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A new descriptor of amino acids based on the three dimensional vector of atomic interaction field
A noval molecular structural expression method, three-dimensional vector of atomic interaction field (3D-VAIF), has been newly developed based on electrostatic and steric interaction between different types of atoms. Feature descriptors of single amino acid, i.e. principal component scores of struct...
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Published in: | Chinese science bulletin 2006-03, Vol.51 (5), p.524-529 |
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description | A noval molecular structural expression method, three-dimensional vector of atomic interaction field (3D-VAIF), has been newly developed based on electrostatic and steric interaction between different types of atoms. Feature descriptors of single amino acid, i.e. principal component scores of structural information for amino acids (SSIA), are obtained through calculation of structural information of 20 coded amino acids using principal component analysis (PCA) method, and the strict tests are performed on the property of SSIA by three quantitative structure-activity relationships (QSARs)/quantitative sequence-activity models (QSAMs) models of 58 ngiotensin-converting enzymes (ACE), 48 bitter tasting thresholds (BTT) and 31 bradykinin potentiating pentapeptides (BPP). Cumulative multiple correlation coefficients (E^2cum) are 0.789, 0.856 and 0.838; and corresponding cross-validated correlation coefficients (Q^2Loo) are 0.773, 0.837 and 0.815, respectively. Good results indicate that SSIA are better than traditional descriptors of amino acid in quantitative sequence-activity relationships of peptide analogues. |
doi_str_mv | 10.1007/s11434-006-0524-7 |
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Feature descriptors of single amino acid, i.e. principal component scores of structural information for amino acids (SSIA), are obtained through calculation of structural information of 20 coded amino acids using principal component analysis (PCA) method, and the strict tests are performed on the property of SSIA by three quantitative structure-activity relationships (QSARs)/quantitative sequence-activity models (QSAMs) models of 58 ngiotensin-converting enzymes (ACE), 48 bitter tasting thresholds (BTT) and 31 bradykinin potentiating pentapeptides (BPP). Cumulative multiple correlation coefficients (E^2cum) are 0.789, 0.856 and 0.838; and corresponding cross-validated correlation coefficients (Q^2Loo) are 0.773, 0.837 and 0.815, respectively. 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All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c332t-7d43b94ee00a6a2d1bb88450916cbd039d20a0d68c3191bfc42400d6aa27796b3</citedby><cites>FETCH-LOGICAL-c332t-7d43b94ee00a6a2d1bb88450916cbd039d20a0d68c3191bfc42400d6aa27796b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/86894X/86894X.jpg</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Zhou, Peng</creatorcontrib><creatorcontrib>Zhou, Yuan</creatorcontrib><creatorcontrib>Wu, Shirong</creatorcontrib><creatorcontrib>Li, Bo</creatorcontrib><creatorcontrib>Tian, Feifei</creatorcontrib><creatorcontrib>Li, Zhiliang</creatorcontrib><title>A new descriptor of amino acids based on the three dimensional vector of atomic interaction field</title><title>Chinese science bulletin</title><addtitle>Chinese Science Bulletin</addtitle><description>A noval molecular structural expression method, three-dimensional vector of atomic interaction field (3D-VAIF), has been newly developed based on electrostatic and steric interaction between different types of atoms. Feature descriptors of single amino acid, i.e. principal component scores of structural information for amino acids (SSIA), are obtained through calculation of structural information of 20 coded amino acids using principal component analysis (PCA) method, and the strict tests are performed on the property of SSIA by three quantitative structure-activity relationships (QSARs)/quantitative sequence-activity models (QSAMs) models of 58 ngiotensin-converting enzymes (ACE), 48 bitter tasting thresholds (BTT) and 31 bradykinin potentiating pentapeptides (BPP). Cumulative multiple correlation coefficients (E^2cum) are 0.789, 0.856 and 0.838; and corresponding cross-validated correlation coefficients (Q^2Loo) are 0.773, 0.837 and 0.815, respectively. Good results indicate that SSIA are better than traditional descriptors of amino acid in quantitative sequence-activity relationships of peptide analogues.</description><subject>Amino acid sequence</subject><subject>Amino acids</subject><subject>Atomic interactions</subject><subject>Bradykinin</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Electrostatic properties</subject><subject>Pentapeptides</subject><subject>Principal components analysis</subject><subject>Structure-activity relationships</subject><subject>主成分分析</subject><subject>偏最小二乘回归</subject><subject>原子间相互作用力场</subject><subject>多重回归分析</subject><subject>定量构效关系</subject><subject>氨基酸</subject><subject>结构信息</subject><subject>量子化学</subject><issn>1001-6538</issn><issn>2095-9273</issn><issn>1861-9541</issn><issn>2095-9281</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNpFkU1PHDEMhkcVlVhofwC3qD1wmmInmczMcYWgVELiQs9RPjxLYDfZTYYC_75Bu4iDZVt-Xst63TRnCL8QoL8oiFLIFkC10HHZ9l-aBQ4K27GTeFRrAGxVJ4bj5qSUx9oJ7PmiMUsW6YV5Ki6H7ZwySxMzmxATMy74wqwp5FmKbH6gGpmI-bChWEKKZs3-kfsQzWkTHAtxpmzcXMdsCrT235qvk1kX-n7Ip83f66v7y5v29u73n8vlbeuE4HPbeynsKIkAjDLco7XDIDsYUTnrQYyegwGvBidwRDs5ySXU3hje96Oy4rQ53-99MXEycaUf03OuJxb99DpbTbx6Ax1AV8mfe3Kb0-6ZyvyJcqWk7IduwErhnnI5lZJp0tscNia_aQT97rnee67rXv3uue6r5sdB85DiahfqFda4pymsSXMUXEF9wX8DzH7I</recordid><startdate>20060301</startdate><enddate>20060301</enddate><creator>Zhou, Peng</creator><creator>Zhou, Yuan</creator><creator>Wu, Shirong</creator><creator>Li, Bo</creator><creator>Tian, Feifei</creator><creator>Li, Zhiliang</creator><general>Springer Nature B.V</general><general>College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China</general><general>College of Bioengineering, Chongqing University, Chongqing 400044, China</general><general>Key Laboratory of Biomedical Engineering of Ministry of Education and Chongqing Municipality, Chongqing 400044, China%Key Laboratory of Biomedical Engineering of Ministry of Education and Chongqing Municipality, Chongqing 400044, China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W94</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20060301</creationdate><title>A new descriptor of amino acids based on the three dimensional vector of atomic interaction field</title><author>Zhou, Peng ; 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Feature descriptors of single amino acid, i.e. principal component scores of structural information for amino acids (SSIA), are obtained through calculation of structural information of 20 coded amino acids using principal component analysis (PCA) method, and the strict tests are performed on the property of SSIA by three quantitative structure-activity relationships (QSARs)/quantitative sequence-activity models (QSAMs) models of 58 ngiotensin-converting enzymes (ACE), 48 bitter tasting thresholds (BTT) and 31 bradykinin potentiating pentapeptides (BPP). Cumulative multiple correlation coefficients (E^2cum) are 0.789, 0.856 and 0.838; and corresponding cross-validated correlation coefficients (Q^2Loo) are 0.773, 0.837 and 0.815, respectively. Good results indicate that SSIA are better than traditional descriptors of amino acid in quantitative sequence-activity relationships of peptide analogues.</abstract><cop>Beijing</cop><pub>Springer Nature B.V</pub><doi>10.1007/s11434-006-0524-7</doi><tpages>6</tpages></addata></record> |
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subjects | Amino acid sequence Amino acids Atomic interactions Bradykinin Correlation coefficient Correlation coefficients Electrostatic properties Pentapeptides Principal components analysis Structure-activity relationships 主成分分析 偏最小二乘回归 原子间相互作用力场 多重回归分析 定量构效关系 氨基酸 结构信息 量子化学 |
title | A new descriptor of amino acids based on the three dimensional vector of atomic interaction field |
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