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Published: Tuesday, 06 August 2019 13:53
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Development of new methods for designing RNA molecules that fold into desired spatial structures and their use for development of new functional RNAs and for prediction of noncoding RNAs in transcriptome sequences (2017/25/B/NZ2/01294); 1 494 250 PLN; 2018-2021. PI: J.M.Bujnicki, vice-PI: T.Wirecki
Ribonucleic acid (RNA) molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, they sense and communicate responses to cellular signals, and even catalyze chemical reactions. These functions of RNAs depend on their ability to assume one or more structures, which is encoded by the ribonucleotide sequence. One of the fundamental challenges of biology and chemistry is to design molecules that form desired structures and carry out desired functions. The computational design of RNA requires solving the so-called RNA inverse folding problem: given a target structure, identify one or more sequences that fold into that structure (and do not fold into any other structure). Nonetheless, RNA design is challenging, especially for molecules with complex structures. In particular, there is a scarcity of methods for designing RNA 3D structures, and they have severe restrictions – for instance they usually require a fixed RNA structural framework and only allow the RNA bases to change, but keep the sequence length and the shape of the RNA chain fixed. In the project, we are developing a new software package for computational design of RNA sequences, which takes into account 3D structure, conformational changes, and binding of RNA molecules to each other.
We have developed two prototypical methods for RNA sequence design: DesiRNA for secondary-structure based design which allows designing oligomers and alternative structures, and SimRNA-Design for 3D based design, “mutating” the RNA sequence during 3D folding simulations. We are further developing the two methods, and we plan to combine them into one package for designing of RNAs composed of one or multiple strands, and capable of switching between different 3D structures (including changes of the global shape, patterns of canonical and non-canonical base pairs, and oligomeric states). The new program will enable changing sequence length in the form of small insertions and deletions. The design of RNA molecules with such flexibility is entirely out of reach for currently existing programs. The utility of the new computational method will be tested by the experimental validation of designed RNAs. First, selected designed RNA molecules will be synthesized, and their structure(s) will be analyzed. A combination of computational design, structural modeling, and experimental analyses will thereby lead to the development of new, artificial, functional RNAs. Second, the new method will be used to enrich alignments of naturally occurring RNAs (e.g., riboswitches, ribozymes) with artificial sequences, aiming to improve the methodology of remote homology detection, as it was earlier done for protein sequence alignments. We will use the combination of natural and artificially designed sequences to improve the sequence profile/covariation information for known RNA families with members of a known 3D structure. These sequence profiles extended by structure-based sequence design will aid in the searches for previously unknown members of these RNA families in genomic sequence databases. Structural and functional predictions (e.g., new candidates for functional RNAs) will also be validated experimentally.
The project is carried out by an interdisciplinary team of researchers, including computer programmers, researchers specializing in computer simulations and data analysis, and biochemists who analyze RNA molecules experimentally
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Published: Friday, 05 April 2019 12:36
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FNP (TEAM): Modeling of dynamic interactions between RNA and small molecules and its practical applications (POIR.04.04.00-00-3CF0/16-00); 3 449 541 PLN; 2017-2020. PI: J.M.Bujnicki, vice-PI: F.Stefaniak
Ribonucleic acid (RNA) molecules play pivotal roles in living organisms. They are involved in a variety of biological processes: they transmit genetic information, they sense and communicate responses to cellular signals, and even catalyze chemical reactions. The cellular and molecular functions of RNAs depend on the structure of the ribonucleotide chain and on interactions with other molecules, which are defined by the ribonucleotide sequence. Structures and functions of RNAs are often modulated by chemical compounds, including naturally occurring molecules as well as compounds obtained by synthetic organic chemistry. Many RNA molecules are known or predicted targets of small molecule drugs, and the continuous discovery of new functional RNAs involved in various biomedically important processes increases the demand on the development of new small molecules targeting RNA, and on methods for analyzing RNA-small molecule ligand interactions.
Unfortunately, the advancement of computational methods for predicting RNA-ligand interactions lags behind the analogous methods for analyzing protein-ligand interactions. In particular, there is a dearth of computational methods for modeling the 3D structure and dynamics of RNA-ligand complexes. Currently, it is almost impossible to computationally predict structures of RNA-ligand complexes that involve large conformational changes of the RNA upon ligand binding, or that are stable only in the presence of the ligand, unless very similar structures are already known. This situation hampers equally basic studies of RNA sequence-structure-function relationships, and applied research on the development of small molecule regulators of biomedically important RNAs.
In this research project, we develop and experimentally validate a general-purpose computational method for predicting RNA-ligand interactions that can model conformational changes. The new method enables simulations of conformational changes in RNA in response to ligand binding, such as those in riboswitches, which are currently out of reach for existing programs. It also extends the range of applications involving the prediction of potential ligands for target RNAs in the context of virtual screening.
We also test our computational approach in practice. It is applied to study the basic mechanism of action of RNAs known to be regulated by small molecules, e.g., riboswitches. We look for novel inhibitors for RNAs from bacterial and viral pathogens, like RNA promoter of influenza A or hepatitis C virus (HCV) and internal ribosome entry site (IRES). Such holistic and interdisciplinary approach enables us not only to verify the developed computational methods but also significantly expands the knowledge of the nature of RNA, with possible practical applications in many areas of science and industry.
Publications resulting from and supported by the project:
Ponce-Salvatierra A, Astha, Merdas K, Nithin C, Ghosh P, Mukherjee S, Bujnicki JM
Computational modeling of RNA 3D structure based on experimental data.
Biosci Rep. 2019 Feb 8;39(2).
Nithin C, Ghosh P, Bujnicki JM
Bioinformatics Tools and Benchmarks for Computational Docking and 3D structure prediction of RNA-protein complexes
Genes (Basel). 2018 Aug 25;9(9). pii: E432. doi: 10.3390/genes9090432.
Kumari P, Aeschimann F, Gaidatzis D, Keusch J, Ghosh P, Neagu A, Pachulska-Wieczorek K, Bujnicki JM, Gut H, Grosshans H, Ciosk R
Evolutionary plasticity of the NHL domain underlies distinct solutions to RNA recognition.
Nat Commun. 2018 Apr 19;9(1):1549.
