elaine C
EC
Thomas
Veena
V
Rizzo
Robert C
RC
Case
David A
DA
James
Thomas L
TL
Kuntz
Irwin D
ID
D000465:Algorithms; D001665:Binding Sites; D008024:Ligands; D008958:Models, Molecular; D012313:RNA / Q000737:chemistry* / Q000378:metabolism; D012984:Software
D008024:Ligands; D012313:RNA