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However, docking large molecules such as peptides remains challenging, while the docking of large non-peptidic biopolymers is still insufficiently explored. Existing tools often exhibit limitations in both accuracy and computational efficiency when applied to longer peptides or other polymers. Moreover, although generative deep learning and machine learning approaches have shown promise, they still frequently lack robust ranking metrics, resulting in suboptimal performance. To address these limitations, we developed STELLAR (Score-Tuning for Efficient Ranking of Large Ligands using an Accurate and Refined Docking Configuration), a workflow designed to enable efficient and accurate docking of highly flexible long-chain biopolymers exceeding 10 subunits. STELLAR implements a fragment-based strategy, decomposing the biopolymer into smaller units for individual docking, followed by recomposition into full-length structures. It also includes optimized algorithms for handling long-chain biopolymers. The pipeline integrates structural optimization steps using tools such as GNINA, RDKit, and GROMACS, ensuring physically realistic poses. STELLAR achieved RMSD values below 5 \u00c5 in validation experiments using benchmark complexes from Propedia and the Protein Data Bank (PDB). It offers a faster and more efficient alternative to several state-of-the-art tools across a range of peptide lengths. Additionally, it scales linearly in computational time, runs primarily on CPUs with minimal GPU usage, avoids reliance on generative approximations, provides an accurate metric for ligand ranking, and reduces computational cost compared to similar tools. Its design also supports high-throughput screening of linear polymer\u2013protein interactions by efficiently reducing the complexity associated with high conformational flexibility.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c00987","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T10:01:52Z","timestamp":1789552912000},"page":"12645-12666","source":"Crossref","is-referenced-by-count":0,"title":["STELLAR: A Fragment-Based\nDocking Workflow for Highly\nFlexible Long-Chain Biopolymers"],"prefix":"10.1021","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1251-8072","authenticated-orcid":true,"given":"Alejandro","family":"Rodri\u0301guez-Marti\u0301nez","sequence":"first","affiliation":[{"name":"UCAM Universidad Cato\u0301lica de Murcia (UCAM) , , ,","place":["Murcia, Spain, 30107"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9970-4950","authenticated-orcid":true,"given":"Jochem","family":"Nelen","sequence":"additional","affiliation":[{"name":"UCAM Universidad Cato\u0301lica de Murcia (UCAM) , , ,","place":["Murcia, Spain, 30107"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2735-4859","authenticated-orcid":true,"given":"Miguel","family":"Carmena-Barguen\u0303o","sequence":"additional","affiliation":[{"name":"UCAM Universidad Cato\u0301lica de Murcia (UCAM) , , ,","place":["Murcia, Spain, 30107"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5029-3089","authenticated-orcid":true,"given":"Carlos","family":"Marti\u0301nez-Corte\u0301s","sequence":"additional","affiliation":[{"name":"UCAM Universidad Cato\u0301lica de Murcia (UCAM) , , ,","place":["Murcia, Spain, 30107"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4468-7898","authenticated-orcid":true,"given":"Horacio","family":"Pe\u0301rez-Sa\u0301nchez","sequence":"additional","affiliation":[{"name":"UCAM Universidad Cato\u0301lica de Murcia (UCAM) , , ,","place":["Murcia, Spain, 30107"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,9,16]]},"reference":[{"issue":"11","key":"2026101208072793100_cit1","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1007\/s40273-021-01065-y","article-title":"How Much Does It Cost to Research and Develop a New\nDrug? 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(accessed July 30, 2026)."},{"issue":"D1","key":"2026101208072793100_cit63","doi-asserted-by":"publisher","first-page":"D488","DOI":"10.1093\/nar\/gkac1077","article-title":"RCSB Protein\nData Bank (RCSB.Org): Delivery of Experimentally-Determined PDB Structures\nalongside One Million Computed Structure Models of Proteins from Artificial\nIntelligence\/Machine Learning","volume":"51","author":"Burley","year":"2023","journal-title":"Nucleic Acids\nRes."},{"issue":"1","key":"2026101208072793100_cit64","doi-asserted-by":"publisher","DOI":"10.1186\/1752-153X-2-5","article-title":"Pybel: A Python Wrapper for the OpenBabel\nCheminformatics Toolkit","volume":"2","author":"O\u2019Boyle","year":"2008","journal-title":"Chem. Central J."},{"issue":"4","key":"2026101208072793100_cit65","doi-asserted-by":"publisher","first-page":"2353","DOI":"10.3390\/ai5040116","article-title":"SIBILA: Automated\nMachine-Learning-Based\nDevelopment of Interpretable Machine-Learning Models on High-Performance\nComputing Platforms","volume":"5","author":"Banegas-Luna","year":"2024","journal-title":"AI"},{"issue":"12","key":"2026101208072793100_cit66","doi-asserted-by":"publisher","first-page":"916","DOI":"10.1038\/nchembio.707","article-title":"Structural Basis of P38\u03b1 Regulation\nby Hematopoietic Tyrosine Phosphatase","volume":"7","author":"Francis","year":"2011","journal-title":"Nat.\nChem. Biol."},{"issue":"8","key":"2026101208072793100_cit67","doi-asserted-by":"publisher","first-page":"704","DOI":"10.1038\/nsmb.2861","article-title":"Allosteric Enhancement\nof MAP Kinase P38\u03b1\u2019s Activity and Substrate Selectivity\nby Docking Interactions","volume":"21","author":"Tokunaga","year":"2014","journal-title":"Nat. Struct Mol. Biol."},{"issue":"204","key":"2026101208072793100_cit68","doi-asserted-by":"publisher","DOI":"10.1126\/scisignal.2002241","article-title":"A Distinct\nInteraction Mode Revealed\nby the Crystal Structure of the Kinase P38\u03b1 with the MAPK Binding\nDomain of the Phosphatase MKP5","volume":"4","author":"Zhang","year":"2011","journal-title":"Sci. Signaling"},{"issue":"2","key":"2026101208072793100_cit69","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1038\/35000065","article-title":"A Conserved Docking\nMotif in MAP Kinases Common to Substrates, Activators and Regulators","volume":"2","author":"Tanoue","year":"2000","journal-title":"Nat. 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