Dr Vladimir Likic: bioinformatics and systems biology

Our research interests include classical and emerging fields in bioinformatics, in particular applied bioinformatics and systems biology.

For systems biology please follow this link.

Protein sequence analysis and applications to protein transport systems:

All cellular life forms are bound by a biological membrane and many cells, including those of humans and most human pathogens, have distinct “sub-cellular compartments” due to internal, membrane-bound structures. In order for cells to grow and divide, these subcellular compartments need to be continuously populated with new protein molecules: to provide structural framework, biosynthetic capability and metabolic activity. The substrate protein molecules are delivered into subcellular compartments specifically and efficiently by molecular machines referred to as protein translocases. In collaboration with Trevor Lithgow ( Department of Biochemistry Monash University) we are working to elucidate functions of mitochondrial transport proteins and secretion systems in bacterial pathogens. This research involves sequence analysis, iterative searches of genomic databases, application of pattern recognition for motif detection, and application of classification methods to discriminate similar proteins that perform distinct biological functions.

Bioinformatics for metabolic profiling and biomarkers:

We are interested in methods for signal processing, post-processing, and statistical analysis of metabolic profiling and biomarker data. In collaboration with Malcolm McConville ( Department of Biochemistry, University of Melbourne) we are developing methods for direct characterisation of parasitic pathogens metabolome by low-molecular weight profiling experiments, based on gas-chromatography mass-spectrometry (GC-MS), liquid-chromatography mass-spectrometry (LC-MS), and nuclear magnetic resonance (NMR). We use the trypanosomatidae of the genus Leishmania as the model organism. Leishmania are sandfly-transmitted parasites endemic throughout the tropic and subtropics which infects around 12 million people worldwide.

Database of Leishmania metabolic pathways:

We are currently developing a pathway/genome database for Leishmania (LeishCyc), based on the data provided by The Leishmania major Friedlin Genome Project from the Sanger Institute, and our own curation. The development of LeishCyc is based on the methodology developed by Peter Karp from SRI International. This is the technology behind BioCyc collection of databases, including EcoCyc and MetaCyc.

Computer simulations of biological systems:

It is well understood that protein three-dimensional structure are not static at physiological temperatures, rather their conformational flexibility is ubiquitous and necessary for function. Protein motions are extraordinarily complex which characteristic times spanning more than ten orders of magnitude. Only a few experimental techniques are capable providing information about protein motions (protein NMR being probably the most versatile), and theoretical methods which can provide insight into protein dynamics are invaluable. We have a long standing interest in molecular dynamics (MD) simulations of protein dynamics which allow one to study computer models of protein intrinsic motion. In the past we have studied intestinal fatty-acid binding protein by MD simulations, and also calmodulin, a small protein which acts as a principal modulator of intracellular calcium signalling pathways. We are particularly interested in the interpretation and applications of protein MD simulations, their chaotic behavior, and the reproducibility problem which arises from the difficulty to properly sample protein's conformational space.

Scientific data and information management:

The biological research is increasingly becoming integrative and data-driven. An important yet largely unsolved problem is the need to accurately capture the information associated with complex biological experiments (such as those in proteomics, metabolomics, or protein structure determination), which includes both experimental data and associated metadata (essential for repeating the experiments and re-interpretation of results if the current knowledge evolves beyond the initial interpretation).

Selected publications (full publications list)

Doyle MA, MacRae JI, De Souza DP, Saunders EC, McConville MJ, and Vladimir Likic, LeishCyc: a biochemical pathways database for Leishmania major, BMC Systems Biology, 3:57 (2009) (link to article)

Robinson MD, De Souza DP, Keen WW, Saunders EC, McConville MJ, Speed TP, Vladimir Likic, A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments, BMC Bioinformatics, 8:419 (2007).

McConville MJ, de Souza D, Saunders E, Vladimir Likic, Naderer T, Living in a phagolysosome; metabolism of Leishmania amastigotes, Trends Parasitol. 2007 Jun 30; [Epub ahead of print] PMID: 17606406

Gentle IE, Perry AJ, Alacock FH, Vladimir Likic, Dolezal P, Ng E, Purcell AW, McConville MJ, Naderer T, Chanez AL, Charriere F, Aschinger C, Schneider A, Tokatlidis K, Lithgow T, Conserved motifs reveal details of ancestry and structure in the small TIM chaperones of the mitochondrial intermembrane space, Molecular Biology and Evolution, Feb 2007 [Epub ahead of print], PMID: 17329230.

Dolezal P, Vladimir Likic, Tachezy J, and Lithgow T, Evolution of the Molecular Machines for Protein Import into Mitochondria, Science 313: 314-318 (2006).

DeSouza DP, Saunders EC, McConville MJ, Vladimir Likic, Progressive Peak Clustering in GC-MS Experiments Applied to Leishmania Parasites, Bioinformatics 22(11):1391-6 (2006)