CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation
Lipid nanobubbles with different gas cores may integrate the biocompatibility of lipids, powerful physicochemical properties of nanobubbles, and therapeutic effects of gas molecules, which thus promote enormous biomedical applications such as ultrasound molecular imaging, gene/drug delivery, and gas...
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creator | Li, Xiu He, Yuan Wang, Yuxuan Lin, Kaidong Lin, Xubo |
description | Lipid nanobubbles with different gas cores may integrate the biocompatibility of lipids, powerful physicochemical properties of nanobubbles, and therapeutic effects of gas molecules, which thus promote enormous biomedical applications such as ultrasound molecular imaging, gene/drug delivery, and gas therapy. In order for further more precise applications, the exact molecular mechanisms for the interactions between lipid nanobubbles and biological systems should be studied. Molecular dynamics (MD) simulation provides a powerful computational tool for this purpose. However, previous state-of-the-art MD simulations of free gas nanobubble/lipid nanobubble employed the vacuum as their gas cores, which is not suitable for studying the interactions between functional lipid nanobubbles and biological systems and revealing the biological roles of gas molecules. Hence, in this work, we developed and optimized the CHARMM36 all-atom gas parameters for six gases including N2, O2, H2, CO, CO2, and SO2, which accurately reproduced the gas density at different pressures as well as the spontaneous formation of gas nanobubbles. Subsequent applications of these gas parameters for lipid nanobubble simulations also reproduced the self-assembly process of the lipid nanobubble. We further developed a Python script to generate all-atom lipid nanobubble simulation systems, which was proven to be efficient for all-atom MD simulations of lipid nanobubbles and to be able to capture the exact dynamics of gas molecules at the gas–lipid and lipid–water interfaces of the lipid nanobubble. In summary, the all-atom gas models proposed in this work are suitable for simulating free gas nanobubbles and lipid nanobubbles, which are supposed to overcome the shortcomings of previous state-of-the-art MD simulations with the vacuum replacing the gas core and play key roles in revealing the molecular-level interactions between lipid nanobubbles and biological systems. |
doi_str_mv | 10.1021/acs.jcim.4c01027 |
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In order for further more precise applications, the exact molecular mechanisms for the interactions between lipid nanobubbles and biological systems should be studied. Molecular dynamics (MD) simulation provides a powerful computational tool for this purpose. However, previous state-of-the-art MD simulations of free gas nanobubble/lipid nanobubble employed the vacuum as their gas cores, which is not suitable for studying the interactions between functional lipid nanobubbles and biological systems and revealing the biological roles of gas molecules. Hence, in this work, we developed and optimized the CHARMM36 all-atom gas parameters for six gases including N2, O2, H2, CO, CO2, and SO2, which accurately reproduced the gas density at different pressures as well as the spontaneous formation of gas nanobubbles. Subsequent applications of these gas parameters for lipid nanobubble simulations also reproduced the self-assembly process of the lipid nanobubble. We further developed a Python script to generate all-atom lipid nanobubble simulation systems, which was proven to be efficient for all-atom MD simulations of lipid nanobubbles and to be able to capture the exact dynamics of gas molecules at the gas–lipid and lipid–water interfaces of the lipid nanobubble. In summary, the all-atom gas models proposed in this work are suitable for simulating free gas nanobubbles and lipid nanobubbles, which are supposed to overcome the shortcomings of previous state-of-the-art MD simulations with the vacuum replacing the gas core and play key roles in revealing the molecular-level interactions between lipid nanobubbles and biological systems.</description><identifier>ISSN: 1549-9596</identifier><identifier>ISSN: 1549-960X</identifier><identifier>EISSN: 1549-960X</identifier><identifier>DOI: 10.1021/acs.jcim.4c01027</identifier><identifier>PMID: 39262130</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Biocompatibility ; Biomedical materials ; Carbon dioxide ; Computational Chemistry ; Gas density ; Gas formation ; Gases ; Gases - chemistry ; Lipids ; Lipids - chemistry ; Molecular dynamics ; Molecular Dynamics Simulation ; Nanostructures - chemistry ; Parameters ; Self-assembly ; Simulation ; Software ; Sulfur dioxide</subject><ispartof>Journal of chemical information and modeling, 2024-10, Vol.64 (19), p.7503-7512</ispartof><rights>2024 American Chemical Society</rights><rights>Copyright American Chemical Society Oct 14, 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a247t-85fb7deb6a3eeb3697470ed12fd4288de96c5ec06822d6fc8ea457ee091f00a33</cites><orcidid>0000-0002-4417-3582</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c01027$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jcim.4c01027$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>315,781,785,2766,27078,27926,27927,56740,56790</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39262130$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Xiu</creatorcontrib><creatorcontrib>He, Yuan</creatorcontrib><creatorcontrib>Wang, Yuxuan</creatorcontrib><creatorcontrib>Lin, Kaidong</creatorcontrib><creatorcontrib>Lin, Xubo</creatorcontrib><title>CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation</title><title>Journal of chemical information and modeling</title><addtitle>J. Chem. Inf. Model</addtitle><description>Lipid nanobubbles with different gas cores may integrate the biocompatibility of lipids, powerful physicochemical properties of nanobubbles, and therapeutic effects of gas molecules, which thus promote enormous biomedical applications such as ultrasound molecular imaging, gene/drug delivery, and gas therapy. In order for further more precise applications, the exact molecular mechanisms for the interactions between lipid nanobubbles and biological systems should be studied. Molecular dynamics (MD) simulation provides a powerful computational tool for this purpose. However, previous state-of-the-art MD simulations of free gas nanobubble/lipid nanobubble employed the vacuum as their gas cores, which is not suitable for studying the interactions between functional lipid nanobubbles and biological systems and revealing the biological roles of gas molecules. Hence, in this work, we developed and optimized the CHARMM36 all-atom gas parameters for six gases including N2, O2, H2, CO, CO2, and SO2, which accurately reproduced the gas density at different pressures as well as the spontaneous formation of gas nanobubbles. Subsequent applications of these gas parameters for lipid nanobubble simulations also reproduced the self-assembly process of the lipid nanobubble. We further developed a Python script to generate all-atom lipid nanobubble simulation systems, which was proven to be efficient for all-atom MD simulations of lipid nanobubbles and to be able to capture the exact dynamics of gas molecules at the gas–lipid and lipid–water interfaces of the lipid nanobubble. In summary, the all-atom gas models proposed in this work are suitable for simulating free gas nanobubbles and lipid nanobubbles, which are supposed to overcome the shortcomings of previous state-of-the-art MD simulations with the vacuum replacing the gas core and play key roles in revealing the molecular-level interactions between lipid nanobubbles and biological systems.</description><subject>Biocompatibility</subject><subject>Biomedical materials</subject><subject>Carbon dioxide</subject><subject>Computational Chemistry</subject><subject>Gas density</subject><subject>Gas formation</subject><subject>Gases</subject><subject>Gases - chemistry</subject><subject>Lipids</subject><subject>Lipids - chemistry</subject><subject>Molecular dynamics</subject><subject>Molecular Dynamics Simulation</subject><subject>Nanostructures - chemistry</subject><subject>Parameters</subject><subject>Self-assembly</subject><subject>Simulation</subject><subject>Software</subject><subject>Sulfur dioxide</subject><issn>1549-9596</issn><issn>1549-960X</issn><issn>1549-960X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kE1Lw0AQhhdRrFbvniTgxYOpsx_ZZPEUirZCq-AHeFs22QmkJNmaTQ7-e1PbehA87bA87zvDQ8gFhQkFRm9N7iervKwnIofhIz4gJzQSKlQSPg73c6TkiJx6vwLgXEl2TEZcMckohxNyN52nL8sll0FaVWHauTqYGR8sncUqKFwbLMp1aYMn07isz7IKg9ey7ivTla45I0eFqTye794xeX-4f5vOw8Xz7HGaLkLDRNyFSVRkscVMGo6YcaliEQNaygorWJJYVDKPMAeZMGZlkSdoRBQjgqIFgOF8TK63vevWffboO12XPseqMg263mtOgQuhEqADevUHXbm-bYbrBoqBjAAiMVCwpfLWed9ioddtWZv2S1PQG7F6EKs3YvVO7BC53BX3WY32N7A3OQA3W-Anul_6b983XbOBWA</recordid><startdate>20241014</startdate><enddate>20241014</enddate><creator>Li, Xiu</creator><creator>He, Yuan</creator><creator>Wang, Yuxuan</creator><creator>Lin, Kaidong</creator><creator>Lin, Xubo</creator><general>American Chemical Society</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>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4417-3582</orcidid></search><sort><creationdate>20241014</creationdate><title>CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation</title><author>Li, Xiu ; He, Yuan ; Wang, Yuxuan ; Lin, Kaidong ; Lin, Xubo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a247t-85fb7deb6a3eeb3697470ed12fd4288de96c5ec06822d6fc8ea457ee091f00a33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Biocompatibility</topic><topic>Biomedical materials</topic><topic>Carbon dioxide</topic><topic>Computational Chemistry</topic><topic>Gas density</topic><topic>Gas formation</topic><topic>Gases</topic><topic>Gases - chemistry</topic><topic>Lipids</topic><topic>Lipids - chemistry</topic><topic>Molecular dynamics</topic><topic>Molecular Dynamics Simulation</topic><topic>Nanostructures - chemistry</topic><topic>Parameters</topic><topic>Self-assembly</topic><topic>Simulation</topic><topic>Software</topic><topic>Sulfur dioxide</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Xiu</creatorcontrib><creatorcontrib>He, Yuan</creatorcontrib><creatorcontrib>Wang, Yuxuan</creatorcontrib><creatorcontrib>Lin, Kaidong</creatorcontrib><creatorcontrib>Lin, Xubo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of chemical information and modeling</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Xiu</au><au>He, Yuan</au><au>Wang, Yuxuan</au><au>Lin, Kaidong</au><au>Lin, Xubo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation</atitle><jtitle>Journal of chemical information and modeling</jtitle><addtitle>J. Chem. Inf. Model</addtitle><date>2024-10-14</date><risdate>2024</risdate><volume>64</volume><issue>19</issue><spage>7503</spage><epage>7512</epage><pages>7503-7512</pages><issn>1549-9596</issn><issn>1549-960X</issn><eissn>1549-960X</eissn><abstract>Lipid nanobubbles with different gas cores may integrate the biocompatibility of lipids, powerful physicochemical properties of nanobubbles, and therapeutic effects of gas molecules, which thus promote enormous biomedical applications such as ultrasound molecular imaging, gene/drug delivery, and gas therapy. In order for further more precise applications, the exact molecular mechanisms for the interactions between lipid nanobubbles and biological systems should be studied. Molecular dynamics (MD) simulation provides a powerful computational tool for this purpose. However, previous state-of-the-art MD simulations of free gas nanobubble/lipid nanobubble employed the vacuum as their gas cores, which is not suitable for studying the interactions between functional lipid nanobubbles and biological systems and revealing the biological roles of gas molecules. Hence, in this work, we developed and optimized the CHARMM36 all-atom gas parameters for six gases including N2, O2, H2, CO, CO2, and SO2, which accurately reproduced the gas density at different pressures as well as the spontaneous formation of gas nanobubbles. Subsequent applications of these gas parameters for lipid nanobubble simulations also reproduced the self-assembly process of the lipid nanobubble. We further developed a Python script to generate all-atom lipid nanobubble simulation systems, which was proven to be efficient for all-atom MD simulations of lipid nanobubbles and to be able to capture the exact dynamics of gas molecules at the gas–lipid and lipid–water interfaces of the lipid nanobubble. In summary, the all-atom gas models proposed in this work are suitable for simulating free gas nanobubbles and lipid nanobubbles, which are supposed to overcome the shortcomings of previous state-of-the-art MD simulations with the vacuum replacing the gas core and play key roles in revealing the molecular-level interactions between lipid nanobubbles and biological systems.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>39262130</pmid><doi>10.1021/acs.jcim.4c01027</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-4417-3582</orcidid></addata></record> |
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subjects | Biocompatibility Biomedical materials Carbon dioxide Computational Chemistry Gas density Gas formation Gases Gases - chemistry Lipids Lipids - chemistry Molecular dynamics Molecular Dynamics Simulation Nanostructures - chemistry Parameters Self-assembly Simulation Software Sulfur dioxide |
title | CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation |
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