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TMCrys: predict propensity of success for transmembrane protein crystallization
MOTIVATION: Transmembrane proteins (TMPs) are crucial in the life of the cells. As they have special properties, their structure is hard to determine––the PDB database consists of 2% TMPs, despite the fact that they are predicted to make up to 25% of the human proteome. Crystallization prediction me...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137969/ https://www.ncbi.nlm.nih.gov/pubmed/29718100 http://dx.doi.org/10.1093/bioinformatics/bty342 |
Sumario: | MOTIVATION: Transmembrane proteins (TMPs) are crucial in the life of the cells. As they have special properties, their structure is hard to determine––the PDB database consists of 2% TMPs, despite the fact that they are predicted to make up to 25% of the human proteome. Crystallization prediction methods were developed to aid the target selection for structure determination, however, there is a need for a TMP specific service. RESULTS: Here, we present TMCrys, a crystallization prediction method that surpasses existing prediction methods in performance thanks to its specialization for TMPs. We expect TMCrys to improve target selection of TMPs. AVAILABILITY AND IMPLEMENTATION: https://github.com/brgenzim/tmcrys SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
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