Calculations of acute intravenous toxicity in mice based on local regression models in superoverlapping clusters (LRMSC)
Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descriptors of organic chemicals and their acute intravenous toxicity in mice have been presented. This approach includes three steps: structure-similarity chemicals selection for every compound-of-interest (c...
Gespeichert in:
Veröffentlicht in: | Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry Biomedical chemistry, 2011-12, Vol.5 (4), p.346-356 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 356 |
---|---|
container_issue | 4 |
container_start_page | 346 |
container_title | Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry |
container_volume | 5 |
creator | Raevsky, O. A. Grigoriev, V. Yu Liplavskaya, E. A. Worth, A. P. |
description | Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descriptors of organic chemicals and their acute intravenous toxicity in mice have been presented. This approach includes three steps: structure-similarity chemicals selection for every compound-of-interest (clusterization); construction of quantitative structure — toxicity models for every cluster (without including of compounds-of-interest); application of the obtained QSAR equations for chemical-of-interest toxicity estimation. This approach has been applied for calculations of acute intravenous toxicity for 10241 organic chemicals. For 7759 compounds possessing structural neighbors with the Tanimoto index (Tc) of 0.30 and above the standard deviation of the calculated vs. experimental log(1/LD
50
) values was 0.51 at the estimation of the experimental determination error of ±0.50 (log(1/LD
50
) value). Calculations performed for remaining compounds (∼24%) were not as good as those made for the former group, possibly due to lack of reasonable number of structurally related analogues. It’s suggested that this QSAR approach can be useful for prediction of biological activity and toxicity of large sets of chemical compounds. |
doi_str_mv | 10.1134/S1990750811040081 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1419361808</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2505982961</sourcerecordid><originalsourceid>FETCH-LOGICAL-c300t-ac7f2718362860a672531c7d232c18a350320d9c3bd7735c59ad6995998ae3f33</originalsourceid><addsrcrecordid>eNp1kU9LxDAQxYMouK5-AG_B03qoJk3bNEcp_oMVwdVzyabTpUva1Ewru9_eLCsKiqcZht97M8Mj5JyzK85Fcr3gSjGZspxzlrBQDshkN4pkyrPD757lx-QEcc1YxoVKJmRTaGtGq4fGdUhdTbUZB6BNN3j9AZ0bkQ5u05hm2IYhbRsDdKkRKuo6ap3RlnpYeUAMBrR1FVjcgTj24N0HeKv7vulW1NgRB_BIZ_OXp0VxeUqOam0Rzr7qlLzd3b4WD9H8-f6xuJlHRjA2RNrIOpY8F1mcZ0xnMk4FN7KKRWx4rkXKRMwqZcSyklKkJlW6ypRKlco1iFqIKZntfXvv3kfAoWwbNGCt7iB8V_KEK5HxnOUBvfiFrt3ou3BdqVicSaXCiinhe8h4h-ihLnvftNpvS87KXRTlnyiCJt5rMLDdCvyP8f-iTwEGirc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>902679977</pqid></control><display><type>article</type><title>Calculations of acute intravenous toxicity in mice based on local regression models in superoverlapping clusters (LRMSC)</title><source>SpringerLink Journals - AutoHoldings</source><creator>Raevsky, O. A. ; Grigoriev, V. Yu ; Liplavskaya, E. A. ; Worth, A. P.</creator><creatorcontrib>Raevsky, O. A. ; Grigoriev, V. Yu ; Liplavskaya, E. A. ; Worth, A. P.</creatorcontrib><description>Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descriptors of organic chemicals and their acute intravenous toxicity in mice have been presented. This approach includes three steps: structure-similarity chemicals selection for every compound-of-interest (clusterization); construction of quantitative structure — toxicity models for every cluster (without including of compounds-of-interest); application of the obtained QSAR equations for chemical-of-interest toxicity estimation. This approach has been applied for calculations of acute intravenous toxicity for 10241 organic chemicals. For 7759 compounds possessing structural neighbors with the Tanimoto index (Tc) of 0.30 and above the standard deviation of the calculated vs. experimental log(1/LD
50
) values was 0.51 at the estimation of the experimental determination error of ±0.50 (log(1/LD
50
) value). Calculations performed for remaining compounds (∼24%) were not as good as those made for the former group, possibly due to lack of reasonable number of structurally related analogues. It’s suggested that this QSAR approach can be useful for prediction of biological activity and toxicity of large sets of chemical compounds.</description><identifier>ISSN: 1990-7508</identifier><identifier>EISSN: 1990-7516</identifier><identifier>DOI: 10.1134/S1990750811040081</identifier><language>eng</language><publisher>Dordrecht: SP MAIK Nauka/Interperiodica</publisher><subject>Bioorganic Chemistry ; Chemistry ; Chemistry and Materials Science ; Cluster analysis ; Medicinal Chemistry ; Regression analysis ; Rodents ; Toxicity</subject><ispartof>Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry, 2011-12, Vol.5 (4), p.346-356</ispartof><rights>Pleiades Publishing, Ltd. 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c300t-ac7f2718362860a672531c7d232c18a350320d9c3bd7735c59ad6995998ae3f33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1134/S1990750811040081$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1134/S1990750811040081$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids></links><search><creatorcontrib>Raevsky, O. A.</creatorcontrib><creatorcontrib>Grigoriev, V. Yu</creatorcontrib><creatorcontrib>Liplavskaya, E. A.</creatorcontrib><creatorcontrib>Worth, A. P.</creatorcontrib><title>Calculations of acute intravenous toxicity in mice based on local regression models in superoverlapping clusters (LRMSC)</title><title>Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry</title><addtitle>Biochem. Moscow Suppl. Ser. B</addtitle><description>Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descriptors of organic chemicals and their acute intravenous toxicity in mice have been presented. This approach includes three steps: structure-similarity chemicals selection for every compound-of-interest (clusterization); construction of quantitative structure — toxicity models for every cluster (without including of compounds-of-interest); application of the obtained QSAR equations for chemical-of-interest toxicity estimation. This approach has been applied for calculations of acute intravenous toxicity for 10241 organic chemicals. For 7759 compounds possessing structural neighbors with the Tanimoto index (Tc) of 0.30 and above the standard deviation of the calculated vs. experimental log(1/LD
50
) values was 0.51 at the estimation of the experimental determination error of ±0.50 (log(1/LD
50
) value). Calculations performed for remaining compounds (∼24%) were not as good as those made for the former group, possibly due to lack of reasonable number of structurally related analogues. It’s suggested that this QSAR approach can be useful for prediction of biological activity and toxicity of large sets of chemical compounds.</description><subject>Bioorganic Chemistry</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Cluster analysis</subject><subject>Medicinal Chemistry</subject><subject>Regression analysis</subject><subject>Rodents</subject><subject>Toxicity</subject><issn>1990-7508</issn><issn>1990-7516</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kU9LxDAQxYMouK5-AG_B03qoJk3bNEcp_oMVwdVzyabTpUva1Ewru9_eLCsKiqcZht97M8Mj5JyzK85Fcr3gSjGZspxzlrBQDshkN4pkyrPD757lx-QEcc1YxoVKJmRTaGtGq4fGdUhdTbUZB6BNN3j9AZ0bkQ5u05hm2IYhbRsDdKkRKuo6ap3RlnpYeUAMBrR1FVjcgTj24N0HeKv7vulW1NgRB_BIZ_OXp0VxeUqOam0Rzr7qlLzd3b4WD9H8-f6xuJlHRjA2RNrIOpY8F1mcZ0xnMk4FN7KKRWx4rkXKRMwqZcSyklKkJlW6ypRKlco1iFqIKZntfXvv3kfAoWwbNGCt7iB8V_KEK5HxnOUBvfiFrt3ou3BdqVicSaXCiinhe8h4h-ihLnvftNpvS87KXRTlnyiCJt5rMLDdCvyP8f-iTwEGirc</recordid><startdate>20111201</startdate><enddate>20111201</enddate><creator>Raevsky, O. A.</creator><creator>Grigoriev, V. Yu</creator><creator>Liplavskaya, E. A.</creator><creator>Worth, A. P.</creator><general>SP MAIK Nauka/Interperiodica</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88I</scope><scope>8AO</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M2P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7U7</scope><scope>C1K</scope></search><sort><creationdate>20111201</creationdate><title>Calculations of acute intravenous toxicity in mice based on local regression models in superoverlapping clusters (LRMSC)</title><author>Raevsky, O. A. ; Grigoriev, V. Yu ; Liplavskaya, E. A. ; Worth, A. P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c300t-ac7f2718362860a672531c7d232c18a350320d9c3bd7735c59ad6995998ae3f33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Bioorganic Chemistry</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Cluster analysis</topic><topic>Medicinal Chemistry</topic><topic>Regression analysis</topic><topic>Rodents</topic><topic>Toxicity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Raevsky, O. A.</creatorcontrib><creatorcontrib>Grigoriev, V. Yu</creatorcontrib><creatorcontrib>Liplavskaya, E. A.</creatorcontrib><creatorcontrib>Worth, A. P.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Raevsky, O. A.</au><au>Grigoriev, V. Yu</au><au>Liplavskaya, E. A.</au><au>Worth, A. P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Calculations of acute intravenous toxicity in mice based on local regression models in superoverlapping clusters (LRMSC)</atitle><jtitle>Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry</jtitle><stitle>Biochem. Moscow Suppl. Ser. B</stitle><date>2011-12-01</date><risdate>2011</risdate><volume>5</volume><issue>4</issue><spage>346</spage><epage>356</epage><pages>346-356</pages><issn>1990-7508</issn><eissn>1990-7516</eissn><abstract>Modeling of quantitative structure — activity relationships (QSAR) between physicochemical descriptors of organic chemicals and their acute intravenous toxicity in mice have been presented. This approach includes three steps: structure-similarity chemicals selection for every compound-of-interest (clusterization); construction of quantitative structure — toxicity models for every cluster (without including of compounds-of-interest); application of the obtained QSAR equations for chemical-of-interest toxicity estimation. This approach has been applied for calculations of acute intravenous toxicity for 10241 organic chemicals. For 7759 compounds possessing structural neighbors with the Tanimoto index (Tc) of 0.30 and above the standard deviation of the calculated vs. experimental log(1/LD
50
) values was 0.51 at the estimation of the experimental determination error of ±0.50 (log(1/LD
50
) value). Calculations performed for remaining compounds (∼24%) were not as good as those made for the former group, possibly due to lack of reasonable number of structurally related analogues. It’s suggested that this QSAR approach can be useful for prediction of biological activity and toxicity of large sets of chemical compounds.</abstract><cop>Dordrecht</cop><pub>SP MAIK Nauka/Interperiodica</pub><doi>10.1134/S1990750811040081</doi><tpages>11</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1990-7508 |
ispartof | Biochemistry (Moscow). Supplement. Series B, Biomedical chemistry, 2011-12, Vol.5 (4), p.346-356 |
issn | 1990-7508 1990-7516 |
language | eng |
recordid | cdi_proquest_miscellaneous_1419361808 |
source | SpringerLink Journals - AutoHoldings |
subjects | Bioorganic Chemistry Chemistry Chemistry and Materials Science Cluster analysis Medicinal Chemistry Regression analysis Rodents Toxicity |
title | Calculations of acute intravenous toxicity in mice based on local regression models in superoverlapping clusters (LRMSC) |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T21%3A13%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Calculations%20of%20acute%20intravenous%20toxicity%20in%20mice%20based%20on%20local%20regression%20models%20in%20superoverlapping%20clusters%20(LRMSC)&rft.jtitle=Biochemistry%20(Moscow).%20Supplement.%20Series%20B,%20Biomedical%20chemistry&rft.au=Raevsky,%20O.%20A.&rft.date=2011-12-01&rft.volume=5&rft.issue=4&rft.spage=346&rft.epage=356&rft.pages=346-356&rft.issn=1990-7508&rft.eissn=1990-7516&rft_id=info:doi/10.1134/S1990750811040081&rft_dat=%3Cproquest_cross%3E2505982961%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=902679977&rft_id=info:pmid/&rfr_iscdi=true |