Predicting the Reactivity of Proteins from Their Sequence Alone: Kazal Family of Protein Inhibitors of Serine Proteinases
An additivity-based sequence to reactivity algorithm for the interaction of members of the Kazal family of protein inhibitors with six selected serine proteinases is described. Ten consensus variable contact positions in the inhibitor were identified, and the 19 possible variants at each of these po...
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| Veröffentlicht in: | Proceedings of the National Academy of Sciences - PNAS 2001-02, Vol.98 (4), p.1410-1415 |
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| container_title | Proceedings of the National Academy of Sciences - PNAS |
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| creator | Lu, Stephen M. Lu, Wuyuan Qasim, M. A. Anderson, Stephen Apostol, Izydor Ardelt, Wojciech Bigler, Theresa Chiang, Yi Wen Cook, James Michael N. G. James Kato, Ikunoshin Kelly, Clyde Kohr, William Komiyama, Tomoko Lin, Tiao-Yin Ogawa, Michio Otlewski, Jacek Park, Soon-Jae Qasim, Sabiha Ranjbar, Michael Tashiro, Misao Warne, Nicholas Whatley, Harry Wieczorek, Anna Wieczorek, Maciej Wilusz, Tadeusz Wynn, Richard Zhang, Wenlei Laskowski, Michael |
| description | An additivity-based sequence to reactivity algorithm for the interaction of members of the Kazal family of protein inhibitors with six selected serine proteinases is described. Ten consensus variable contact positions in the inhibitor were identified, and the 19 possible variants at each of these positions were expressed. The free energies of interaction of these variants and the wild type were measured. For an additive system, this data set allows for the calculation of all possible sequences, subject to some restrictions. The algorithm was extensively tested. It is exceptionally fast so that all possible sequences can be predicted. The strongest, the most specific possible, and the least specific inhibitors were designed, and an evolutionary problem was solved. |
| doi_str_mv | 10.1073/pnas.031581398 |
| format | Article |
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A. ; Anderson, Stephen ; Apostol, Izydor ; Ardelt, Wojciech ; Bigler, Theresa ; Chiang, Yi Wen ; Cook, James ; Michael N. G. James ; Kato, Ikunoshin ; Kelly, Clyde ; Kohr, William ; Komiyama, Tomoko ; Lin, Tiao-Yin ; Ogawa, Michio ; Otlewski, Jacek ; Park, Soon-Jae ; Qasim, Sabiha ; Ranjbar, Michael ; Tashiro, Misao ; Warne, Nicholas ; Whatley, Harry ; Wieczorek, Anna ; Wieczorek, Maciej ; Wilusz, Tadeusz ; Wynn, Richard ; Zhang, Wenlei ; Laskowski, Michael</creator><creatorcontrib>Lu, Stephen M. ; Lu, Wuyuan ; Qasim, M. A. ; Anderson, Stephen ; Apostol, Izydor ; Ardelt, Wojciech ; Bigler, Theresa ; Chiang, Yi Wen ; Cook, James ; Michael N. G. James ; Kato, Ikunoshin ; Kelly, Clyde ; Kohr, William ; Komiyama, Tomoko ; Lin, Tiao-Yin ; Ogawa, Michio ; Otlewski, Jacek ; Park, Soon-Jae ; Qasim, Sabiha ; Ranjbar, Michael ; Tashiro, Misao ; Warne, Nicholas ; Whatley, Harry ; Wieczorek, Anna ; Wieczorek, Maciej ; Wilusz, Tadeusz ; Wynn, Richard ; Zhang, Wenlei ; Laskowski, Michael</creatorcontrib><description>An additivity-based sequence to reactivity algorithm for the interaction of members of the Kazal family of protein inhibitors with six selected serine proteinases is described. Ten consensus variable contact positions in the inhibitor were identified, and the 19 possible variants at each of these positions were expressed. The free energies of interaction of these variants and the wild type were measured. For an additive system, this data set allows for the calculation of all possible sequences, subject to some restrictions. The algorithm was extensively tested. It is exceptionally fast so that all possible sequences can be predicted. The strongest, the most specific possible, and the least specific inhibitors were designed, and an evolutionary problem was solved.</description><identifier>ISSN: 0027-8424</identifier><identifier>EISSN: 1091-6490</identifier><identifier>DOI: 10.1073/pnas.031581398</identifier><identifier>PMID: 11171964</identifier><language>eng</language><publisher>United States: National Academy of Sciences</publisher><subject>Additivity ; Algorithms ; Amino Acid Sequence ; Animals ; Bacterial Proteins ; Binding Sites ; Biochemistry ; Biological Sciences ; Birds ; Cattle ; Chymotrypsin - metabolism ; Dynamic range ; Enzymes ; Free energy ; Humans ; Leukocyte Elastase - metabolism ; Ligands ; Mathematical constants ; Molecular Sequence Data ; Ovomucin - metabolism ; Pancreatic Elastase - metabolism ; Proteins ; Reactivity ; Serine Endopeptidases - metabolism ; Subtilisins - metabolism ; Trypsin inhibitors ; Trypsin Inhibitors - metabolism</subject><ispartof>Proceedings of the National Academy of Sciences - PNAS, 2001-02, Vol.98 (4), p.1410-1415</ispartof><rights>Copyright 1993-2001 National Academy of Sciences of the United States of America</rights><rights>Copyright National Academy of Sciences Feb 13, 2001</rights><rights>Copyright © 2001, The National Academy of Sciences 2001</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c378t-9ecd54a077afa58161806f03b3b9796e0d7704041e91f4417e430f6374521b243</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.pnas.org/content/98/4.cover.gif</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/3054889$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/3054889$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,723,776,780,799,881,27903,27904,53769,53771,57995,58228</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11171964$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lu, Stephen M.</creatorcontrib><creatorcontrib>Lu, Wuyuan</creatorcontrib><creatorcontrib>Qasim, M. A.</creatorcontrib><creatorcontrib>Anderson, Stephen</creatorcontrib><creatorcontrib>Apostol, Izydor</creatorcontrib><creatorcontrib>Ardelt, Wojciech</creatorcontrib><creatorcontrib>Bigler, Theresa</creatorcontrib><creatorcontrib>Chiang, Yi Wen</creatorcontrib><creatorcontrib>Cook, James</creatorcontrib><creatorcontrib>Michael N. G. James</creatorcontrib><creatorcontrib>Kato, Ikunoshin</creatorcontrib><creatorcontrib>Kelly, Clyde</creatorcontrib><creatorcontrib>Kohr, William</creatorcontrib><creatorcontrib>Komiyama, Tomoko</creatorcontrib><creatorcontrib>Lin, Tiao-Yin</creatorcontrib><creatorcontrib>Ogawa, Michio</creatorcontrib><creatorcontrib>Otlewski, Jacek</creatorcontrib><creatorcontrib>Park, Soon-Jae</creatorcontrib><creatorcontrib>Qasim, Sabiha</creatorcontrib><creatorcontrib>Ranjbar, Michael</creatorcontrib><creatorcontrib>Tashiro, Misao</creatorcontrib><creatorcontrib>Warne, Nicholas</creatorcontrib><creatorcontrib>Whatley, Harry</creatorcontrib><creatorcontrib>Wieczorek, Anna</creatorcontrib><creatorcontrib>Wieczorek, Maciej</creatorcontrib><creatorcontrib>Wilusz, Tadeusz</creatorcontrib><creatorcontrib>Wynn, Richard</creatorcontrib><creatorcontrib>Zhang, Wenlei</creatorcontrib><creatorcontrib>Laskowski, Michael</creatorcontrib><title>Predicting the Reactivity of Proteins from Their Sequence Alone: Kazal Family of Protein Inhibitors of Serine Proteinases</title><title>Proceedings of the National Academy of Sciences - PNAS</title><addtitle>Proc Natl Acad Sci U S A</addtitle><description>An additivity-based sequence to reactivity algorithm for the interaction of members of the Kazal family of protein inhibitors with six selected serine proteinases is described. Ten consensus variable contact positions in the inhibitor were identified, and the 19 possible variants at each of these positions were expressed. The free energies of interaction of these variants and the wild type were measured. For an additive system, this data set allows for the calculation of all possible sequences, subject to some restrictions. The algorithm was extensively tested. It is exceptionally fast so that all possible sequences can be predicted. The strongest, the most specific possible, and the least specific inhibitors were designed, and an evolutionary problem was solved.</description><subject>Additivity</subject><subject>Algorithms</subject><subject>Amino Acid Sequence</subject><subject>Animals</subject><subject>Bacterial Proteins</subject><subject>Binding Sites</subject><subject>Biochemistry</subject><subject>Biological Sciences</subject><subject>Birds</subject><subject>Cattle</subject><subject>Chymotrypsin - metabolism</subject><subject>Dynamic range</subject><subject>Enzymes</subject><subject>Free energy</subject><subject>Humans</subject><subject>Leukocyte Elastase - metabolism</subject><subject>Ligands</subject><subject>Mathematical constants</subject><subject>Molecular Sequence Data</subject><subject>Ovomucin - metabolism</subject><subject>Pancreatic Elastase - metabolism</subject><subject>Proteins</subject><subject>Reactivity</subject><subject>Serine Endopeptidases - metabolism</subject><subject>Subtilisins - metabolism</subject><subject>Trypsin inhibitors</subject><subject>Trypsin Inhibitors - metabolism</subject><issn>0027-8424</issn><issn>1091-6490</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNptkc1v1DAQxS0EokvhygmQxYFbyjh24hhxqSr6oVaiouVsOdlJ16vEXmynYvnr8arb1YJ6suz3e6P3PIS8ZXDEQPLPK2fiEXBWNYyr5hmZMVCsqIWC52QGUMqiEaU4IK9iXAKAqhp4SQ4YY5KpWszI-jrg3HbJujuaFkh_oMmXe5vW1Pf0OviE1kXaBz_S2wXaQG_w14SuQ3o8eIdf6KX5YwZ6akY77HvohVvY1iYf4ub1BoN1-CiaiPE1edGbIeKb7XlIfp5-uz05L66-n12cHF8VHZdNKhR280oYkNL0JresWQN1D7zlrZKqRphLCQIEQ8V6IZhEwaGvuRRVydpS8EPy9WHuampHnHfoUjCDXgU7mrDW3lj9r-LsQt_5e12qUkK2f9rag8_FY9KjjR0Og3Hop6gl1KVSlcrgx__ApZ-Cy9V0CUwwqNgG-rAfZpficSEZeL8F8iftZNVooTcz9uI8qet-GoaEv1MG3z2Ay5h3sCM5VKJpFP8LNXKuyQ</recordid><startdate>20010213</startdate><enddate>20010213</enddate><creator>Lu, Stephen M.</creator><creator>Lu, Wuyuan</creator><creator>Qasim, M. 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A.</au><au>Anderson, Stephen</au><au>Apostol, Izydor</au><au>Ardelt, Wojciech</au><au>Bigler, Theresa</au><au>Chiang, Yi Wen</au><au>Cook, James</au><au>Michael N. G. James</au><au>Kato, Ikunoshin</au><au>Kelly, Clyde</au><au>Kohr, William</au><au>Komiyama, Tomoko</au><au>Lin, Tiao-Yin</au><au>Ogawa, Michio</au><au>Otlewski, Jacek</au><au>Park, Soon-Jae</au><au>Qasim, Sabiha</au><au>Ranjbar, Michael</au><au>Tashiro, Misao</au><au>Warne, Nicholas</au><au>Whatley, Harry</au><au>Wieczorek, Anna</au><au>Wieczorek, Maciej</au><au>Wilusz, Tadeusz</au><au>Wynn, Richard</au><au>Zhang, Wenlei</au><au>Laskowski, Michael</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the Reactivity of Proteins from Their Sequence Alone: Kazal Family of Protein Inhibitors of Serine Proteinases</atitle><jtitle>Proceedings of the National Academy of Sciences - PNAS</jtitle><addtitle>Proc Natl Acad Sci U S A</addtitle><date>2001-02-13</date><risdate>2001</risdate><volume>98</volume><issue>4</issue><spage>1410</spage><epage>1415</epage><pages>1410-1415</pages><issn>0027-8424</issn><eissn>1091-6490</eissn><abstract>An additivity-based sequence to reactivity algorithm for the interaction of members of the Kazal family of protein inhibitors with six selected serine proteinases is described. Ten consensus variable contact positions in the inhibitor were identified, and the 19 possible variants at each of these positions were expressed. The free energies of interaction of these variants and the wild type were measured. For an additive system, this data set allows for the calculation of all possible sequences, subject to some restrictions. The algorithm was extensively tested. It is exceptionally fast so that all possible sequences can be predicted. The strongest, the most specific possible, and the least specific inhibitors were designed, and an evolutionary problem was solved.</abstract><cop>United States</cop><pub>National Academy of Sciences</pub><pmid>11171964</pmid><doi>10.1073/pnas.031581398</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Proceedings of the National Academy of Sciences - PNAS, 2001-02, Vol.98 (4), p.1410-1415 |
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| subjects | Additivity Algorithms Amino Acid Sequence Animals Bacterial Proteins Binding Sites Biochemistry Biological Sciences Birds Cattle Chymotrypsin - metabolism Dynamic range Enzymes Free energy Humans Leukocyte Elastase - metabolism Ligands Mathematical constants Molecular Sequence Data Ovomucin - metabolism Pancreatic Elastase - metabolism Proteins Reactivity Serine Endopeptidases - metabolism Subtilisins - metabolism Trypsin inhibitors Trypsin Inhibitors - metabolism |
| title | Predicting the Reactivity of Proteins from Their Sequence Alone: Kazal Family of Protein Inhibitors of Serine Proteinases |
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