A Paradigm Shift in Alzheimer's Research: Advanced Machine Learning Predictive Modeling of TDZD-8's Quantum Tunneling Efficacy in GSK3β Inhibition

A Paradigm Shift in Alzheimer's Research: Advanced Machine Learning Predictive Modeling of TDZD-8's Quantum Tunneling Efficacy in GSK3β Inhibition | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 27 May 2025 V1 Latest version Share on A Paradigm Shift in Alzheimer's Research: Advanced Machine Learning Predictive Modeling of TDZD-8's Quantum Tunneling Efficacy in GSK3β Inhibition Author : Arsh Jha 0009-0009-4767-8226 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174837856.61198713/v1 272 views 104 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This pioneering research represents a historic advancement in drug discovery by being the first to predict and report the quantum tunneling probability for TDZD-8, a selective GSK3β inhibitor, using sophisticated machine learning techniques. By integrating Convolutional Neural Networks (CNNs) with quantum mechanical principles, the study achieves highly accurate simulations of tunneling probabilities, revealing results within an optimal range crucial for therapeutic efficacy. This novel approach enhances the understanding of drug-target interactions and establishes a new paradigm in drug design, with significant implications for Alzheimer’s disease treatment. The integration of advanced predictive modeling with quantum mechanics marks a transformative step in the development of targeted therapies, offering a deeper insight into the molecular mechanisms underlying drug action. Supplementary Material File (official quantum tunneling research paper (1).pdf) Download 301.51 KB Information & Authors Information Version history V1 Version 1 27 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords alzheimer's disease convolutional neural networks (cnns) gsk3β inhibitor machine learning quantum tunneling tdzd-8 Authors Affiliations Arsh Jha 0009-0009-4767-8226 [email protected] North Carolina School of Science and Mathematics, North Carolina View all articles by this author Metrics & Citations Metrics Article Usage 272 views 104 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Arsh Jha. A Paradigm Shift in Alzheimer's Research: Advanced Machine Learning Predictive Modeling of TDZD-8's Quantum Tunneling Efficacy in GSK3β Inhibition. Authorea . 27 May 2025. DOI: https://doi.org/10.22541/au.174837856.61198713/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); Cited by Razieh Dashti, Fariba Safaei, Golfam Sadeghian, Seyyed Abed Hosseini, Milad Salimibani, Peptide-functionalized nanomaterials for controlled drug delivery and regenerative therapies in retinal diseases, Journal of Biomaterials Applications, 40 , 10, (1235-1262), (2025). https://doi.org/10.1177/08853282251395196 Crossref Loading... View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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