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Computationally modeling mammalian succinate dehydrogenase kinetics identifies the origins and primary determinants of ROS production
Succinate dehydrogenase (SDH) is an inner mitochondrial membrane protein complex that links the Krebs cycle to the electron transport system. It can produce significant amounts of superoxide (O2·¯) and hydrogen peroxide (H2O2); however, the precise mechanisms are unknown. This fact hinders the devel...
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Published in: | The Journal of biological chemistry 2020-11, Vol.295 (45), p.15262-15279 |
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description | Succinate dehydrogenase (SDH) is an inner mitochondrial membrane protein complex that links the Krebs cycle to the electron transport system. It can produce significant amounts of superoxide (O2·¯) and hydrogen peroxide (H2O2); however, the precise mechanisms are unknown. This fact hinders the development of next-generation antioxidant therapies targeting mitochondria. To help address this problem, we developed a computational model to analyze and identify the kinetic mechanism of O2·¯ and H2O2 production by SDH. Our model includes the major redox centers in the complex, namely FAD, three iron-sulfur clusters, and a transiently bound semiquinone. Oxidation state transitions involve a one- or two-electron redox reaction, each being thermodynamically constrained. Model parameters were simultaneously fit to many data sets using a variety of succinate oxidation and free radical production data. In the absence of respiratory chain inhibitors, model analysis revealed the 3Fe-4S iron-sulfur cluster as the primary O2·¯ source. However, when the quinone reductase site is inhibited or the quinone pool is highly reduced, O2·¯ is generated primarily by the FAD. In addition, H2O2 production is only significant when the enzyme is fully reduced, and fumarate is absent. Our simulations also reveal that the redox state of the quinone pool is the primary determinant of free radical production by SDH. In this study, we showed the importance of analyzing enzyme kinetics and associated side reactions in a consistent, quantitative, and biophysically detailed manner using a diverse set of experimental data to interpret and explain experimental observations from a unified perspective. |
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It can produce significant amounts of superoxide (O2·¯) and hydrogen peroxide (H2O2); however, the precise mechanisms are unknown. This fact hinders the development of next-generation antioxidant therapies targeting mitochondria. To help address this problem, we developed a computational model to analyze and identify the kinetic mechanism of O2·¯ and H2O2 production by SDH. Our model includes the major redox centers in the complex, namely FAD, three iron-sulfur clusters, and a transiently bound semiquinone. Oxidation state transitions involve a one- or two-electron redox reaction, each being thermodynamically constrained. Model parameters were simultaneously fit to many data sets using a variety of succinate oxidation and free radical production data. In the absence of respiratory chain inhibitors, model analysis revealed the 3Fe-4S iron-sulfur cluster as the primary O2·¯ source. However, when the quinone reductase site is inhibited or the quinone pool is highly reduced, O2·¯ is generated primarily by the FAD. In addition, H2O2 production is only significant when the enzyme is fully reduced, and fumarate is absent. Our simulations also reveal that the redox state of the quinone pool is the primary determinant of free radical production by SDH. In this study, we showed the importance of analyzing enzyme kinetics and associated side reactions in a consistent, quantitative, and biophysically detailed manner using a diverse set of experimental data to interpret and explain experimental observations from a unified perspective.</description><identifier>ISSN: 0021-9258</identifier><identifier>EISSN: 1083-351X</identifier><identifier>DOI: 10.1074/jbc.RA120.014483</identifier><identifier>PMID: 32859750</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Algorithms ; Animals ; Computational Biology ; computer modeling ; enzyme kinetics ; enzyme mechanism ; free radicals ; Guinea Pigs ; hydrogen peroxide ; Kinetics ; mechanistic regulation ; Models, Biological ; oxidative stress ; Reactive Oxygen Species - metabolism ; redox regulation ; succinate dehydrogenase (SDH) ; Succinate Dehydrogenase - metabolism ; superoxide ; superoxide ion ; ubiquinone</subject><ispartof>The Journal of biological chemistry, 2020-11, Vol.295 (45), p.15262-15279</ispartof><rights>2020 © 2020 Manhas et al.</rights><rights>2020 Manhas et al.</rights><rights>2020 Manhas et al. 2020 Manhas et al.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c447t-f1ccda0eb4f8ad2fcc07eb6182bd35e9865b3b546e850a4542f9d6c146bb01b3</citedby><cites>FETCH-LOGICAL-c447t-f1ccda0eb4f8ad2fcc07eb6182bd35e9865b3b546e850a4542f9d6c146bb01b3</cites><orcidid>0000-0002-6988-1964 ; 0000-0001-6424-9938</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650251/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0021925817503609$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,3549,27924,27925,45780,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32859750$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Manhas, Neeraj</creatorcontrib><creatorcontrib>Duong, Quynh V.</creatorcontrib><creatorcontrib>Lee, Pilhwa</creatorcontrib><creatorcontrib>Richardson, Joshua D.</creatorcontrib><creatorcontrib>Robertson, John D.</creatorcontrib><creatorcontrib>Moxley, Michael A.</creatorcontrib><creatorcontrib>Bazil, Jason N.</creatorcontrib><title>Computationally modeling mammalian succinate dehydrogenase kinetics identifies the origins and primary determinants of ROS production</title><title>The Journal of biological chemistry</title><addtitle>J Biol Chem</addtitle><description>Succinate dehydrogenase (SDH) is an inner mitochondrial membrane protein complex that links the Krebs cycle to the electron transport system. It can produce significant amounts of superoxide (O2·¯) and hydrogen peroxide (H2O2); however, the precise mechanisms are unknown. This fact hinders the development of next-generation antioxidant therapies targeting mitochondria. To help address this problem, we developed a computational model to analyze and identify the kinetic mechanism of O2·¯ and H2O2 production by SDH. Our model includes the major redox centers in the complex, namely FAD, three iron-sulfur clusters, and a transiently bound semiquinone. Oxidation state transitions involve a one- or two-electron redox reaction, each being thermodynamically constrained. Model parameters were simultaneously fit to many data sets using a variety of succinate oxidation and free radical production data. In the absence of respiratory chain inhibitors, model analysis revealed the 3Fe-4S iron-sulfur cluster as the primary O2·¯ source. However, when the quinone reductase site is inhibited or the quinone pool is highly reduced, O2·¯ is generated primarily by the FAD. In addition, H2O2 production is only significant when the enzyme is fully reduced, and fumarate is absent. Our simulations also reveal that the redox state of the quinone pool is the primary determinant of free radical production by SDH. In this study, we showed the importance of analyzing enzyme kinetics and associated side reactions in a consistent, quantitative, and biophysically detailed manner using a diverse set of experimental data to interpret and explain experimental observations from a unified perspective.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Computational Biology</subject><subject>computer modeling</subject><subject>enzyme kinetics</subject><subject>enzyme mechanism</subject><subject>free radicals</subject><subject>Guinea Pigs</subject><subject>hydrogen peroxide</subject><subject>Kinetics</subject><subject>mechanistic regulation</subject><subject>Models, Biological</subject><subject>oxidative stress</subject><subject>Reactive Oxygen Species - metabolism</subject><subject>redox regulation</subject><subject>succinate dehydrogenase (SDH)</subject><subject>Succinate Dehydrogenase - metabolism</subject><subject>superoxide</subject><subject>superoxide ion</subject><subject>ubiquinone</subject><issn>0021-9258</issn><issn>1083-351X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kTtvFDEUhS0EIkugp0IuaWaxZ2yPhwIpWoWHFClSSEFn-XFn12HGXmxPpP0B_G8cdomgwI2Le865R_dD6DUla0p69u7O2PXNBW3JmlDGZPcErSiRXdNx-u0pWhHS0mZouTxDL3K-I_WxgT5HZ10r-dBzskI_N3HeL0UXH4OepgOeo4PJhy2e9TzryeuA82KtD7oAdrA7uBS3EHQG_N0HKN5m7B2E4kcPGZcd4Jj81oeMdXB4n_ys06E6C6S5poSScRzxzfXXOotusQ-bX6Jno54yvDr95-j24-Xt5nNzdf3py-biqrGM9aUZqbVOEzBslNq1o7WkByOobI3rOAxScNMZzgRITjTjrB0HJyxlwhhCTXeOPhxj94uZwdnaOulJnTqqqL36dxL8Tm3jveoFJy2nNeDtKSDFHwvkomafLUyTDhCXrFrWSdHLXogqJUepTTHnBOPjGkrUAzxV4anf8NQRXrW8-bveo-EPrSp4fxRAvdG9h6Sy9RAsOJ_AFuWi_3_6L63Pr1M</recordid><startdate>20201106</startdate><enddate>20201106</enddate><creator>Manhas, Neeraj</creator><creator>Duong, Quynh V.</creator><creator>Lee, Pilhwa</creator><creator>Richardson, Joshua D.</creator><creator>Robertson, John D.</creator><creator>Moxley, Michael A.</creator><creator>Bazil, Jason N.</creator><general>Elsevier Inc</general><general>American Society for Biochemistry and Molecular Biology</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-6988-1964</orcidid><orcidid>https://orcid.org/0000-0001-6424-9938</orcidid></search><sort><creationdate>20201106</creationdate><title>Computationally modeling mammalian succinate dehydrogenase kinetics identifies the origins and primary determinants of ROS production</title><author>Manhas, Neeraj ; Duong, Quynh V. ; Lee, Pilhwa ; Richardson, Joshua D. ; Robertson, John D. ; Moxley, Michael A. ; Bazil, Jason N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c447t-f1ccda0eb4f8ad2fcc07eb6182bd35e9865b3b546e850a4542f9d6c146bb01b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Computational Biology</topic><topic>computer modeling</topic><topic>enzyme kinetics</topic><topic>enzyme mechanism</topic><topic>free radicals</topic><topic>Guinea Pigs</topic><topic>hydrogen peroxide</topic><topic>Kinetics</topic><topic>mechanistic regulation</topic><topic>Models, Biological</topic><topic>oxidative stress</topic><topic>Reactive Oxygen Species - metabolism</topic><topic>redox regulation</topic><topic>succinate dehydrogenase (SDH)</topic><topic>Succinate Dehydrogenase - metabolism</topic><topic>superoxide</topic><topic>superoxide ion</topic><topic>ubiquinone</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Manhas, Neeraj</creatorcontrib><creatorcontrib>Duong, Quynh V.</creatorcontrib><creatorcontrib>Lee, Pilhwa</creatorcontrib><creatorcontrib>Richardson, Joshua D.</creatorcontrib><creatorcontrib>Robertson, John D.</creatorcontrib><creatorcontrib>Moxley, Michael A.</creatorcontrib><creatorcontrib>Bazil, Jason N.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The Journal of biological chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Manhas, Neeraj</au><au>Duong, Quynh V.</au><au>Lee, Pilhwa</au><au>Richardson, Joshua D.</au><au>Robertson, John D.</au><au>Moxley, Michael A.</au><au>Bazil, Jason N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computationally modeling mammalian succinate dehydrogenase kinetics identifies the origins and primary determinants of ROS production</atitle><jtitle>The Journal of biological chemistry</jtitle><addtitle>J Biol Chem</addtitle><date>2020-11-06</date><risdate>2020</risdate><volume>295</volume><issue>45</issue><spage>15262</spage><epage>15279</epage><pages>15262-15279</pages><issn>0021-9258</issn><eissn>1083-351X</eissn><abstract>Succinate dehydrogenase (SDH) is an inner mitochondrial membrane protein complex that links the Krebs cycle to the electron transport system. It can produce significant amounts of superoxide (O2·¯) and hydrogen peroxide (H2O2); however, the precise mechanisms are unknown. This fact hinders the development of next-generation antioxidant therapies targeting mitochondria. To help address this problem, we developed a computational model to analyze and identify the kinetic mechanism of O2·¯ and H2O2 production by SDH. Our model includes the major redox centers in the complex, namely FAD, three iron-sulfur clusters, and a transiently bound semiquinone. Oxidation state transitions involve a one- or two-electron redox reaction, each being thermodynamically constrained. Model parameters were simultaneously fit to many data sets using a variety of succinate oxidation and free radical production data. In the absence of respiratory chain inhibitors, model analysis revealed the 3Fe-4S iron-sulfur cluster as the primary O2·¯ source. However, when the quinone reductase site is inhibited or the quinone pool is highly reduced, O2·¯ is generated primarily by the FAD. In addition, H2O2 production is only significant when the enzyme is fully reduced, and fumarate is absent. Our simulations also reveal that the redox state of the quinone pool is the primary determinant of free radical production by SDH. In this study, we showed the importance of analyzing enzyme kinetics and associated side reactions in a consistent, quantitative, and biophysically detailed manner using a diverse set of experimental data to interpret and explain experimental observations from a unified perspective.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32859750</pmid><doi>10.1074/jbc.RA120.014483</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-6988-1964</orcidid><orcidid>https://orcid.org/0000-0001-6424-9938</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Computational Biology computer modeling enzyme kinetics enzyme mechanism free radicals Guinea Pigs hydrogen peroxide Kinetics mechanistic regulation Models, Biological oxidative stress Reactive Oxygen Species - metabolism redox regulation succinate dehydrogenase (SDH) Succinate Dehydrogenase - metabolism superoxide superoxide ion ubiquinone |
title | Computationally modeling mammalian succinate dehydrogenase kinetics identifies the origins and primary determinants of ROS production |
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