Abstract
Coffee industry is threatened by production losses due to the rust disease since 1850. The coffee leaf rust (CLR) disease has an important social and economical impacts and its control is still a challenge. The CLR pathogen is the fungus Hemileia vastatrix Berkeley & Broome (Basidiomycota, order Pucciniales) that is currently controlled by using non-specific anti-fungal chemicals spraying. The advances in molecular biology and bioinformatics may allow the identification of new targets and environmentally safe strategies for controlling CLR. Several genomic and transcriptomic data are available for H. vastatrix that allow searching for new proteins to achieve a better disease control. We used the dataset of 34,242 sequences from the fungal genome and transcriptome, with a filtering strategy for protein annotation, structure and cell sublocalization to select three essential proteins related to steroid synthesis, cell membrane, and cell wall metabolism. This short paper reports the ongoing study to allow the development of new molecules that might be validated and contribute to new products that are specific and ecologically friendly.
Supported by Bayer Grants4Target/Embrapa.
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Lima, J.D. et al. (2020). Searching in Silico Novel Targets for Specific Coffee Rust Disease Control. In: Kowada, L., de Oliveira, D. (eds) Advances in Bioinformatics and Computational Biology. BSB 2019. Lecture Notes in Computer Science(), vol 11347. Springer, Cham. https://doi.org/10.1007/978-3-030-46417-2_10
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DOI: https://doi.org/10.1007/978-3-030-46417-2_10
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