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Review Article

Advances in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs

[ Vol. 26 , Issue. 26 ]


Kuo-Chen Chou*   Pages 4918 - 4943 ( 26 )


The smallest unit of life is a cell, which contains numerous protein molecules. Most of the functions critical to the cell’s survival are performed by these proteins located in its different organelles, usually called ‘‘subcellular locations”. Information of subcellular localization for a protein can provide useful clues about its function. To reveal the intricate pathways at the cellular level, knowledge of the subcellular localization of proteins in a cell is prerequisite. Therefore, one of the fundamental goals in molecular cell biology and proteomics is to determine the subcellular locations of proteins in an entire cell. It is also indispensable for prioritizing and selecting the right targets for drug development. Unfortunately, it is both timeconsuming and costly to determine the subcellular locations of proteins purely based on experiments. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods for rapidly and effectively identifying the subcellular locations of uncharacterized proteins based on their sequences information alone. Actually, considerable progresses have been achieved in this regard. This review is focused on those methods, which have the capacity to deal with multi-label proteins that may simultaneously exist in two or more subcellular location sites. Protein molecules with this kind of characteristic are vitally important for finding multi-target drugs, a current hot trend in drug development. Focused in this review are also those methods that have use-friendly web-servers established so that the majority of experimental scientists can use them to get the desired results without the need to go through the detailed mathematics involved.


5-step rules, multi-label proteins, multi-target drugs, global accuracy and metrics, local accuracy and metrics, absolute true rate, web-server.


Gordon Life Science Institute, Boston, MA 02478

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