Bujnicki lab - NCN (OPUS)
  • RNA has recently emerged as an attractive target for new drug development. Our team is developing new methods to study the interactions between RNA and ligands. Recently, we have developed a new machine learning method called AnnapuRNA to predict how small chemical molecules interact with structured RNA molecules. Research published in PLoS Comput Biol. 2021 Feb 1;17(2):e1008309. doi: 10.1371/journal.pcbi.1008309. Read More
  • 1

About Laboratory Of Bioinformatics And Protein Engineering

Our group is involved in theoretical and experimental research on nucleic acids and proteins. The current focus is on RNA sequence-structure-function relationships (in particular 3D modeling), RNA-protein complexes, and enzymes acting on RNA.
 
We study the rules that govern the sequence-structure-function relationships in proteins and nucleic acids and use the acquired knowledge to predict structures and functions for uncharacterized gene products, to alter the known structures and functions of proteins and RNAs and to engineer molecules with new properties.
 
Our key strength is in the integration of various types of theoretical and experimental analyses. We develop and use computer programs for modeling of protein three-dimensional structures based on heterogenous, low-resolution, noisy and ambivalent experimental data. We are also involved in genome-scale phylogenetic analyses, with the focus on identification of proteins that belong to particular families. Subsequently, we characterize experimentally the function of the most interesting new genes/proteins identified by bioinformatics. We also use theoretical predictions to guide protein engineering, using rational and random approaches. Our ultimate goal is to identify complete sets of enzymes involved in particular metabolic pathways (e.g. RNA modification, DNA repair) and to design proteins with new properties, in particular enzymes with new useful functions, which have not been observed in the nature.
 
We are well-equipped with respect to both theoretical and experimental analyses. Our lab offers excellent environment for training of young researchers in both bioinformatics and molecular biology/biochemistry of protein-nucleic acid interactions.


More Good Science

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