Computational modeling of RNA 3D structures, with the aid of experimental restraints.
In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation ("Greek science" approach) or utilize information derived from known structures of other RNA molecules ("Babylonian science" approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately.
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Marcin
M
Magnus
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Dorota
D
Matelska
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Grzegorz
G
Lach
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Grzegorz
G
Chojnowski
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Michal J
MJ
Boniecki
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Elzbieta
E
Purta
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Wayne
W
Dawson
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland.
Stanislaw
S
Dunin-Horkawicz
Laboratory of Bioinformatics and Protein Engineering; International Institute of Molecular and Cell Biology; Warsaw, Poland; Laboratory of Structural Bioinformatics; Institute of Molecular Biology and Biotechnology; Faculty of Biology; Adam Mickiewicz University; Poznan, Poland.
Janusz M
JM
Bujnicki
D000465:Algorithms; D020029:Base Pairing; D019295:Computational Biology / Q000379:methods; D019143:Evolution, Molecular; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry* / Q000235:genetics; D012997:Solvents; D013816:Thermodynamics
D012997:Solvents; D012313:RNA
RNA structure; RNA structure prediction; bioinformatics; chemical probing; macromolecular modeling