Influences of excluded volume of molecules on signaling processes on the biomembrane
We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of t...
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description | We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor. |
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We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0062218</identifier><identifier>PMID: 23658714</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Biology ; Cell Membrane - metabolism ; Cellular signal transduction ; Clusters ; Computer Science ; Computer simulation ; Cytoplasm ; Diffusion ; Epidermal growth factor ; Kinases ; Life sciences ; Membranes ; Models, Biological ; Molecular chains ; Physics ; Protein binding ; Proteins ; Receptors ; Receptors, G-Protein-Coupled - metabolism ; Signal processing ; Signal Transduction ; Signaling ; Stochastic models ; Stochastic Processes ; Stochasticity ; Transduction ; Two dimensional models</subject><ispartof>PloS one, 2013-05, Vol.8 (5), p.e62218-e62218</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Fujii et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Fujii et al 2013 Fujii et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c758t-378e76fc65516576e67ade1e17780a1a0b21c959ddc8206a476098d0ebcabe523</citedby><cites>FETCH-LOGICAL-c758t-378e76fc65516576e67ade1e17780a1a0b21c959ddc8206a476098d0ebcabe523</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642174/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642174/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23864,27922,27923,53789,53791,79370,79371</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23658714$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Reisert, Johannes</contributor><creatorcontrib>Fujii, Masashi</creatorcontrib><creatorcontrib>Nishimori, Hiraku</creatorcontrib><creatorcontrib>Awazu, Akinori</creatorcontrib><title>Influences of excluded volume of molecules on signaling processes on the biomembrane</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.</description><subject>Biology</subject><subject>Cell Membrane - metabolism</subject><subject>Cellular signal transduction</subject><subject>Clusters</subject><subject>Computer Science</subject><subject>Computer simulation</subject><subject>Cytoplasm</subject><subject>Diffusion</subject><subject>Epidermal growth factor</subject><subject>Kinases</subject><subject>Life sciences</subject><subject>Membranes</subject><subject>Models, Biological</subject><subject>Molecular chains</subject><subject>Physics</subject><subject>Protein binding</subject><subject>Proteins</subject><subject>Receptors</subject><subject>Receptors, G-Protein-Coupled - metabolism</subject><subject>Signal processing</subject><subject>Signal Transduction</subject><subject>Signaling</subject><subject>Stochastic models</subject><subject>Stochastic Processes</subject><subject>Stochasticity</subject><subject>Transduction</subject><subject>Two dimensional models</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl2L1DAUhoso7rr6D0QLgujFjPlOeiMsix8DCwu6ehvS9LSTIW3Gpl3Wf2_qdJep7IX0IuXked-TnLxZ9hKjNaYSf9iFse-MX-9DB2uEBCFYPcpOcUHJShBEHx_9n2TPYtwhxKkS4ml2QqjgSmJ2ml1vutqP0FmIeahzuLV-rKDKb4IfW5hKbfBgRz_td3l0Terpuibf9yFp4qE8bCEvXWihLXvTwfPsSW18hBfzepb9-Pzp-uLr6vLqy-bi_HJlJVfDikoFUtRWcI4FlwKENBVgwFIqZLBBJcG24EVVWUWQMEwKVKgKQWlNCZzQs-z1wXfvQ9TzQKLGlClMUSFlIjYHogpmp_e9a03_Wwfj9N9C6Btt-sFZD5pYxVVFDHBaMUhNCimEqaWUJWIFTF4f525j2UJloRt64xemy53ObXUTbjQVjGDJksG72aAPv0aIg25dtOB9GlkYp3NzhDkuGE7om3_Qh283U41JF3BdHVJfO5nqcyYVY4SgIlHrB6j0VdA6m9JTu1RfCN4vBIkZ4HZozBij3nz_9v_s1c8l-_aI3YLxwzamnA0udHEJsgNo-xBjD_X9kDHSU_jvpqGn8Os5_En26viB7kV3aad_AKBI_qU</recordid><startdate>20130502</startdate><enddate>20130502</enddate><creator>Fujii, Masashi</creator><creator>Nishimori, Hiraku</creator><creator>Awazu, Akinori</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20130502</creationdate><title>Influences of excluded volume of molecules on signaling processes on the biomembrane</title><author>Fujii, Masashi ; Nishimori, Hiraku ; Awazu, Akinori</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c758t-378e76fc65516576e67ade1e17780a1a0b21c959ddc8206a476098d0ebcabe523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Biology</topic><topic>Cell Membrane - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fujii, Masashi</au><au>Nishimori, Hiraku</au><au>Awazu, Akinori</au><au>Reisert, Johannes</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influences of excluded volume of molecules on signaling processes on the biomembrane</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-05-02</date><risdate>2013</risdate><volume>8</volume><issue>5</issue><spage>e62218</spage><epage>e62218</epage><pages>e62218-e62218</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23658714</pmid><doi>10.1371/journal.pone.0062218</doi><tpages>e62218</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biology Cell Membrane - metabolism Cellular signal transduction Clusters Computer Science Computer simulation Cytoplasm Diffusion Epidermal growth factor Kinases Life sciences Membranes Models, Biological Molecular chains Physics Protein binding Proteins Receptors Receptors, G-Protein-Coupled - metabolism Signal processing Signal Transduction Signaling Stochastic models Stochastic Processes Stochasticity Transduction Two dimensional models |
title | Influences of excluded volume of molecules on signaling processes on the biomembrane |
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