Editing Proteomics (section)

==Practical applications==

===New drug discovery===
One major development to come from the study of human genes and proteins has been the identification of potential new drugs for the treatment of disease. This relies on [[genome]] and [[proteome]] information to identify proteins associated with a disease, which computer software can then use as targets for new drugs. For example, if a certain protein is implicated in a disease, its 3D structure provides the information to design drugs to interfere with the action of the protein. A molecule that fits the active site of an enzyme, but cannot be released by the enzyme, inactivates the enzyme. This is the basis of new drug-discovery tools, which aim to find new drugs to inactivate proteins involved in disease. As genetic differences among individuals are found, researchers expect to use these techniques to develop personalized drugs that are more effective for the individual.<ref name="Vaidyanathan12">{{cite journal | vauthors = Vaidyanathan G | title = Redefining clinical trials: the age of personalized medicine | journal = Cell | volume = 148 | issue = 6 | pages = 1079–1080 | date = March 2012 | pmid = 22424218 | doi = 10.1016/j.cell.2012.02.041 | doi-access = free }}</ref>

Proteomics is also used to reveal complex plant-insect interactions that help identify candidate genes involved in the defensive response of plants to herbivory.<ref>{{cite journal | vauthors = Rakwal R, Komatsu S | title = Role of jasmonate in the rice (Oryza sativa L.) self-defense mechanism using proteome analysis | journal = Electrophoresis | volume = 21 | issue = 12 | pages = 2492–2500 | date = July 2000 | pmid = 10939463 | doi = 10.1002/1522-2683(20000701)21:12<2492::AID-ELPS2492>3.0.CO;2-2 | s2cid = 24979515 }}</ref><ref>{{cite journal | vauthors = Wu J, Baldwin IT | title = New insights into plant responses to the attack from insect herbivores | journal = Annual Review of Genetics | volume = 44 | pages = 1–24 | year = 2010 | pmid = 20649414 | doi = 10.1146/annurev-genet-102209-163500 }}</ref><ref>{{cite journal | vauthors = Sangha JS, Chen YH, Kaur J, Khan W, Abduljaleel Z, Alanazi MS, Mills A, Adalla CB, Bennett J, Prithiviraj B, Jahn GC, Leung H | display-authors = 6 | title = Proteome Analysis of Rice (Oryza sativa L.) Mutants Reveals Differentially Induced Proteins during Brown Planthopper (Nilaparvata lugens) Infestation | journal = International Journal of Molecular Sciences | volume = 14 | issue = 2 | pages = 3921–3945 | date = February 2013 | pmid = 23434671 | pmc = 3588078 | doi = 10.3390/ijms14023921 | doi-access = free }}</ref>

A branch of proteomics called [[chemoproteomics]] provides numerous tools and techniques to detect protein targets of drugs.<ref>{{cite journal | vauthors = Moellering RE, Cravatt BF | title = How chemoproteomics can enable drug discovery and development | journal = Chemistry & Biology | volume = 19 | issue = 1 | pages = 11–22 | date = January 2012 | pmid = 22284350 | pmc = 3312051 | doi = 10.1016/j.chembiol.2012.01.001 }}</ref>

===Interaction proteomics and protein networks===
Interaction proteomics is the analysis of protein interactions from scales of binary interactions to proteome- or network-wide.  Most proteins function via [[protein–protein interaction]]s, and one goal of interaction proteomics is to [[Methods to investigate protein-protein interactions|identify binary protein interactions]], [[multiprotein complex|protein complexes]], and [[interactome]]s.

Several methods are available to [[Methods to investigate protein-protein interactions|probe protein–protein interactions]]. While the most traditional method is yeast [[Two-hybrid screening|two-hybrid analysis]], a powerful emerging method is [[co-immunoprecipitation|affinity purification]] followed by [[protein mass spectrometry]] using [[protein tag|tagged protein baits]]. Other methods include [[surface plasmon resonance]] (SPR),<ref>{{cite book | vauthors = de Mol NJ | chapter = Surface Plasmon Resonance for Proteomics | title = Chemical Genomics and Proteomics | series = Methods in Molecular Biology | volume = 800 | pages = 33–53 | date = 2012 | pmid = 21964781 | doi = 10.1007/978-1-61779-349-3_4 | isbn = 978-1-61779-348-6 }}</ref><ref>{{cite journal | vauthors = Visser NF, Heck AJ | title = Surface plasmon resonance mass spectrometry in proteomics | journal = Expert Review of Proteomics | volume = 5 | issue = 3 | pages = 425–433 | date = June 2008 | pmid = 18532910 | doi = 10.1586/14789450.5.3.425 | s2cid = 11772983 }}</ref> [[protein microarray]]s, [[dual polarisation interferometry]], [[microscale thermophoresis]], [[kinetic exclusion assay]], and experimental methods such as [[phage display]] and ''in silico'' computational methods.

Knowledge of protein-protein interactions is especially useful in regard to [[biological network]]s and [[systems biology]], for example in [[cell signaling]] cascades and [[gene regulatory network]]s (GRNs, where knowledge of [[transcription factor|protein-DNA interactions]] is also informative). Proteome-wide analysis of protein interactions, and integration of these interaction patterns into larger [[biological network]]s, is crucial towards understanding [[#Proteomics for systems biology|systems-level biology]].<ref name="Bensimon_2012">{{cite journal | vauthors = Bensimon A, Heck AJ, Aebersold R | title = Mass spectrometry-based proteomics and network biology | journal = Annual Review of Biochemistry | volume = 81 | issue = 1 | pages = 379–405 | date = 7 July 2012 | pmid = 22439968 | doi = 10.1146/annurev-biochem-072909-100424 }}</ref><ref name="Sabidó_2012">{{cite journal | vauthors = Sabidó E, Selevsek N, Aebersold R | title = Mass spectrometry-based proteomics for systems biology | journal = Current Opinion in Biotechnology | volume = 23 | issue = 4 | pages = 591–597 | date = August 2012 | pmid = 22169889 | doi = 10.1016/j.copbio.2011.11.014 }}</ref>

===Expression proteomics===
Expression proteomics includes the analysis of [[Protein expression (biotechnology)|protein expression]] at a larger scale. It helps identify main proteins in a particular sample, and those proteins differentially expressed in related samples—such as diseased vs. healthy tissue. If a protein is found only in a diseased sample then it can be a useful drug target or diagnostic marker. Proteins with the same or similar expression profiles may also be functionally related. There are technologies such as 2D-PAGE and [[mass spectrometry]] that are used in expression proteomics.<ref name="What is Proteomics?"/>

===Biomarkers===
{{Main|Biomarker}}
The [[National Institutes of Health]] has defined a biomarker as "a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention."<ref>{{cite journal | vauthors = Strimbu K, Tavel JA | title = What are biomarkers? | journal = Current Opinion in HIV and AIDS | volume = 5 | issue = 6 | pages = 463–466 | date = November 2010 | pmid = 20978388 | pmc = 3078627 | doi = 10.1097/COH.0b013e32833ed177 }}</ref><ref>{{cite journal | title = Biomarkers and surrogate endpoints: preferred definitions and conceptual framework | journal = Clinical Pharmacology and Therapeutics | volume = 69 | issue = 3 | pages = 89–95 | date = March 2001 | pmid = 11240971 | doi = 10.1067/mcp.2001.113989 | s2cid = 288484 | author1 = Biomarkers Definitions Working Group }}</ref>

Understanding the proteome, the structure and function of each protein and the complexities of protein–protein interactions are critical for developing the most effective diagnostic techniques and disease treatments in the future. For example, proteomics is highly useful in the identification of candidate biomarkers (proteins in body fluids that are of value for diagnosis), identification of the bacterial antigens that are targeted by the immune response, and identification of possible immunohistochemistry markers of infectious or neoplastic diseases.<ref name=Ceciliani2014>{{cite journal | vauthors = Ceciliani F, Eckersall D, Burchmore R, Lecchi C | title = Proteomics in veterinary medicine: applications and trends in disease pathogenesis and diagnostics | journal = Veterinary Pathology | volume = 51 | issue = 2 | pages = 351–362 | date = March 2014 | pmid = 24045891 | doi = 10.1177/0300985813502819 | hdl-access = free | s2cid = 25693263 | hdl = 2434/226049 }}</ref>

An interesting use of proteomics is using specific protein biomarkers to diagnose disease. A number of techniques allow to test for proteins produced during a particular disease, which helps to diagnose the disease quickly. Techniques include [[western blot]], [[immunohistochemical staining]], [[enzyme linked immunosorbent assay]] (ELISA) or [[mass spectrometry]].<ref name=Klopfleisch1>{{cite journal | vauthors = Klopfleisch R, Klose P, Weise C, Bondzio A, Multhaup G, Einspanier R, Gruber AD | title = Proteome of metastatic canine mammary carcinomas: similarities to and differences from human breast cancer | journal = Journal of Proteome Research | volume = 9 | issue = 12 | pages = 6380–6391 | date = December 2010 | pmid = 20932060 | doi = 10.1021/pr100671c }}</ref><ref>{{cite journal | vauthors = Klopfleisch R, Gruber AD | title = Increased expression of BRCA2 and RAD51 in lymph node metastases of canine mammary adenocarcinomas | journal = Veterinary Pathology | volume = 46 | issue = 3 | pages = 416–422 | date = May 2009 | pmid = 19176491 | doi = 10.1354/vp.08-VP-0212-K-FL | s2cid = 11583190 | doi-access = free }}</ref> [[Secretomics]], a subfield of proteomics that studies [[secretory protein|secreted proteins]] and secretion pathways using proteomic approaches, has recently emerged as an important tool for the discovery of biomarkers of disease.<ref name=pmid17425459>{{cite journal | vauthors = Hathout Y | title = Approaches to the study of the cell secretome | journal = Expert Review of Proteomics | volume = 4 | issue = 2 | pages = 239–248 | date = April 2007 | pmid = 17425459 | doi = 10.1586/14789450.4.2.239 | s2cid = 26169223 }}</ref>

===Proteogenomics===
In [[proteogenomics]], proteomic technologies such as [[mass spectrometry]] are used for improving [[gene annotation]]s. Parallel analysis of the genome and the proteome facilitates discovery of post-translational modifications and proteolytic events,<ref name="Gupta07">{{cite journal | vauthors = Gupta N, Tanner S, Jaitly N, Adkins JN, Lipton M, Edwards R, Romine M, Osterman A, Bafna V, Smith RD, Pevzner PA | display-authors = 6 | title = Whole proteome analysis of post-translational modifications: applications of mass-spectrometry for proteogenomic annotation | journal = Genome Research | volume = 17 | issue = 9 | pages = 1362–1377 | date = September 2007 | pmid = 17690205 | pmc = 1950905 | doi = 10.1101/gr.6427907 }}</ref> especially when comparing multiple species (comparative proteogenomics).<ref name="Gupta08">{{cite journal | vauthors = Gupta N, Benhamida J, Bhargava V, Goodman D, Kain E, Kerman I, Nguyen N, Ollikainen N, Rodriguez J, Wang J, Lipton MS, Romine M, Bafna V, Smith RD, Pevzner PA | display-authors = 6 | title = Comparative proteogenomics: combining mass spectrometry and comparative genomics to analyze multiple genomes | journal = Genome Research | volume = 18 | issue = 7 | pages = 1133–1142 | date = July 2008 | pmid = 18426904 | pmc = 2493402 | doi = 10.1101/gr.074344.107 }}</ref>

===Structural proteomics===
Structural proteomics includes the analysis of protein structures at large-scale. It compares protein structures and helps identify functions of newly discovered genes. The structural analysis also helps to understand that where drugs bind to proteins and also shows where proteins interact with each other. This understanding is achieved using different technologies such as X-ray crystallography and NMR spectroscopy.<ref name="What is Proteomics?">{{cite web |url=http://www.proteomic.org/html/proteomics_.html |title=What is Proteomics? |publisher=ProteoConsult}}{{MEDRS|date=November 2013}}</ref>