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From ChEMBL database 1217 unique compounds were retrieved which were analyzed by:\n                    <jats:bold>\n                      <jats:italic>i<\/jats:italic>\n                    <\/jats:bold>\n                    . conventional 2D\u2010QSAR (Quantitative Structure\u2010Activity Relationship) with Dragon descriptors and molecular fingerprints,\n                    <jats:bold>\n                      <jats:italic>ii<\/jats:italic>\n                    <\/jats:bold>\n                    . Transformer\u2010CNN, leveraging SMILES augmentation. Morgan fingerprint\u2010based model with random forest classifier algorithm produced the best predictive model with strong Matthews correlation coefficient (MCC). Although the descriptor\u2010based model had lower predictive quality, it provided important insights into the structural features of the ligands through permutation and SHAP analyses. Contour maps for fingerprint\u2010based model specify favourable regions for lead optimization. 85 new compounds from ChEMBL were deployed as validation set; retrieving more than 80% balanced accuracy, confirming model robustness. This model was incorporated in Streamlit\u2010based FXR PREDICTOR, a user\u2010friendly application for virtual screening.\n                  <\/jats:p>","DOI":"10.1002\/slct.202503774","type":"journal-article","created":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T22:16:28Z","timestamp":1768688188000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Toward Development of \u201cFXR PREDICTOR\u201d: A Web\u2010Based Application for\u00a0Estimating Biological Activity of Chemical Compounds Toward Farnesoid X Receptor"],"prefix":"10.1002","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4818-9047","authenticated-orcid":false,"given":"Amit Kumar","family":"Halder","sequence":"first","affiliation":[{"name":"Dr. B. C. 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