{"title":"兼职蛋白质-一种系统化概念的方法。","authors":"Maria Krantz, Edda Klipp","doi":"10.3233/ISB-190473","DOIUrl":null,"url":null,"abstract":"<p><p>Moonlighting refers to a protein with at least two unrelated, mechanistically different functions. As a concept, moonlighting describes a large and diverse group of proteins which have been discovered in a multitude of organisms. As of today, a systematized view on these proteins is missing. Here, we propose a classification of moonlighting proteins by two classifiers. We use the function of the protein as a first classifier: activating - activating (Type I), activating - inhibiting (Type II), inhibiting - activating (Type III) and inhibiting - inhibiting (Type IV). To further specify the type of moonlighting protein, we used a second classifier based on the character of the factor that switches the function of the protein: external factor affecting the protein (Type A), change in the first pathway (Type B), change in the second pathway (Type C), equal competition between both pathways (Type D). Using a small two-pathway model we simulated these types of moonlighting proteins to elucidate possible behaviors of the types of moonlighting proteins. We find that, using the results of our simulations, we can classify the behavior of the moonlighting types into Blinker, Splitter andSwitch.</p>","PeriodicalId":39379,"journal":{"name":"In Silico Biology","volume":"14 1-2","pages":"71-83"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/ISB-190473","citationCount":"5","resultStr":"{\"title\":\"Moonlighting proteins - an approach to systematize the concept.\",\"authors\":\"Maria Krantz, Edda Klipp\",\"doi\":\"10.3233/ISB-190473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Moonlighting refers to a protein with at least two unrelated, mechanistically different functions. As a concept, moonlighting describes a large and diverse group of proteins which have been discovered in a multitude of organisms. As of today, a systematized view on these proteins is missing. Here, we propose a classification of moonlighting proteins by two classifiers. We use the function of the protein as a first classifier: activating - activating (Type I), activating - inhibiting (Type II), inhibiting - activating (Type III) and inhibiting - inhibiting (Type IV). To further specify the type of moonlighting protein, we used a second classifier based on the character of the factor that switches the function of the protein: external factor affecting the protein (Type A), change in the first pathway (Type B), change in the second pathway (Type C), equal competition between both pathways (Type D). Using a small two-pathway model we simulated these types of moonlighting proteins to elucidate possible behaviors of the types of moonlighting proteins. We find that, using the results of our simulations, we can classify the behavior of the moonlighting types into Blinker, Splitter andSwitch.</p>\",\"PeriodicalId\":39379,\"journal\":{\"name\":\"In Silico Biology\",\"volume\":\"14 1-2\",\"pages\":\"71-83\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3233/ISB-190473\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"In Silico Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/ISB-190473\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"In Silico Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/ISB-190473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Moonlighting proteins - an approach to systematize the concept.
Moonlighting refers to a protein with at least two unrelated, mechanistically different functions. As a concept, moonlighting describes a large and diverse group of proteins which have been discovered in a multitude of organisms. As of today, a systematized view on these proteins is missing. Here, we propose a classification of moonlighting proteins by two classifiers. We use the function of the protein as a first classifier: activating - activating (Type I), activating - inhibiting (Type II), inhibiting - activating (Type III) and inhibiting - inhibiting (Type IV). To further specify the type of moonlighting protein, we used a second classifier based on the character of the factor that switches the function of the protein: external factor affecting the protein (Type A), change in the first pathway (Type B), change in the second pathway (Type C), equal competition between both pathways (Type D). Using a small two-pathway model we simulated these types of moonlighting proteins to elucidate possible behaviors of the types of moonlighting proteins. We find that, using the results of our simulations, we can classify the behavior of the moonlighting types into Blinker, Splitter andSwitch.
In Silico BiologyComputer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍:
The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.