{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:40:23Z","timestamp":1764783623858},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2014,5,16]],"date-time":"2014-05-16T00:00:00Z","timestamp":1400198400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"published-print":{"date-parts":[[2014,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Acute toxicity means the ability of a substance to cause adverse effects within a short period following dosing or exposure, which is usually the first step in the toxicological investigations of unknown substances. The median lethal dose, LD<jats:sub>50<\/jats:sub>, is frequently used as a general indicator of a substance\u2019s acute toxicity, and there is a high demand on developing non-animal-based prediction of LD<jats:sub>50<\/jats:sub>. Unfortunately, it is difficult to accurately predict compound LD<jats:sub>50<\/jats:sub> using a single QSAR model, because the acute toxicity may involve complex mechanisms and multiple biochemical processes.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In this study, we reported the use of local lazy learning (LLL) methods, which could capture subtle local structure-toxicity relationships around each query compound, to develop LD<jats:sub>50<\/jats:sub> prediction models: (a) local lazy regression (LLR): a linear regression model built using <jats:italic>k<\/jats:italic> neighbors; (b) SA: the arithmetical mean of the activities of <jats:italic>k<\/jats:italic> nearest neighbors; (c) SR: the weighted mean of the activities of <jats:italic>k<\/jats:italic> nearest neighbors; (d) GP: the projection point of the compound on the line defined by its two nearest neighbors. We defined the applicability domain (AD) to decide to what an extent and under what circumstances the prediction is reliable. In the end, we developed a consensus model based on the predicted values of individual LLL models, yielding correlation coefficients R<jats:sup>2<\/jats:sup> of 0.712 on a test set containing 2,896 compounds.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Encouraged by the promising results, we expect that our consensus LLL model of LD<jats:sub>50<\/jats:sub> would become a useful tool for predicting acute toxicity. All models developed in this study are available via <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/www.dddc.ac.cn\/admetus\" ext-link-type=\"uri\">http:\/\/www.dddc.ac.cn\/admetus<\/jats:ext-link>.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1758-2946-6-26","type":"journal-article","created":{"date-parts":[[2014,5,16]],"date-time":"2014-05-16T05:03:25Z","timestamp":1400216605000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Estimation of acute oral toxicity in rat using local lazy learning"],"prefix":"10.1186","volume":"6","author":[{"given":"Jing","family":"Lu","sequence":"first","affiliation":[]},{"given":"Jianlong","family":"Peng","sequence":"additional","affiliation":[]},{"given":"Jinan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Qiancheng","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Bi","sequence":"additional","affiliation":[]},{"given":"Likun","family":"Gong","sequence":"additional","affiliation":[]},{"given":"Mingyue","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Xiaomin","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Weiliang","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Hualiang","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Kaixian","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2014,5,16]]},"reference":[{"key":"603_CR1","first-page":"300","volume-title":"Screening Methods in Pharmacology","author":"R Turner","year":"1965","unstructured":"Turner R: Acute toxicity: The determination of LD50. Screening Methods in Pharmacology. 1965, New York: Academic Press, 300-"},{"key":"603_CR2","first-page":"1","volume-title":"Regulation (EC) No 1907\/2006 of the European Parliament and of the Council of 18 December 2006 concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), establishing a European Chemicals Agency, amending Directive 1999\/45","author":"European Parliament and of council","year":"2006","unstructured":"European Parliament and of council: Regulation (EC) No 1907\/2006 of the European Parliament and of the Council of 18 December 2006 concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), establishing a European Chemicals Agency, amending Directive 1999\/45\/EC and repealing Council Regulation (EEC) No. 793\/93 and Commission Regulation (EC) No. 1488\/94 as well as Council Directive 76\/769\/EEC and Commission Directives 91\/155\/EEC, 93\/67\/EEC, 93\/105\/EC and 2000\/21\/EC. 2006, Official Journal of the European Union 396, 1-849."},{"key":"603_CR3","first-page":"115","volume":"2","author":"K Enslein","year":"1978","unstructured":"Enslein K: A toxicity estimation model. J Environ Pathol Toxicol. 1978, 2: 115-121.","journal-title":"J Environ Pathol Toxicol"},{"key":"603_CR4","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1177\/074823378900500210","volume":"5","author":"K Enslein","year":"1989","unstructured":"Enslein K, Lander TR, Tomb ME, Craig PN: A predictive model for estimating rat oral LD50 values. Toxicol Ind Health. 1989, 5: 261-387.","journal-title":"Toxicol Ind Health"},{"key":"603_CR5","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1080\/10629369908039170","volume":"10","author":"DV Eldred","year":"1999","unstructured":"Eldred DV, Jurs PC: Prediction of acute mammalian toxicity of organophosphorus pesticide compounds from molecular structure. SAR QSAR Environ Res. 1999, 10: 75-99. 10.1080\/10629369908039170.","journal-title":"SAR QSAR Environ Res"},{"key":"603_CR6","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1021\/tx050090r","volume":"19","author":"JX Guo","year":"2006","unstructured":"Guo JX, Wu JJ, Wright JB, Lushington GH: Mechanistic insight into acetylcholinesterase inhibition and acute toxicity of organophosphorus compounds: a molecular modeling study. Chem Res Toxicol. 2006, 19: 209-216. 10.1021\/tx050090r.","journal-title":"Chem Res Toxicol"},{"key":"603_CR7","doi-asserted-by":"publisher","first-page":"1913","DOI":"10.1021\/tx900189p","volume":"22","author":"H Zhu","year":"2009","unstructured":"Zhu H, Martin TM, Ye L, Sedykh A, Young DM, Tropsha A: Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure. Chem Res Toxicol. 2009, 22: 1913-1921. 10.1021\/tx900189p.","journal-title":"Chem Res Toxicol"},{"key":"603_CR8","volume-title":"Concepts and Applications of Molecular Similarity","author":"MA Johnson","year":"1990","unstructured":"Johnson MA, Maggiora GM: Concepts and Applications of Molecular Similarity. 1990, New York: John Wiley & Sons"},{"key":"603_CR9","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1021\/ci600299j","volume":"47","author":"H Yuan","year":"2007","unstructured":"Yuan H, Wang Y, Cheng Y: Local and global quantitative structure-activity relationship modeling and prediction for the baseline toxicity. J Chem Inf Model. 2007, 47: 159-169. 10.1021\/ci600299j.","journal-title":"J Chem Inf Model"},{"key":"603_CR10","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1002\/ps.2780150106","volume":"15","author":"GW Adamson","year":"1984","unstructured":"Adamson GW, Bawden D, Saggers DT: Quantitative structure-activity relationship studies of acute toxicity (LD50) in a large series of herbicidal benzimidazoles. Pestic Sci. 1984, 15: 31-39. 10.1002\/ps.2780150106.","journal-title":"Pestic Sci"},{"key":"603_CR11","unstructured":"Oral rat 50 percent lethal dose: [http:\/\/www.epa.gov\/nrmrl\/std\/qsar\/qsar.html] (accessed July 12, 2012)"},{"key":"603_CR12","unstructured":"Accelrys Toxicity Database. 2011, San Diego, CA: Accelrys Software Inc, .4"},{"key":"603_CR13","first-page":"353","volume":"43","author":"C Petterino","year":"2001","unstructured":"Petterino C, Paolo B: Toxicology of various anticoagulant rodenticides in animals. Vet Hum Toxicol. 2001, 43: 353-360.","journal-title":"Vet Hum Toxicol"},{"key":"603_CR14","unstructured":"Sybyl. St. Louis, MO: Tripos Inc, 63144\u20132913"},{"key":"603_CR15","unstructured":"AMPAC. Shawnee, KS: Semichem, Inc, 62216"},{"key":"603_CR16","unstructured":"COmprehensive DEscriptors for Structural and Statistical Analysis (CODESSA). Shawnee, KS: Semichem, Inc, 66216"},{"key":"603_CR17","unstructured":"Accelrys Discovery Studio. San Diego, CA: Accelrys Software Inc, 92121"},{"key":"603_CR18","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1021\/ci9800211","volume":"38","author":"P Willett","year":"1998","unstructured":"Willett P, Barnard JM, Downs GM: Chemical similarity searching. J Chem Inf Comput Sci. 1998, 38: 983-996. 10.1021\/ci9800211.","journal-title":"J Chem Inf Comput Sci"},{"key":"603_CR19","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1021\/ci100050t","volume":"50","author":"D Rogers","year":"2010","unstructured":"Rogers D, Hahn M: Extended-connectivity fingerprints. J Chem Inf Model. 2010, 50: 742-754. 10.1021\/ci100050t.","journal-title":"J Chem Inf Model"},{"key":"603_CR20","unstructured":"MDL Information Systems, Inc. 14600 Catalina Street, San Leandro, CA, 94577"},{"key":"603_CR21","unstructured":"Landrum G: RDKit: Open-Source Cheminformatics. [http:\/\/www.rdkit.org] (release 2013.03.2)"},{"key":"603_CR22","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1007\/s10822-005-9012-4","volume":"19","author":"J Liu","year":"2005","unstructured":"Liu J, Yang L, Li Y, Pan D, Hopfinger AJ: Prediction of plasma protein binding of drugs using Kier-Hall valence connectivity indices and 4D-fingerprint molecular similarity analyses. J Comput Aided Mol Des. 2005, 19: 567-783. 10.1007\/s10822-005-9012-4.","journal-title":"J Comput Aided Mol Des"},{"key":"603_CR23","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1016\/j.bmc.2005.08.035","volume":"14","author":"J Liu","year":"2006","unstructured":"Liu J, Yang L, Li Y, Pan D, Hopfinger AJ: Constructing plasma protein binding model based on a combination of cluster analysis and 4D-fingerprint molecular similarity analyses. Bioorg Med Chem. 2006, 14: 611-621. 10.1016\/j.bmc.2005.08.035.","journal-title":"Bioorg Med Chem"},{"key":"603_CR24","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1023\/A:1019154432472","volume":"26","author":"A Lipkus","year":"1999","unstructured":"Lipkus A: A proof of the triangle inequality for the Tanimoto distance. J Math Chem. 1999, 26: 263-265. 10.1023\/A:1019154432472.","journal-title":"J Math Chem"},{"key":"603_CR25","doi-asserted-by":"publisher","first-page":"1984","DOI":"10.1021\/ci060132x","volume":"46","author":"S Zhang","year":"2006","unstructured":"Zhang S, Golbraikh A, Oloff S, Kohn H, Tropsha A: A novel automated lazy learning QSAR (ALL-QSAR) approach: method development, applications, and virtual screening of chemical databases using validated ALL-QSAR models. J Chem Inf Model. 2006, 46: 1984-1995. 10.1021\/ci060132x.","journal-title":"J Chem Inf Model"},{"key":"603_CR26","doi-asserted-by":"publisher","first-page":"2713","DOI":"10.1021\/jm050260x","volume":"49","author":"S Zhang","year":"2006","unstructured":"Zhang S, Golbraikh A, Tropsha A: Development of quantitative structure-binding affinity relationship models based on novel geometrical chemical descriptors of the protein-ligand interfaces. J Med Chem. 2006, 49: 2713-2724. 10.1021\/jm050260x.","journal-title":"J Med Chem"},{"key":"603_CR27","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.1021\/ci700016d","volume":"47","author":"M Hewitt","year":"2007","unstructured":"Hewitt M, Cronin MT, Madden JC, Rowe PH, Johnson C, Obi A, Enoch SJ: Consensus QSAR models: do the benefits outweigh the complexity?. J Chem Inf Model. 2007, 47: 1460-1468. 10.1021\/ci700016d.","journal-title":"J Chem Inf Model"},{"key":"603_CR28","doi-asserted-by":"publisher","first-page":"766","DOI":"10.1021\/ci700443v","volume":"48","author":"H Zhu","year":"2008","unstructured":"Zhu H, Tropsha A, Fourches D, Varnek A, Papa E, Gramatica P, Oberg T, Dao P, Cherkasov A, Tetko IV: Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis. J Chem Inf Model. 2008, 48: 766-784. 10.1021\/ci700443v.","journal-title":"J Chem Inf Model"},{"key":"603_CR29","doi-asserted-by":"publisher","first-page":"2636","DOI":"10.1002\/jcc.21002","volume":"29","author":"J Li","year":"2008","unstructured":"Li J, Lei B, Liu H, Li S, Yao X, Liu M, Gramatica P: QSAR study of malonyl-CoA decarboxylase inhibitors using GA-MLR and a new strategy of consensus modeling. J Comput Chem. 2008, 29: 2636-2647. 10.1002\/jcc.21002.","journal-title":"J Comput Chem"},{"key":"603_CR30","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1177\/026119290503300209","volume":"33","author":"TI Netzeva","year":"2005","unstructured":"Netzeva TI, Worth A, Aldenberg T, Benigni R, Cronin MT, Gramatica P, Jaworska JS, Kahn S, Klopman G, Marchant CA, Myatt G, Nikolova-Jeliazkova N, Patlewicz GY, Perkins R, Roberts D, Schultz T, Stanton DW, van de Sandt JJ, Tong W, Veith G, Yang C: Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52. Altern Lab Anim. 2005, 33: 155-173.","journal-title":"Altern Lab Anim"},{"key":"603_CR31","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1177\/026119290503300508","volume":"33","author":"J Jaworska","year":"2005","unstructured":"Jaworska J, Nikolova-Jeliazkova N, Aldenberg T: QSAR applicabilty domain estimation by projection of the training set descriptor space: a review. Altern Lab Anim. 2005, 33: 445-459.","journal-title":"Altern Lab Anim"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1758-2946-6-26\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-6-26.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-6-26.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,2]],"date-time":"2021-09-02T04:12:57Z","timestamp":1630555977000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/1758-2946-6-26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,5,16]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,12]]}},"alternative-id":["603"],"URL":"https:\/\/doi.org\/10.1186\/1758-2946-6-26","relation":{},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,5,16]]},"assertion":[{"value":"28 March 2014","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 May 2014","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 May 2014","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"26"}}