Predicting Hydration Gibbs Energies of Natural Cyclodextrins Using BAR, ER and DFT Methods

preprint OA: closed CC-BY-4.0
📄 Open PDF Full text JSON View at publisher
AI-generated deep summary by claude@2026-07, 2026-07-05 · read from full text

The paper uses computational chemistry to predict hydration Gibbs energies for natural α-, β-, and γ-cyclodextrins, applying Bennett acceptance ratio and energy representation methods and also estimating hydration energies from DFT geometry optimization and frequency calculations in both gas and aqueous phases. It further analyzes hydrogen bonding patterns using molecular dynamics simulations. The main reported outputs are comparative hydration Gibbs energies across cyclodextrin types, alongside hydrogen-bonding information from simulation. The authors note the work is a preprint and has not been peer reviewed. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Full text 11,228 characters · extracted from preprint-html · click to expand
Predicting Hydration Gibbs Energies of Natural Cyclodextrins Using BAR, ER and DFT Methods | 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 Predicting Hydration Gibbs Energies of Natural Cyclodextrins Using BAR, ER and DFT Methods Masao Fujisawa, Tomonori Ohata, Hirohito Ikeda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9060605/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Cyclodextrins (CyDs) are nonreducing cyclic sugars consisting of a ring of glucose residues linked by a-1,4 bonds. CyDs can accommodate various types of guest molecules in their internal cavity, and their solubility is influenced by the cavity size and substituents. In this study, various computational approaches were used to determine hydration Gibbs energies of natural α-, β-, and γ-CyDs. Hydration Gibbs energies were calculated using the Bennett acceptance ratio and energy representation methods. In addition, hydration Gibbs energies were estimated based on geometry optimization and frequency calculations using density functional theory in both gas and aqueous phases. Furthermore, hydrogen bonding was analyzed through molecular dynamics simulations. Cyclodextrin Hydration Gibbs energy BAR ER DFT Hydrogen bond analysis Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers invited by journal 23 Mar, 2026 Editor assigned by journal 16 Mar, 2026 Submission checks completed at journal 15 Mar, 2026 First submitted to journal 15 Mar, 2026 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-9060605","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607101701,"identity":"cd89d9a3-3825-4250-887e-e18e2b2a6146","order_by":0,"name":"Masao Fujisawa","email":"data:image/png;base64,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","orcid":"","institution":"Kindai University","correspondingAuthor":true,"prefix":"","firstName":"Masao","middleName":"","lastName":"Fujisawa","suffix":""},{"id":607101705,"identity":"c822ea77-faad-47d1-aa11-566aa532b297","order_by":1,"name":"Tomonori Ohata","email":"","orcid":"","institution":"Fukuoka University","correspondingAuthor":false,"prefix":"","firstName":"Tomonori","middleName":"","lastName":"Ohata","suffix":""},{"id":607101710,"identity":"6dd8a272-bccb-4a97-9b8c-4717d282ae6f","order_by":2,"name":"Hirohito Ikeda","email":"","orcid":"","institution":"Fukuoka University","correspondingAuthor":false,"prefix":"","firstName":"Hirohito","middleName":"","lastName":"Ikeda","suffix":""}],"badges":[],"createdAt":"2026-03-07 20:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9060605/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9060605/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104835608,"identity":"f86a7aea-0e69-415f-9242-a9274f117e70","added_by":"auto","created_at":"2026-03-17 17:46:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":523583,"visible":true,"origin":"","legend":"","description":"","filename":"rev69708cc3697142a4b04cffd24fdf5ae9.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9060605/v1_covered_6277b06d-d997-4ae6-9fb7-1410186d3c5b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predicting Hydration Gibbs Energies of Natural Cyclodextrins Using BAR, ER and DFT Methods","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-chemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Chemistry](https://link.springer.com/journal/44371)","snPcode":"44371","submissionUrl":"https://submission.nature.com/new-submission/44371/3","title":"Discover Chemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cyclodextrin, Hydration Gibbs energy, BAR, ER, DFT, Hydrogen bond analysis","lastPublishedDoi":"10.21203/rs.3.rs-9060605/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9060605/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCyclodextrins (CyDs) are nonreducing cyclic sugars consisting of a ring of glucose residues linked by a-1,4 bonds. CyDs can accommodate various types of guest molecules in their internal cavity, and their solubility is influenced by the cavity size and substituents. In this study, various computational approaches were used to determine hydration Gibbs energies of natural α-, β-, and γ-CyDs. Hydration Gibbs energies were calculated using the Bennett acceptance ratio and energy representation methods. In addition, hydration Gibbs energies were estimated based on geometry optimization and frequency calculations using density functional theory in both gas and aqueous phases. Furthermore, hydrogen bonding was analyzed through molecular dynamics simulations.\u003c/p\u003e","manuscriptTitle":"Predicting Hydration Gibbs Energies of Natural Cyclodextrins Using BAR, ER and DFT Methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-17 13:28:52","doi":"10.21203/rs.3.rs-9060605/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-14T05:53:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T12:30:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135442895527362929609608064042195197518","date":"2026-05-07T06:07:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"103122016420316799511028605884450856910","date":"2026-05-06T19:33:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-23T08:32:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T17:19:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-15T05:27:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Chemistry","date":"2026-03-15T05:24:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-chemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Chemistry](https://link.springer.com/journal/44371)","snPcode":"44371","submissionUrl":"https://submission.nature.com/new-submission/44371/3","title":"Discover Chemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24c39f50-77f7-45ab-9628-1ec1557a705d","owner":[],"postedDate":"March 17th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-14T05:53:01+00:00","index":28,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T12:30:38+00:00","index":26,"fulltext":""},{"type":"reviewerAgreed","content":"135442895527362929609608064042195197518","date":"2026-05-07T06:07:27+00:00","index":25,"fulltext":""},{"type":"reviewerAgreed","content":"103122016420316799511028605884450856910","date":"2026-05-06T19:33:07+00:00","index":24,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T08:40:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-17 13:28:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9060605","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9060605","identity":"rs-9060605","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

References (12)

Source provenance

crossref
last seen: 2026-05-30T01:00:32.498764+00:00
europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-05-21T05:10:58.409756+00:00
License: CC-BY-4.0