PhD candidate / guest
I am a bioinformatician specialised in VENOMICS. I not only aim at the evolution of toxins, also aim at exploiting animal venom compounds for the development of novel therapeutics with BIOINFORMATICS methods.
VENOMICS will implement an innovative workflow involving cutting-edge transcriptomics, proteomics and high-throughput peptide production technologies to decipher venom diversity.
BIOINFORMATICS is used to tackle specific challenges associated with the identification and annotations of toxins. Recognizing toxin transcript sequences among second generation sequencing data cannot rely only on basic sequence similarity because toxins are highly divergent. Mass spectrometry sequencing of mature toxins is challenging because toxins can display a large number of post-translational modifications (PTM). Identifying the mature toxin region in toxin precursor sequences requires the prediction of the cleavage sites of proprotein convertases, most of which are unknown or not well characterized. Tracing the evolutionary relationships between toxins should consider specific mechanisms of rapid evolution as well as interactions between predatory animals and prey. Rapidly determining the activity of toxins is the main bottleneck in venomics discovery, but some recent ML approaches give hope that accurate predictions of toxin specificity could be made in the near future, and ML methods can also simulate some progress of drug developments, which give instructions and cut the number of candidates for clinical tests, which finally saves huge amount of researching time and fund.