Thesis supervisor: professor Maido Remm (University of Tartu).
Opponent: Dr. Helena Safavi-Hemami, (Utah University, Salt Lake City, USA).
Conopeptides are small proteins found in the venom of cone snails (Conus sp.). Cone snails feed on worms, molluscs and fish. They paralyze their prey with venom and swallow it whole. The fast immobilization appears as a result of the mixture of conopeptides in the venom. Conopeptides are synthesized as prepropeptides with a signal sequence for transport into the venom duct, pro-peptide that facilitates proper folding and mature peptide. Conopeptides are grouped into superfamilies according to the signal sequences.
Scientists are studying the conopeptides hoping to find new drug candidates. Conopeptides are specific modulators of ion channels in nerve and muscle cells and therefore can be potentially used as painkillers or muscle relaxants.
Aim of this study was to develop a method for finding and classifying conopeptides from large amounts of sequences. Classification is important since finding the proteins similar to a newly discovered protein we get a lot of information about it. We used two types of models for classification and identification – profile hidden Markov Models (pHMMs) and position specific scoring matrices (PSSMs). With the signal peptide present the classification is 100% specific and sensitive. By combining the pHMMs and PSSMs we were able to obtain 91% sensitivity also for classification of mature peptides, which is better than with other methods.
The second aim of this study was to find conopeptides from the genome and venom duct transcriptome of Conus consors. We used multiple methods, including the pHMMs, to locate the conopeptides. We discovered 214 conopeptides from the genome, 187 of which were novel. We also described the exon-intron structure for 15 conopeptide genes from 13 different superfamilies. Gene structure may influence the propagation of conopeptide diversity.