A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity
The molecular orbital semi-empirical method AM1 was employed to calculate a set of molecular properties (variables) of 22 flavonoid compounds (flavones) with anti-HIV-1 activity and nine new compounds were proposed for anti-HIV-1 activity prediction. Pattern recognition techniques, principal compone...
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Veröffentlicht in: | European journal of medicinal chemistry 2003-11, Vol.38 (11), p.929-938 |
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container_title | European journal of medicinal chemistry |
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creator | Souza, Jaime de Almeida Santos, Regina Helena Ferreira, Márcia Miguel Castro Molfetta, Fábio Alberto Camargo, Ademir João Maria Honório, Káthia da Silva, Albérico Borges Ferreira |
description | The molecular orbital semi-empirical method AM1 was employed to calculate a set of molecular properties (variables) of 22 flavonoid compounds (flavones) with anti-HIV-1 activity and nine new compounds were proposed for anti-HIV-1 activity prediction. Pattern recognition techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA) and K-nearest neighbor (KNN), were employed in order to reduce dimensionality and investigate which subset of variables could be more effective for classifying the flavones according to their degree of anti-HIV-1 activity. The PCA, HCA, SDA and KNN studies showed that the variables log
P (partition coefficient), molecular volume (VOL) and electron affinity (EA) are responsible for the separation between anti-HIV-1 active and inactive compounds. The prediction study was done with a new set of nine analog compounds by using the PCA, HCA, SDA and KNN methods and only one of them was predicted as active against HIV-1. |
doi_str_mv | 10.1016/j.ejmech.2003.06.001 |
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P (partition coefficient), molecular volume (VOL) and electron affinity (EA) are responsible for the separation between anti-HIV-1 active and inactive compounds. The prediction study was done with a new set of nine analog compounds by using the PCA, HCA, SDA and KNN methods and only one of them was predicted as active against HIV-1.</description><identifier>ISSN: 0223-5234</identifier><identifier>EISSN: 1768-3254</identifier><identifier>DOI: 10.1016/j.ejmech.2003.06.001</identifier><identifier>PMID: 14642325</identifier><identifier>CODEN: EJMCA5</identifier><language>eng</language><publisher>Oxford: Elsevier Masson SAS</publisher><subject>AM1 ; Anti-HIV Agents - chemistry ; Anti-HIV-1 activity ; Antibiotics. Antiinfectious agents. Antiparasitic agents ; Antiviral agents ; Biological and medical sciences ; Cluster Analysis ; Flavones ; Flavonoids - chemistry ; Hierarchical cluster analysis ; K-nearest neighbor ; Medical sciences ; Pharmacology. Drug treatments ; Principal component analysis ; Principal Component Analysis - methods ; Stepwise discriminant analysis ; Structure-Activity Relationship</subject><ispartof>European journal of medicinal chemistry, 2003-11, Vol.38 (11), p.929-938</ispartof><rights>2003 Éditions scientifiques et médicales Elsevier SAS</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c388t-b7baf0f2e0f0a84be342da9298fd2ef3a14d1ddf7e06324b5f00e20367047843</citedby><cites>FETCH-LOGICAL-c388t-b7baf0f2e0f0a84be342da9298fd2ef3a14d1ddf7e06324b5f00e20367047843</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ejmech.2003.06.001$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15307110$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/14642325$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Souza, Jaime</creatorcontrib><creatorcontrib>de Almeida Santos, Regina Helena</creatorcontrib><creatorcontrib>Ferreira, Márcia Miguel Castro</creatorcontrib><creatorcontrib>Molfetta, Fábio Alberto</creatorcontrib><creatorcontrib>Camargo, Ademir João</creatorcontrib><creatorcontrib>Maria Honório, Káthia</creatorcontrib><creatorcontrib>da Silva, Albérico Borges Ferreira</creatorcontrib><title>A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity</title><title>European journal of medicinal chemistry</title><addtitle>Eur J Med Chem</addtitle><description>The molecular orbital semi-empirical method AM1 was employed to calculate a set of molecular properties (variables) of 22 flavonoid compounds (flavones) with anti-HIV-1 activity and nine new compounds were proposed for anti-HIV-1 activity prediction. Pattern recognition techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA) and K-nearest neighbor (KNN), were employed in order to reduce dimensionality and investigate which subset of variables could be more effective for classifying the flavones according to their degree of anti-HIV-1 activity. The PCA, HCA, SDA and KNN studies showed that the variables log
P (partition coefficient), molecular volume (VOL) and electron affinity (EA) are responsible for the separation between anti-HIV-1 active and inactive compounds. The prediction study was done with a new set of nine analog compounds by using the PCA, HCA, SDA and KNN methods and only one of them was predicted as active against HIV-1.</description><subject>AM1</subject><subject>Anti-HIV Agents - chemistry</subject><subject>Anti-HIV-1 activity</subject><subject>Antibiotics. Antiinfectious agents. Antiparasitic agents</subject><subject>Antiviral agents</subject><subject>Biological and medical sciences</subject><subject>Cluster Analysis</subject><subject>Flavones</subject><subject>Flavonoids - chemistry</subject><subject>Hierarchical cluster analysis</subject><subject>K-nearest neighbor</subject><subject>Medical sciences</subject><subject>Pharmacology. Drug treatments</subject><subject>Principal component analysis</subject><subject>Principal Component Analysis - methods</subject><subject>Stepwise discriminant analysis</subject><subject>Structure-Activity Relationship</subject><issn>0223-5234</issn><issn>1768-3254</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1r3DAQhkVJaTbb_oMQdElpD3ZHH_7IJRCWpgkEegm9ClkasVpsa2PJG_bfV6kXcutpmOF5X4aHkEsGJQNW_9iVuBvQbEsOIEqoSwD2gaxYU7eF4JU8IyvgXBQVF_KcXMS4A4CqBvhEzpmsJc_Qiug7-jLrMc0DNVscvNE91aOlMenkY_q3xzTbIw2Oul4fwhi8pSYM-zCPNtJvyxHjd_rq0zaHky8eHv9QbZI_-HT8TD463Uf8cppr8nz_83nzUDz9_vW4uXsqjGjbVHRNpx04juBAt7JDIbnVN_ymdZajE5pJy6x1DUItuOwqB4AcRN2AbFop1uTrUrufwsuMManBR4N9r0cMc1QNk1lNFrImcgHNFGKc0Kn95Ac9HRUD9WZW7dRiVr2ZVVCrbDbHrk79czegfQ-dVGbg-gTomK25SY_Gx3euEtAwBpm7XTjMMg4eJxWNx9Gg9ROapGzw___kLwkzmR8</recordid><startdate>20031101</startdate><enddate>20031101</enddate><creator>Souza, Jaime</creator><creator>de Almeida Santos, Regina Helena</creator><creator>Ferreira, Márcia Miguel Castro</creator><creator>Molfetta, Fábio Alberto</creator><creator>Camargo, Ademir João</creator><creator>Maria Honório, Káthia</creator><creator>da Silva, Albérico Borges Ferreira</creator><general>Elsevier Masson SAS</general><general>Elsevier</general><scope>IQODW</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><scope>7X8</scope></search><sort><creationdate>20031101</creationdate><title>A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity</title><author>Souza, Jaime ; de Almeida Santos, Regina Helena ; Ferreira, Márcia Miguel Castro ; Molfetta, Fábio Alberto ; Camargo, Ademir João ; Maria Honório, Káthia ; da Silva, Albérico Borges Ferreira</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-b7baf0f2e0f0a84be342da9298fd2ef3a14d1ddf7e06324b5f00e20367047843</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>AM1</topic><topic>Anti-HIV Agents - chemistry</topic><topic>Anti-HIV-1 activity</topic><topic>Antibiotics. Antiinfectious agents. Antiparasitic agents</topic><topic>Antiviral agents</topic><topic>Biological and medical sciences</topic><topic>Cluster Analysis</topic><topic>Flavones</topic><topic>Flavonoids - chemistry</topic><topic>Hierarchical cluster analysis</topic><topic>K-nearest neighbor</topic><topic>Medical sciences</topic><topic>Pharmacology. Drug treatments</topic><topic>Principal component analysis</topic><topic>Principal Component Analysis - methods</topic><topic>Stepwise discriminant analysis</topic><topic>Structure-Activity Relationship</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Souza, Jaime</creatorcontrib><creatorcontrib>de Almeida Santos, Regina Helena</creatorcontrib><creatorcontrib>Ferreira, Márcia Miguel Castro</creatorcontrib><creatorcontrib>Molfetta, Fábio Alberto</creatorcontrib><creatorcontrib>Camargo, Ademir João</creatorcontrib><creatorcontrib>Maria Honório, Káthia</creatorcontrib><creatorcontrib>da Silva, Albérico Borges Ferreira</creatorcontrib><collection>Pascal-Francis</collection><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>European journal of medicinal chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Souza, Jaime</au><au>de Almeida Santos, Regina Helena</au><au>Ferreira, Márcia Miguel Castro</au><au>Molfetta, Fábio Alberto</au><au>Camargo, Ademir João</au><au>Maria Honório, Káthia</au><au>da Silva, Albérico Borges Ferreira</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity</atitle><jtitle>European journal of medicinal chemistry</jtitle><addtitle>Eur J Med Chem</addtitle><date>2003-11-01</date><risdate>2003</risdate><volume>38</volume><issue>11</issue><spage>929</spage><epage>938</epage><pages>929-938</pages><issn>0223-5234</issn><eissn>1768-3254</eissn><coden>EJMCA5</coden><abstract>The molecular orbital semi-empirical method AM1 was employed to calculate a set of molecular properties (variables) of 22 flavonoid compounds (flavones) with anti-HIV-1 activity and nine new compounds were proposed for anti-HIV-1 activity prediction. Pattern recognition techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA) and K-nearest neighbor (KNN), were employed in order to reduce dimensionality and investigate which subset of variables could be more effective for classifying the flavones according to their degree of anti-HIV-1 activity. The PCA, HCA, SDA and KNN studies showed that the variables log
P (partition coefficient), molecular volume (VOL) and electron affinity (EA) are responsible for the separation between anti-HIV-1 active and inactive compounds. The prediction study was done with a new set of nine analog compounds by using the PCA, HCA, SDA and KNN methods and only one of them was predicted as active against HIV-1.</abstract><cop>Oxford</cop><pub>Elsevier Masson SAS</pub><pmid>14642325</pmid><doi>10.1016/j.ejmech.2003.06.001</doi><tpages>10</tpages></addata></record> |
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subjects | AM1 Anti-HIV Agents - chemistry Anti-HIV-1 activity Antibiotics. Antiinfectious agents. Antiparasitic agents Antiviral agents Biological and medical sciences Cluster Analysis Flavones Flavonoids - chemistry Hierarchical cluster analysis K-nearest neighbor Medical sciences Pharmacology. Drug treatments Principal component analysis Principal Component Analysis - methods Stepwise discriminant analysis Structure-Activity Relationship |
title | A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity |
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