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Therefore, a large number of ACS sequences present in public databases lack any functional annotation at the level of substrate specificity. Recently, several examples have been reported where the enzymes showing high sequence similarity to luciferases or coumarate:CoA ligases have been surprisingly found to activate fatty acyl substrates in experimental studies. In this work, we have investigated the relationship between the substrate specificity of ACS and their sequence\/structural features, and developed a novel computational protocol for <jats:italic>in silico<\/jats:italic> assignment of substrate preference.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We have used a knowledge-based approach which involves compilation of substrate specificity information for various experimentally characterized ACS and derivation of profile HMMs for each subfamily. These HMM profiles can accurately differentiate probable cognate substrates from non-cognate possibilities with high specificity (Sp) and sensitivity (Sn) (Sn = 0.91-1.0, Sp = 0.96-1.0) values. Using homologous crystal structures, we identified a limited number of contact residues crucial for substrate recognition i.e. specificity determining residues (SDRs). Patterns of SDRs from different subfamilies have been used to derive predictive rules for correlating them to substrate preference. The power of the SDR approach has been demonstrated by correct prediction of substrates for enzymes which show apparently anomalous substrate preference. Furthermore, molecular modeling of the substrates in the active site has been carried out to understand the structural basis of substrate selection. A web based prediction tool <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/www.nii.res.in\/pred_acs_substr.html\" ext-link-type=\"uri\">http:\/\/www.nii.res.in\/pred_acs_substr.html<\/jats:ext-link> has been developed for automated functional classification of ACS enzymes.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>We have developed a novel computational protocol for predicting substrate preference for ACS superfamily of enzymes using a limited number of SDRs. Using this approach substrate preference can be assigned to a large number of ACS enzymes present in various genomes. It can potentially help in rational design of novel proteins with altered substrate specificities.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-11-57","type":"journal-article","created":{"date-parts":[[2010,1,27]],"date-time":"2010-01-27T19:18:28Z","timestamp":1264619908000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Genome scale prediction of substrate specificity for acyl adenylate superfamily of enzymes based on active site residue profiles"],"prefix":"10.1186","volume":"11","author":[{"given":"Pankaj","family":"Khurana","sequence":"first","affiliation":[]},{"given":"Rajesh S","family":"Gokhale","sequence":"additional","affiliation":[]},{"given":"Debasisa","family":"Mohanty","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,1,27]]},"reference":[{"issue":"29","key":"3514_CR1","doi-asserted-by":"publisher","first-page":"26893","DOI":"10.1074\/jbc.M100355200","volume":"276","author":"HP Stuible","year":"2001","unstructured":"Stuible HP, Kombrink E: Identification of the substrate specificity-conferring amino acid residues of 4-coumarate:coenzyme A ligase allows the rational design of mutant enzymes with new catalytic properties. 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