Laboratory of Bioinformatics and Protein Engineering: Bujnicki Laboratory

Current Research

    The Laboratory of Bioinformatics and Protein Engineering is involved in theoretical and experimental research on sequence-structure-function relationships in proteins and nucleic acids and macromolecular complexes. Theoretical research involves the development of computer software for the analysis of biological macromolecules. Currently, the focus is on the development of software for the structural prediction and modeling of RNA and RNA-protein complexes. Thus far, we have developed and made publicly available one of the first methods for the automated comparative modeling of RNA (ModeRNA;, a method for the structure-based prediction of metal ion binding sites (MetalionRNA;, and statistical potentials for predicting the structure of RNA-protein complexes (DARS-RNP and QUASI-RNP;
   Our suite of programs for protein structure prediction and analysis include the GeneSilico MetaServer for primary, secondary, and tertiary structure prediction (, a method for the quality assessment of protein models (MetaMQAP;, and a method for the discrimination of models according to their agreement with experimental data (FILTREST3D; We also developed methods for the prediction of order/disorder in protein structures ( and protein localization in Gram-negative bacterial cells (MetaLocGramN; We also developed a system of nucleic acid metabolism databases. Published elements of this system include MODOMICS (i.e., a database for the systems biology of RNA modification;, REPAIRtoire (i.e., a database for the systems biology of DNA repair;, and RNApathwaysDB (i.e., a database of pathways of RNA maturation and decay;
   Our experimental research is focused on the elucidation of sequence-structure-function relationships in proteins and nucleic acids using biophysics, biochemistry, molecular biology, and cell biology. Three principal types of analyses are performed by researchers in our wet lab:

• Experimental testing of functional predictions by gene cloning or nucleic acid synthesis, protein or RNA expression, purification, development of in vitro and in vivo functional assays, and biochemical and cellular characterization.
• Experimental testing of protein or RNA structural predictions by application of low-resolution structural probing methods, such as mutagenesis, chemical modification, crosslinking, mass spectrometry, and circular dichroism.
• Protein engineering to obtain enzymes with new, useful features, particularly altered substrate specificity (e.g., nucleases that recognize and cut new sequences in DNA or RNA).

   Our theoretical and experimental research is tightly integrated, demonstrated by the publication of articles that comprise a combination of theoretical and experimental analyses (e.g., prediction and characterization of new enzymes).
Protein engineering involves iterative protein structure model building, model-based experimental planning, a series of experimental analyses, and experiment-based improvement of the models and tools used for model building.



Recent highlights

Successful development of an enzyme that sequencespecifically cuts RNA in RNA/DNA hybrids: a case study

   Ribonucleases (RNases) are valuable tools applied in the analysis of RNA sequences, structures, and function. Their substrate specificity is limited to the recognition of single bases or distinct secondary structures in the substrate. Currently, no RNases are available for the purely sequence-dependent fragmentation of RNA. Researchers from the Bujnicki laboratory, in collaboration with Dr. Nowotny (Head of Laboratory of Protein Structure at IIMCB), have developed a new enzyme that cleaves the RNA strand in DNA-RNA hybrids five nucleotides from a specific recognition sequence. The design involved a combination of computational structure prediction and experimental analyses. The engineered enzyme was a fusion of two functionally distinct domains: RNase HI that hydrolyzes RNA in DNA-RNA hybrids in a processive and sequenceindependent manner and a zinc finger that recognizes a sequence in DNA-RNA hybrids.
   Methods for engineering zinc finger domains with new sequence specificities are readily available, making the acquisition of a library of RNases that recognize and cleave various sequences feasible, much like the commercially available assortment of restriction enzymes. Zinc finger-RNase HI fusions, in addition to in vitro applications, may potentially be used in vivo for targeted RNA degradation. The results of this research are the subject of a patent application and have been published (Sulej et al., Nucleic Acids Res, 2012, 40:11563-115670)

Computational structural analysis of mRNA-splicing machinery in human cells: a case study

   The spliceosome is one of the largest molecular machines known. It excises introns from eukaryotic pre-mRNAs. In human cells, it comprises five RNAs, over 100 “core” proteins, and more than 100 additional associated proteins. The details of the spliceosome mechanism of action are unclear because only a small fraction of spliceosomal proteins have been characterized structurally in high resolution.
   Researchers from the Bujnicki laboratory have performed a comprehensive analysis of the human spliceosomal proteome. They discovered that almost half of the combined sequence of proteins that are abundant in the spliceosome are predicted to be intrinsically disordered, at least when the individual proteins are considered in isolation. They also correlated the type and abundance of disordered proteins with different protein functions. For regions without an experimental structure in the ordered part of the spliceosomal proteome, they predicted and modeled three-dimensional structures. They also developed a database of structural models for the entire spliceosomal proteome, called SpliProt3D.
The results of this work enable multiscale modeling of the structure and dynamics of the entire spliceosome and its subcomplexes and will guide further research toward understanding the molecular mechanism of mRNA splicing. The results of this research have been published (Korneta et al., Nucleic Acids Res, 2012, 40:7046-7065; Korneta and Bujnicki, PLoS Comput Biol, 2012, 8:e1002641).