Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0053197
Title: Benchmarking Human Protein Complexes to Investigate Drug-Related Systems and Evaluate Predicted Protein Complexes
Authors: Wu M.
Yu Q.
Li X. 
Zheng J.
Huang J.-F.
Kwoh C.-K.
Keywords: adenosine triphosphate
drug binding protein
geldanamycin
glutamic acid
guanosine diphosphate
imatinib
mannose
myristic acid
reduced nicotinamide adenine dinucleotide
protein
article
catalog human protein complex
complex formation
computational fluid dynamics
drug protein binding
human
insulin dependent diabetes mellitus
protein analysis
protein database
protein function
protein protein interaction
protein quality
quality control
drug interaction
metabolism
procedures
protein analysis
quality control
Benchmarking
Databases, Protein
Drug Interactions
Humans
Protein Interaction Mapping
Proteins
Issue Date: 2013
Citation: Wu M., Yu Q., Li X., Zheng J., Huang J.-F., Kwoh C.-K. (2013). Benchmarking Human Protein Complexes to Investigate Drug-Related Systems and Evaluate Predicted Protein Complexes. PLoS ONE 8 (2) : e53197. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0053197
Rights: Attribution 4.0 International
Abstract: Protein complexes are key entities to perform cellular functions. Human diseases are also revealed to associate with some specific human protein complexes. In fact, human protein complexes are widely used for protein function annotation, inference of human protein interactome, disease gene prediction, and so on. Therefore, it is highly desired to build an up-to-date catalogue of human complexes to support the research in these applications. Protein complexes from different databases are as expected to be highly redundant. In this paper, we designed a set of concise operations to compile these redundant human complexes and built a comprehensive catalogue called CHPC2012 (Catalogue of Human Protein Complexes). CHPC2012 achieves a higher coverage for proteins and protein complexes than those individual databases. It is also verified to be a set of complexes with high quality as its co-complex protein associations have a high overlap with protein-protein interactions (PPI) in various existing PPI databases. We demonstrated two distinct applications of CHPC2012, that is, investigating the relationship between protein complexes and drug-related systems and evaluating the quality of predicted protein complexes. In particular, CHPC2012 provides more insights into drug development. For instance, proteins involved in multiple complexes (the overlapping proteins) are potential drug targets; the drug-complex network is utilized to investigate multi-target drugs and drug-drug interactions; and the disease-specific complex-drug networks will provide new clues for drug repositioning. With this up-to-date reference set of human protein complexes, we believe that the CHPC2012 catalogue is able to enhance the studies for protein interactions, protein functions, human diseases, drugs, and related fields of research. CHPC2012 complexes can be downloaded from http://www1.i2r.a-star.edu.sg/xlli/CHPC2012/CHPC2012.htm. © 2013 Wu et al.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161344
ISSN: 19326203
DOI: 10.1371/journal.pone.0053197
Rights: Attribution 4.0 International
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