Computational Screening of Natural Products Against SOD1 to Identify Potential ALS Therapeutics

Computational Screening of Natural Products Against SOD1 to Identify Potential ALS Therapeutics | 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 Article Computational Screening of Natural Products Against SOD1 to Identify Potential ALS Therapeutics Naveed Iqbal, Mahmoud Kandeel, Saba Beigh, Fatima Rasheed, Muhammad Nasir Iqbal, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8879349/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract Neurodegenerative diseases are becoming more common and encompass multiple disorders that result in the loss of neurons, aging of the brain, and eventually lead to death. Amyotrophic lateral sclerosis (ALS) is the most common and devastating neurological disease driven by a gradual loss of motor neurons. It is essential to use cutting-edge technology in drug discovery as conventional methods become slower and more costly. In silico strategies provide a reliable, quick, and affordable alternative to the clumsy in vitro methods to improve our understanding of how drugs affect protein structure and related activities. Natural products have strong anti-inflammatory and antioxidant activities. In the present work, we test natural compounds against the SOD1 protein to combat the ALS disease. After identification of the protein, we performed structure-based pharmacophore screening and ADMET analyses of the top hit compounds based on RMSD. Molecular docking and molecular dynamics simulation analyses were applied, and the top two novel compounds reported against ALS showed effective binding properties. The dynamics simulation experiments were conducted at a 100 ns scale to identify the protein's behavior toward the recognized two ligands, Scytonine and Raocyclamide_A. The novel compounds Scytonine and Raocyclamide_A are non-toxic and meet the requirements of ADMET and BBB likeness parameters. The findings from this study will aid researchers in understanding the chemical compounds that interact with our target SOD1 protein. Furthermore, a future path in the realm of drug discovery may involve studying these molecules in vivo/vitro will help to design and test therapeutic medications. Biological sciences/Computational biology and bioinformatics Biological sciences/Drug discovery Biological sciences/Neuroscience Full Text Additional Declarations No competing interests reported. Supplementary Files S1.csv S2.csv Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Mar, 2026 Reviews received at journal 09 Mar, 2026 Reviews received at journal 04 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers agreed at journal 01 Mar, 2026 Reviews received at journal 01 Mar, 2026 Reviewers agreed at journal 01 Mar, 2026 Reviewers agreed at journal 28 Feb, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers invited by journal 26 Feb, 2026 Editor assigned by journal 26 Feb, 2026 Editor invited by journal 26 Feb, 2026 Submission checks completed at journal 25 Feb, 2026 First submitted to journal 25 Feb, 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. 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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-8879349","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":600105087,"identity":"22ed5cc3-bf94-4b7b-952e-345ddd246faf","order_by":0,"name":"Naveed Iqbal","email":"","orcid":"","institution":"Islamia University of Bahawalpur","correspondingAuthor":false,"prefix":"","firstName":"Naveed","middleName":"","lastName":"Iqbal","suffix":""},{"id":600105088,"identity":"6640ec16-25b4-4139-b014-f6910eeaef81","order_by":1,"name":"Mahmoud Kandeel","email":"","orcid":"","institution":"King Faisal 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