Prediction of aqueous solubility of drugs and pesticides with COSMO-RS
The COSMO‐RS method, originally developed for the prediction of liquid–liquid and liquid–vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO‐RS is n...
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Veröffentlicht in: | Journal of computational chemistry 2002-01, Vol.23 (2), p.275-281 |
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creator | Klamt, Andreas Eckert, Frank Hornig, Martin Beck, Michael E. Bürger, Thorsten |
description | The COSMO‐RS method, originally developed for the prediction of liquid–liquid and liquid–vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO‐RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug‐like compounds. On these data an rms deviation of 0.66 log‐units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log‐units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO‐RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO‐RSol. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 275–281, 2002 |
doi_str_mv | 10.1002/jcc.1168 |
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By this addition, COSMO‐RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug‐like compounds. On these data an rms deviation of 0.66 log‐units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log‐units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO‐RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO‐RSol. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 275–281, 2002</description><identifier>ISSN: 0192-8651</identifier><identifier>EISSN: 1096-987X</identifier><identifier>DOI: 10.1002/jcc.1168</identifier><identifier>PMID: 11924739</identifier><language>eng</language><publisher>New York: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>ADME ; aqueous solubility ; Artificial Intelligence ; COSMO-RS ; drugs ; Models, Chemical ; pesticides ; Pesticides - chemistry ; Pharmaceutical Preparations - chemistry ; prediction ; Solubility ; Thermodynamics ; Water - chemistry</subject><ispartof>Journal of computational chemistry, 2002-01, Vol.23 (2), p.275-281</ispartof><rights>Copyright © 2002 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3898-e02fefd1ff8f1e4a1ec3bda9f0204c3639519796ebf74b265e34f0475876f3c3</citedby><cites>FETCH-LOGICAL-c3898-e02fefd1ff8f1e4a1ec3bda9f0204c3639519796ebf74b265e34f0475876f3c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjcc.1168$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjcc.1168$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11924739$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Klamt, Andreas</creatorcontrib><creatorcontrib>Eckert, Frank</creatorcontrib><creatorcontrib>Hornig, Martin</creatorcontrib><creatorcontrib>Beck, Michael E.</creatorcontrib><creatorcontrib>Bürger, Thorsten</creatorcontrib><title>Prediction of aqueous solubility of drugs and pesticides with COSMO-RS</title><title>Journal of computational chemistry</title><addtitle>J. Comput. Chem</addtitle><description>The COSMO‐RS method, originally developed for the prediction of liquid–liquid and liquid–vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO‐RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug‐like compounds. On these data an rms deviation of 0.66 log‐units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log‐units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO‐RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO‐RSol. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 275–281, 2002</description><subject>ADME</subject><subject>aqueous solubility</subject><subject>Artificial Intelligence</subject><subject>COSMO-RS</subject><subject>drugs</subject><subject>Models, Chemical</subject><subject>pesticides</subject><subject>Pesticides - chemistry</subject><subject>Pharmaceutical Preparations - chemistry</subject><subject>prediction</subject><subject>Solubility</subject><subject>Thermodynamics</subject><subject>Water - chemistry</subject><issn>0192-8651</issn><issn>1096-987X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp10EFPwjAUB_DGaATRxE9gdvQy7Fu3dj2aRVCDQIBE4qXpulaLg-G6Bfn2jrDoydNL3vvln7w_QteA-4BxcLdSqg9A4xPUBcypz2O2PEVdDDzwYxpBB104t8IYk4iG56gDzSFkhHfRYFrqzKrKFhuvMJ78qnVRO88VeZ3a3Fb7wzYr63fnyU3mbbWrrLKZdt7OVh9eMpm_TPzZ_BKdGZk7fdXOHloMHhbJoz-aDJ-S-5GvSMxjX-PAaJOBMbEBHUrQiqSZ5AYHOFSEEh4BZ5zq1LAwDWikSWhwyKKYUUMU6aHbY6wqC-dKbcS2tGtZ7gVgcWhCNE2IQxMNvTnSbZ2udfYH29cb4B_BzuZ6_2-QeE6SNrD11lX6-9fL8lNQRlgkXsdD8TYeLQFmU8HJD52Pdkg</recordid><startdate>20020130</startdate><enddate>20020130</enddate><creator>Klamt, Andreas</creator><creator>Eckert, Frank</creator><creator>Hornig, Martin</creator><creator>Beck, Michael E.</creator><creator>Bürger, Thorsten</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>BSCLL</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></search><sort><creationdate>20020130</creationdate><title>Prediction of aqueous solubility of drugs and pesticides with COSMO-RS</title><author>Klamt, Andreas ; Eckert, Frank ; Hornig, Martin ; Beck, Michael E. ; Bürger, Thorsten</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3898-e02fefd1ff8f1e4a1ec3bda9f0204c3639519796ebf74b265e34f0475876f3c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>ADME</topic><topic>aqueous solubility</topic><topic>Artificial Intelligence</topic><topic>COSMO-RS</topic><topic>drugs</topic><topic>Models, Chemical</topic><topic>pesticides</topic><topic>Pesticides - chemistry</topic><topic>Pharmaceutical Preparations - chemistry</topic><topic>prediction</topic><topic>Solubility</topic><topic>Thermodynamics</topic><topic>Water - chemistry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Klamt, Andreas</creatorcontrib><creatorcontrib>Eckert, Frank</creatorcontrib><creatorcontrib>Hornig, Martin</creatorcontrib><creatorcontrib>Beck, Michael E.</creatorcontrib><creatorcontrib>Bürger, Thorsten</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><jtitle>Journal of computational chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Klamt, Andreas</au><au>Eckert, Frank</au><au>Hornig, Martin</au><au>Beck, Michael E.</au><au>Bürger, Thorsten</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of aqueous solubility of drugs and pesticides with COSMO-RS</atitle><jtitle>Journal of computational chemistry</jtitle><addtitle>J. Comput. Chem</addtitle><date>2002-01-30</date><risdate>2002</risdate><volume>23</volume><issue>2</issue><spage>275</spage><epage>281</epage><pages>275-281</pages><issn>0192-8651</issn><eissn>1096-987X</eissn><abstract>The COSMO‐RS method, originally developed for the prediction of liquid–liquid and liquid–vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO‐RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug‐like compounds. On these data an rms deviation of 0.66 log‐units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log‐units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO‐RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO‐RSol. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 275–281, 2002</abstract><cop>New York</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>11924739</pmid><doi>10.1002/jcc.1168</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | ADME aqueous solubility Artificial Intelligence COSMO-RS drugs Models, Chemical pesticides Pesticides - chemistry Pharmaceutical Preparations - chemistry prediction Solubility Thermodynamics Water - chemistry |
title | Prediction of aqueous solubility of drugs and pesticides with COSMO-RS |
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