Consolidated octanol/water partition coefficients: Combining multiple estimates from different methods to reduce uncertainties in log KOW

Consolidated octanol/water partition coefficients: Combining multiple estimates from different methods to reduce uncertainties in log KOW | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Consolidated octanol/water partition coefficients: Combining multiple estimates from different methods to reduce uncertainties in log K OW Monika Nendza, Verena Kosfeld, Christian Schlechtriem This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4669937/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Mar, 2025 Read the published version in Environmental Sciences Europe → Version 1 posted 16 You are reading this latest preprint version Abstract Background: The octanol/water partition coefficient ( K OW ) is a key parameter for assessing the fate and effects of chemicals. It is a metric of their hydrophobicity, related to uptake and accumulation in organisms and specific tissues, and distribution in water, soil and sediments. The log K OW can be determined experimentally, more often it is calculated. Variability may be due to properties of the substances, different experimental methods, or different computational approaches with different domains of applicability. The objective of the present study is to derive coherent log K OW estimates with known variability by (1) estimating multiple log K OW values by different methods for diverse chemicals to exemplify their variabilities, (2) analysing the variabilities of log K OW estimates by underlying methods and for different chemical classes, and (3) recommending approaches to obtain reliable and robust log K OW estimates for hazard and risk assessment. Results: Comparative analyses were based on 239 case study chemicals representing diverse chemical classes, such as POPs, PCB, PAH, siloxanes, flame retardants, PFAS, pesticides, pharmaceuticals, surfactants, etc. The variability of up to 35 log K OW values per substance, determined experimentally or estimated by different computational approaches, is 1 log unit and more across the entire log K OW range from 8. No systematic pattern is evident. Different methods for deriving log K OW perform sometimes better and sometimes worse for different chemicals. None of the methods (experimental or computational) is consistently superior and any method can be the worst. Conclusions: For scientifically valid and reproducible log K OW estimates with known variability, we recommend a weight-of-evidence (WoE) or averaging approach combining multiple estimates. Consolidated log K OW , being the mean of at least 5 valid data obtained by different independent methods (experimental and computational), are a pragmatic way to deal with the variability and uncertainty of individual results. While this approach does not solve any of the problems about “correctly” determining log K OW , it does limit the bias due to individual erroneous estimates. Consolidated log K OW are robust and reliable measures of hydrophobicity, with variability mostly below 0.2 log units. Lipophilicity log P calculation hydrophobicity QSAR variability uncertainty weight-of-evidence (WoE) aquatic and terrestrial bioaccumulation applicability domain consensus modelling Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Mar, 2025 Read the published version in Environmental Sciences Europe → Version 1 posted Editorial decision: Revision requested 22 Sep, 2024 Reviews received at journal 20 Sep, 2024 Reviews received at journal 20 Sep, 2024 Reviews received at journal 28 Aug, 2024 Reviewers agreed at journal 12 Aug, 2024 Reviewers agreed at journal 12 Aug, 2024 Reviewers agreed at journal 12 Aug, 2024 Reviews received at journal 12 Aug, 2024 Reviewers agreed at journal 28 Jul, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviewers agreed at journal 20 Jul, 2024 Reviewers invited by journal 20 Jul, 2024 Editor assigned by journal 16 Jul, 2024 Submission checks completed at journal 16 Jul, 2024 First submitted to journal 01 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4669937","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":335007519,"identity":"efe44457-1ab3-43c6-85c0-2b4e42aae8be","order_by":0,"name":"Monika Nendza","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYJACCQYGGwY+BuYGZgg/gYGBh7CWNAY2BkawFiAnmSgth0nQYs7ee/Dmj5rz8kAtbdKFO+rq+NnzDzC8qcCtxbLnXLKFxLHbhm0gLTPPHJaQ7HnMwDjnDG4tBjdyzCQM2G4ztsk/bJPmbTsgYXAjmYGZtw2PlvtvzCQS/p2zB9vC21YnYQ/W8g+fLTxmEgfbDiRCtTBLGEiAtDTg0XImx9iysS85Gail2Zq37bDkjDOPDQ7OOYZHy/Ezhjd/fLOz7WdgPngb6DB+/vbEhw/e1ODWgh0cIFXDKBgFo2AUjAJUAADcdUqoG53cxQAAAABJRU5ErkJggg==","orcid":"","institution":"Analytical Laboratory","correspondingAuthor":true,"prefix":"","firstName":"Monika","middleName":"","lastName":"Nendza","suffix":""},{"id":335007521,"identity":"689d7fe4-0d5e-4e89-a96d-a2a0503f6f09","order_by":1,"name":"Verena Kosfeld","email":"","orcid":"","institution":"Fraunhofer-IME","correspondingAuthor":false,"prefix":"","firstName":"Verena","middleName":"","lastName":"Kosfeld","suffix":""},{"id":335007524,"identity":"66670cac-163c-4f42-bf73-cd3fe1159285","order_by":2,"name":"Christian Schlechtriem","email":"","orcid":"","institution":"Fraunhofer-IME","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Schlechtriem","suffix":""}],"badges":[],"createdAt":"2024-07-01 19:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4669937/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4669937/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12302-025-01072-2","type":"published","date":"2025-03-18T15:57:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79120398,"identity":"7245f69b-4576-4a26-af28-49c5913440ee","added_by":"auto","created_at":"2025-03-24 16:06:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1727859,"visible":true,"origin":"","legend":"","description":"","filename":"consolidatedlogKow.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4669937/v1_covered_ac266677-66c6-42ec-bf7c-b97c8c864aef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eConsolidated octanol/water partition coefficients: Combining multiple estimates from different methods to reduce uncertainties in log \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/em\u003e\u003csub\u003e\u003cstrong\u003eOW\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-sciences-europe","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eseu","sideBox":"Learn more about [Environmental Sciences Europe](http://enveurope.springeropen.com)","snPcode":"12302","submissionUrl":"https://submission.nature.com/new-submission/12302/3","title":"Environmental Sciences Europe","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lipophilicity, log P calculation, hydrophobicity, QSAR, variability, uncertainty, weight-of-evidence (WoE), aquatic and terrestrial bioaccumulation, applicability domain, consensus modelling ","lastPublishedDoi":"10.21203/rs.3.rs-4669937/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4669937/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The octanol/water partition coefficient (\u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e) is a key parameter for assessing the fate and effects of chemicals. It is a metric of their hydrophobicity, related to uptake and accumulation in organisms and specific tissues, and distribution in water, soil and sediments. The log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e can be determined experimentally, more often it is calculated. Variability may be due to properties of the substances, different experimental methods, or different computational approaches with different domains of applicability.\u003c/p\u003e\n\u003cp\u003eThe objective of the present study is to derive coherent log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e estimates with known variability by (1) estimating multiple log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e values by different methods for diverse chemicals to exemplify their variabilities, (2) analysing the variabilities of log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e estimates by underlying methods and for different chemical classes, and (3) recommending approaches to obtain reliable and robust log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e estimates for hazard and risk assessment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Comparative analyses were based on 239 case study chemicals representing diverse chemical classes, such as POPs, PCB, PAH, siloxanes, flame retardants, PFAS, pesticides, pharmaceuticals, surfactants, etc. The variability of up to 35 log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e values per substance, determined experimentally or estimated by different computational approaches, is 1 log unit and more across the entire log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e range from \u0026lt; 0 to \u0026gt; 8. No systematic pattern is evident. Different methods for deriving log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e perform sometimes better and sometimes worse for different chemicals. None of the methods (experimental or computational) is consistently superior and any method can be the worst.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e For scientifically valid and reproducible log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e estimates with known variability, we recommend a weight-of-evidence (WoE) or averaging approach combining multiple estimates. Consolidated log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e, being the mean of at least 5 valid data obtained by different independent methods (experimental and computational), are a pragmatic way to deal with the variability and uncertainty of individual results. While this approach does not solve any of the problems about “correctly” determining log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e, it does limit the bias due to individual erroneous estimates. Consolidated log \u003cem\u003eK\u003c/em\u003e\u003csub\u003eOW\u003c/sub\u003e are robust and reliable measures of hydrophobicity, with variability mostly below 0.2 log units.\u003c/p\u003e","manuscriptTitle":"Consolidated octanol/water partition coefficients: Combining multiple estimates from different methods to reduce uncertainties in log KOW","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-08 14:41:54","doi":"10.21203/rs.3.rs-4669937/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-22T08:24:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-20T21:03:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-20T06:41:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-28T19:46:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308795002318757062485430992882271970315","date":"2024-08-12T15:22:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279818461794984329133728054444162825875","date":"2024-08-12T14:04:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1793472168223614109703991794341335529","date":"2024-08-12T13:11:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-12T11:45:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58198217443279442212874177686937248817","date":"2024-07-28T18:13:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189737593423619629834021827520529861825","date":"2024-07-22T15:51:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143171141973759161822005694588414501951","date":"2024-07-22T08:15:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229219517637303325825419059905345623657","date":"2024-07-20T08:28:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-20T06:18:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-16T12:21:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-16T12:20:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Sciences Europe","date":"2024-07-01T18:59:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-sciences-europe","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eseu","sideBox":"Learn more about [Environmental Sciences Europe](http://enveurope.springeropen.com)","snPcode":"12302","submissionUrl":"https://submission.nature.com/new-submission/12302/3","title":"Environmental Sciences Europe","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98291391-4e6f-4026-8a60-d65e874cf8d2","owner":[],"postedDate":"August 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-24T15:59:33+00:00","versionOfRecord":{"articleIdentity":"rs-4669937","link":"https://doi.org/10.1186/s12302-025-01072-2","journal":{"identity":"environmental-sciences-europe","isVorOnly":false,"title":"Environmental Sciences Europe"},"publishedOn":"2025-03-18 15:57:05","publishedOnDateReadable":"March 18th, 2025"},"versionCreatedAt":"2024-08-08 14:41:54","video":"","vorDoi":"10.1186/s12302-025-01072-2","vorDoiUrl":"https://doi.org/10.1186/s12302-025-01072-2","workflowStages":[]},"version":"v1","identity":"rs-4669937","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4669937","identity":"rs-4669937","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}