Structure-Activity Relationship (SAR) as a Weapon Against Chemoresistance in Pancreatic Cancer

Structure-Activity Relationship (SAR) as a Weapon Against Chemoresistance in Pancreatic Cancer | 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 Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed.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. 7 January 2026 V1 Latest version Share on Structure-Activity Relationship (SAR) as a Weapon Against Chemoresistance in Pancreatic Cancer Author : Md Abubakar 0009-0003-2865-5551 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176779129.97728222/v1 154 views 59 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most morbid malignancies with drug resistance to chemotherapy as an alarming challenge. Structure-Activity relationship (SAR) approaches have emerged as useful computational tools to predict and design novel chemotherapeutic agents that would overcome the resistance mechanisms. This review compiles recent advances in SAR based methodologies over the last five years, applied to research in PDAC’s drug resistance and evaluates computational approaches, experimental validations and translational potential. Recent SAR studies have shown progress in three main avenues: ligand-based methods using QSAR, 3D-QSAR and pharmacophore modelling; structure-based approaches integrating molecular docking with binding site analysis; and machine learning (ML) approaches utilizing artificial intelligence (AI); to combat the ever-increasing fatality of pancreatic cancer. However, limitations and drawbacks exist in these methods which include issues in validation with small dataset, risks of overfitting in ML models, restricted applicability domains and significant gaps in translation between computational predictions and clinical outcomes. More so, most SAR studies have not yet explored the pharmacokinetic properties, effects of tumor microenvironment (TME) and stem cell targeting approaches. The field of SAR is nevertheless advancing towards integration of multi-omics data, improvement of experimental validation by using pre-clinical models; combination of SAR with nanomedicine delivery systems and development of AI-powered personalized therapeutic strategies which target specific resistance mechanisms. Supplementary Material File (sar in pdac.docx) Download 2.33 MB Information & Authors Information Version history V1 Version 1 07 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Md Abubakar 0009-0003-2865-5551 [email protected] Jawaharlal Institute of Postgraduate Medical Education and Research View all articles by this author Metrics & Citations Metrics Article Usage 154 views 59 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Md Abubakar. Structure-Activity Relationship (SAR) as a Weapon Against Chemoresistance in Pancreatic Cancer. Authorea . 07 January 2026. DOI: https://doi.org/10.22541/au.176779129.97728222/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 . 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