{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:13:33Z","timestamp":1786122813841,"version":"build-2736575974"},"reference-count":45,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T00:00:00Z","timestamp":1786060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Qatar Research Development and Innovation Council","award":["UREP31-188-3-051"],"award-info":[{"award-number":["UREP31-188-3-051"]}]},{"name":"Qatar Research Development and Innovation Council","award":["ARG01-0601-230451"],"award-info":[{"award-number":["ARG01-0601-230451"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Mol. Sci.","IJMS"],"abstract":"<jats:p>Triple-negative breast cancer (TNBC) is the most clinically aggressive subtype of breast cancer, characterized by the absence of targetable hormone receptors and HER2 amplification, significantly constraining treatment choices. Estrogen Receptor Beta (ER\u03b2) has emerged as a biologically relevant yet underutilized target in TNBC, with its re-expression linked to tumor suppression and improved prognosis, prompting the development of selective ER\u03b2 modulators as a precision therapeutic approach. We introduce ER\u03b2-Score, an interpretable machine learning scoring system developed using a curated dataset of 1699 ER\u03b2 bioactive chemicals obtained from ChEMBL, characterized by 39 physicochemical and three-dimensional molecular descriptors. After implementing scaffold-disjoint train\/test partitioning to avert structural data leakage, a Gradient Boosting Classifier, fine-tuned through Bayesian hyperparameter optimization, attained in five-fold cross-validation a Precision\u2013Recall AUC (Area Under the Curve) of 0.891, a ROC-AUC (Receiver Operating Characteristic) of 0.888, a Matthews Correlation Coefficient of 0.664, an F1-score of 0.838, and a balanced accuracy of 0.831; on the scaffold-disjoint hold-out test set it attained a Precision\u2013Recall AUC of 0.905, a ROC-AUC of 0.864, and a Matthews Correlation Coefficient of 0.578, indicating strong and balanced discrimination between active and inactive ER\u03b2 modulators. We note explicitly that this scaffold-disjoint hold-out constitutes internal validation, since it derives from the same curated ChEMBL workflow used for model development, and it is therefore reported throughout as scaffold-disjoint internal validation rather than as independent external validation. The applicability domain boundaries were established using a k-nearest-neighbor Tanimoto-similarity method with ECFP4 (Extended-Connectivity Fingerprint with a Diameter of 4) fingerprints, offering a quantitative confidence metric that identifies structurally new molecules beyond the model\u2019s reliable prediction range. External validation against independent Tox21 ER\u03b2 bioassay data confirmed genuine, statistically significant predictive signal (ROC-AUC = 0.71) while revealing reduced sensitivity for structurally novel active compounds. The model was subsequently used for extensive virtual screening of natural product and drug-like compound libraries, with prioritized candidates undergoing structure-based molecular docking against the ER\u03b2 co-crystal structure (PDB: 7XWQ) using Smina, facilitating a comprehensive evaluation of hits based on both ligand and structural properties. To enhance accessibility, the complete pipeline was implemented as an open-access interactive web application utilizing Streamlit, enabling researchers to input any SMILES string and obtain, in real time, an activity prediction with a probability score, applicability domain classification, Lipinski drug-likeness assessment, interactive three-dimensional visualization of protein\u2013ligand interactions, and on-demand docking within the ER\u03b2 active site.<\/jats:p>","DOI":"10.3390\/ijms27167089","type":"journal-article","created":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T11:44:53Z","timestamp":1786103093000},"page":"7089","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ER\u03b2-Score: An Interpretable Machine Learning-Based Scoring Function and Web Server for Estrogen Receptor \u03b2-Guided Drug Discovery in Triple-Negative Breast Cancer"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9754-9097","authenticated-orcid":false,"given":"Abbas","family":"Khan","sequence":"first","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7222-6776","authenticated-orcid":false,"given":"Muhammad Ammar","family":"Zahid","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1304-5939","authenticated-orcid":false,"given":"Walid","family":"Kouidri","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2769-3508","authenticated-orcid":false,"given":"Osama Aboubakr","family":"Mohamed","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1323-2053","authenticated-orcid":false,"given":"Ahmed Mohammad","family":"Gharaibeh","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ladun Ibrahim","family":"Mohamed","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1618-7794","authenticated-orcid":false,"given":"Amani Anwar","family":"Al-Mansori","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6373-2629","authenticated-orcid":false,"given":"Mohamed Haitham","family":"Elsayed","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6318-8707","authenticated-orcid":false,"given":"Anwar","family":"Mohammad","sequence":"additional","affiliation":[{"name":"Precision Health Analysis Unit, Translational Research, Dasman Diabetes Institute, Dasman 15462, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2408-552X","authenticated-orcid":false,"given":"Ameera","family":"Al-Jabiry","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Earth Sciences, College of Arts and Science, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6748-3663","authenticated-orcid":false,"given":"Mohanad","family":"Shkoor","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Earth Sciences, College of Arts and Science, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0548-429X","authenticated-orcid":false,"given":"Raed M.","family":"Al-Zoubi","sequence":"additional","affiliation":[{"name":"Surgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha P.O. Box 3050, Qatar"},{"name":"Department of Biomedical Sciences, College of Health Sciences, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"},{"name":"Department of Chemistry, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8363-1582","authenticated-orcid":false,"given":"Abdelali","family":"Agouni","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha P.O. Box 2713, Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,7]]},"reference":[{"key":"ref_1","first-page":"7","article-title":"Cancer statistics, 2018","volume":"68","author":"Siegel","year":"2018","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","first-page":"394","article-title":"Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"CA Cancer J. Clin."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6537","DOI":"10.2147\/CMAR.S300869","article-title":"Prognostic factors in hormone receptor-positive\/human epidermal growth factor receptor 2-negative (Hr+\/her2\u2013) advanced breast cancer: A systematic literature review","volume":"13","author":"Carter","year":"2021","journal-title":"Cancer Manag. 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