Comparative Assessment of Physics-Based In Silico Methods to Calculate Relative Solubilities

Comparative Assessment of Physics-Based In Silico Methods to Calculate Relative Solubilities | 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 Comparative Assessment of Physics-Based In Silico Methods to Calculate Relative Solubilities Adiran Garaizar Suarez, Andreas H. Göller, Michael E. Beck, Sadra Ol Gheta Kashef, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4896360/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Oct, 2024 Read the published version in Journal of Computer-Aided Molecular Design → Version 1 posted 10 You are reading this latest preprint version Abstract Relative solubilities, i.e. whether a given molecule is more soluble in one solvent compared to others, is a critical parameter for pharmaceutical and agricultural formulation development and chemical synthesis, material science, and environmental chemistry. In silico predictions of this crucial variable can help reducing experiments, waste of solvents and synthesis optimization. In this study, we evaluate the performance of different physics-based methods for predicting relative solubilities. Our assessment involves quantum mechanics-based COSMO-RS and molecular dynamics-based free energy methods using OPLS4, the open-source openFF Sage, and GAFF force fields, spanning over 200 solvent-solute combinations. Our investigation highlights the important role of compound multimerization, an effect which must be accounted for to obtain accurate relative solubility predictions. The performance landscape of these methods is varied, with significant differences in precision depending on both the method used and the solute considered, thereby offering an improved understanding of the predictive power of physics-based methods in chemical research. Full Text Additional Declarations No competing interests reported. Supplementary Files RelSolMdCosmoSuppl.docx Cite Share Download PDF Status: Published Journal Publication published 29 Oct, 2024 Read the published version in Journal of Computer-Aided Molecular Design → Version 1 posted Editorial decision: Revision requested 17 Sep, 2024 Reviews received at journal 16 Sep, 2024 Reviews received at journal 12 Sep, 2024 Reviewers agreed at journal 05 Sep, 2024 Reviewers agreed at journal 03 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers invited by journal 02 Sep, 2024 Editor assigned by journal 02 Sep, 2024 Submission checks completed at journal 13 Aug, 2024 First submitted to journal 11 Aug, 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. 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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-4896360","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350878906,"identity":"11692e2f-98c0-4658-9757-ce6c989c5d99","order_by":0,"name":"Adiran Garaizar Suarez","email":"","orcid":"","institution":"Bayer AG","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adiran","middleName":"Garaizar","lastName":"Suarez","suffix":""},{"id":350878907,"identity":"862b571d-1d4e-46f8-a2fe-976ea93d4d5b","order_by":1,"name":"Andreas H. 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