Computational modeling of RNA-protein interactions remains an important endeavor. However, exclusively all-atom approaches that model RNA-protein interactions via molecular dynamics are often problematic in their application. One possible alternative is the implementation of hierarchical approaches, first efficiently exploring configurational space with a coarse-grained representation of the RNA and protein. Subsequently, the lowest energy set of such coarse-grained models can be used as scaffolds for all-atom placements, a standard method in modeling protein 3D-structure. However, the coarse-grained modeling likely will require improved ribonucleotide-amino acid potentials as applied to coarse-grained structures. As a first step we downloaded 1,345 PDB files and clustered them with PISCES to obtain a non-redundant complex data set. The contacts were divided into nine types with DSSR according to the 3D structure of RNA and then 9 sets of potentials were calculated. The potentials were applied to score fifty thousand poses generated by FTDock for twenty-one standard RNA-protein complexes. The results compare favorably to existing RNA-protein potentials. Future research will optimize and test such combined potentials.
|Advisor:||Lustig, Brooke, Eggers, Daryl K.|
|Commitee:||Rascon, Alberto A.|
|School:||San Jose State University|
|School Location:||United States -- California|
|Source:||MAI 56/03M(E), Masters Abstracts International|
|Subjects:||Biochemistry, Bioinformatics, Biophysics|
|Keywords:||Descriptor-based, Hydrogen bonding, Knowledge-base, Protein, RNA, Statistical potential|
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