Absolute Binding Free Energy Calculation and Design of a Subnanomolar Inhibitor of Phosphodiesterase-10
Accurate prediction of absolute protein–ligand binding free energy could considerably enhance the success rate of structure-based drug design but is extremely challenging and time-consuming. Free energy perturbation (FEP) has been proven reliable but is limited to prediction of relative binding free...
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Veröffentlicht in: | Journal of medicinal chemistry 2019-02, Vol.62 (4), p.2099-2111 |
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container_title | Journal of medicinal chemistry |
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creator | Li, Zhe Huang, Yiyou Wu, Yinuo Chen, Jingyi Wu, Deyan Zhan, Chang-Guo Luo, Hai-Bin |
description | Accurate prediction of absolute protein–ligand binding free energy could considerably enhance the success rate of structure-based drug design but is extremely challenging and time-consuming. Free energy perturbation (FEP) has been proven reliable but is limited to prediction of relative binding free energies of similar ligands (with only minor structural differences) in binding with a same drug target in practical drug design applications. Herein, a Gaussian algorithm-enhanced FEP (GA-FEP) protocol has been developed to enhance the FEP simulation performance, enabling to efficiently carry out the FEP simulations on vanishing the whole ligand and, thus, predict the absolute binding free energies (ABFEs). Using the GA-FEP protocol, the FEP simulations for the ABFE calculation (denoted as GA-FEP/ABFE) can achieve a satisfactory accuracy for both structurally similar and diverse ligands in a dataset of more than 100 receptor–ligand systems. Further, our GA-FEP/ABFE-guided lead optimization against phosphodiesterase-10 led to the discovery of a subnanomolar inhibitor (IC50 = 0.87 nM, ∼2000-fold improvement in potency) with cocrystal confirmation. |
doi_str_mv | 10.1021/acs.jmedchem.8b01763 |
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Med. Chem</addtitle><description>Accurate prediction of absolute protein–ligand binding free energy could considerably enhance the success rate of structure-based drug design but is extremely challenging and time-consuming. Free energy perturbation (FEP) has been proven reliable but is limited to prediction of relative binding free energies of similar ligands (with only minor structural differences) in binding with a same drug target in practical drug design applications. Herein, a Gaussian algorithm-enhanced FEP (GA-FEP) protocol has been developed to enhance the FEP simulation performance, enabling to efficiently carry out the FEP simulations on vanishing the whole ligand and, thus, predict the absolute binding free energies (ABFEs). Using the GA-FEP protocol, the FEP simulations for the ABFE calculation (denoted as GA-FEP/ABFE) can achieve a satisfactory accuracy for both structurally similar and diverse ligands in a dataset of more than 100 receptor–ligand systems. Further, our GA-FEP/ABFE-guided lead optimization against phosphodiesterase-10 led to the discovery of a subnanomolar inhibitor (IC50 = 0.87 nM, ∼2000-fold improvement in potency) with cocrystal confirmation.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Binding Sites</subject><subject>Drug Design</subject><subject>Enzyme Inhibitors - chemistry</subject><subject>Enzyme Inhibitors - metabolism</subject><subject>Humans</subject><subject>Ligands</subject><subject>Molecular Dynamics Simulation</subject><subject>Phosphoric Diester Hydrolases - chemistry</subject><subject>Phosphoric Diester Hydrolases - metabolism</subject><subject>Protein Binding</subject><subject>Rats</subject><subject>Thermodynamics</subject><issn>0022-2623</issn><issn>1520-4804</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kDtPHDEQx62IKFxIvkGEXNLsMbb3YZfkgICERKQk9cqP2TujXfuwdwu-fUzuSEk1xf8xMz9CvjFYM-DsUtu8fprQ2R1Oa2mAda34QFas4VDVEuoTsgLgvOItF6fkc85PACAYF5_IqYBWKtE1K7K9MjmOy4z0uw_Ohy29TYj0JmDavtCNHu0y6tnHQHVw9Bqz3wYaB6rpr8UEHeIUR53ofdh54-eYXrWfu5j3u-g85hmTzlgx-EI-DnrM-PU4z8if25vfm7vq4fHH_ebqodKilnNlHWcdulahU03bCtSDrrtGC-asMwaUYshbsJLBgI1URnbYgJNoGlnbEjgjF4fefYrPSzmgn3y2OI46YFxyX-pVraAVqljrg9WmmHPCod8nP-n00jPoXxH3BXH_hrg_Ii6x8-OGxRTtf-iNaTHAwfAvHpcUysPvd_4FDDmL5g</recordid><startdate>20190228</startdate><enddate>20190228</enddate><creator>Li, Zhe</creator><creator>Huang, Yiyou</creator><creator>Wu, Yinuo</creator><creator>Chen, Jingyi</creator><creator>Wu, Deyan</creator><creator>Zhan, Chang-Guo</creator><creator>Luo, Hai-Bin</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>7X8</scope><orcidid>https://orcid.org/0000-0001-5855-8662</orcidid><orcidid>https://orcid.org/0000-0002-2163-0509</orcidid><orcidid>https://orcid.org/0000-0002-4128-7269</orcidid></search><sort><creationdate>20190228</creationdate><title>Absolute Binding Free Energy Calculation and Design of a Subnanomolar Inhibitor of Phosphodiesterase-10</title><author>Li, Zhe ; Huang, Yiyou ; Wu, Yinuo ; Chen, Jingyi ; Wu, Deyan ; Zhan, Chang-Guo ; Luo, Hai-Bin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a348t-cd217ed69ed95663eafa475a31dcdbb0991e260c810fe589b87e50d8eb584c663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Binding Sites</topic><topic>Drug Design</topic><topic>Enzyme Inhibitors - chemistry</topic><topic>Enzyme Inhibitors - metabolism</topic><topic>Humans</topic><topic>Ligands</topic><topic>Molecular Dynamics Simulation</topic><topic>Phosphoric Diester Hydrolases - chemistry</topic><topic>Phosphoric Diester Hydrolases - metabolism</topic><topic>Protein Binding</topic><topic>Rats</topic><topic>Thermodynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Zhe</creatorcontrib><creatorcontrib>Huang, Yiyou</creatorcontrib><creatorcontrib>Wu, Yinuo</creatorcontrib><creatorcontrib>Chen, Jingyi</creatorcontrib><creatorcontrib>Wu, Deyan</creatorcontrib><creatorcontrib>Zhan, Chang-Guo</creatorcontrib><creatorcontrib>Luo, Hai-Bin</creatorcontrib><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><jtitle>Journal of medicinal chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Zhe</au><au>Huang, Yiyou</au><au>Wu, Yinuo</au><au>Chen, Jingyi</au><au>Wu, Deyan</au><au>Zhan, Chang-Guo</au><au>Luo, Hai-Bin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Absolute Binding Free Energy Calculation and Design of a Subnanomolar Inhibitor of Phosphodiesterase-10</atitle><jtitle>Journal of medicinal chemistry</jtitle><addtitle>J. Med. Chem</addtitle><date>2019-02-28</date><risdate>2019</risdate><volume>62</volume><issue>4</issue><spage>2099</spage><epage>2111</epage><pages>2099-2111</pages><issn>0022-2623</issn><eissn>1520-4804</eissn><abstract>Accurate prediction of absolute protein–ligand binding free energy could considerably enhance the success rate of structure-based drug design but is extremely challenging and time-consuming. Free energy perturbation (FEP) has been proven reliable but is limited to prediction of relative binding free energies of similar ligands (with only minor structural differences) in binding with a same drug target in practical drug design applications. Herein, a Gaussian algorithm-enhanced FEP (GA-FEP) protocol has been developed to enhance the FEP simulation performance, enabling to efficiently carry out the FEP simulations on vanishing the whole ligand and, thus, predict the absolute binding free energies (ABFEs). Using the GA-FEP protocol, the FEP simulations for the ABFE calculation (denoted as GA-FEP/ABFE) can achieve a satisfactory accuracy for both structurally similar and diverse ligands in a dataset of more than 100 receptor–ligand systems. Further, our GA-FEP/ABFE-guided lead optimization against phosphodiesterase-10 led to the discovery of a subnanomolar inhibitor (IC50 = 0.87 nM, ∼2000-fold improvement in potency) with cocrystal confirmation.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>30689375</pmid><doi>10.1021/acs.jmedchem.8b01763</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-5855-8662</orcidid><orcidid>https://orcid.org/0000-0002-2163-0509</orcidid><orcidid>https://orcid.org/0000-0002-4128-7269</orcidid></addata></record> |
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subjects | Algorithms Animals Binding Sites Drug Design Enzyme Inhibitors - chemistry Enzyme Inhibitors - metabolism Humans Ligands Molecular Dynamics Simulation Phosphoric Diester Hydrolases - chemistry Phosphoric Diester Hydrolases - metabolism Protein Binding Rats Thermodynamics |
title | Absolute Binding Free Energy Calculation and Design of a Subnanomolar Inhibitor of Phosphodiesterase-10 |
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