{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T17:21:34Z","timestamp":1787937694775,"version":"build-2784847793"},"reference-count":85,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100004156","name":"Mahidol University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004156","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Research Council of Thailand and Mahidol University","award":["N42A660380"],"award-info":[{"award-number":["N42A660380"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mol Divers"],"DOI":"10.1007\/s11030-026-11700-5","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T15:50:15Z","timestamp":1787932215000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Interpretable QSAR modelling for PPAR-\u03b3 agonist prediction by integrating a stacking strategy, docking, and MD simulations"],"prefix":"10.1007","author":[{"given":"Phasit","family":"Charoenkwan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ittipat","family":"Meewan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nalini","family":"Schaduangrat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Watshara","family":"Shoombuatong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,28]]},"reference":[{"issue":"6","key":"11700_CR1","doi-asserted-by":"publisher","first-page":"993","DOI":"10.1016\/j.cell.2005.11.026","volume":"123","author":"M Lehrke","year":"2005","unstructured":"Lehrke M, Lazar MA (2005) The many faces of PPARgamma. Cell 123(6):993\u2013999","journal-title":"Cell"},{"issue":"1","key":"11700_CR2","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1186\/s12933-021-01294-7","volume":"20","author":"L Nesti","year":"2021","unstructured":"Nesti L, Trico D, Mengozzi A, Natali A (2021) Rethinking pioglitazone as a cardioprotective agent: a new perspective on an overlooked drug. Cardiovasc Diabetol 20(1):109","journal-title":"Cardiovasc Diabetol"},{"key":"11700_CR3","doi-asserted-by":"publisher","first-page":"9530","DOI":"10.1038\/srep09530","volume":"5","author":"C Liu","year":"2015","unstructured":"Liu C et al (2015) Identification of a novel selective agonist of PPARgamma with no promotion of adipogenesis and less inhibition of osteoblastogenesis. Sci Rep 5:9530","journal-title":"Sci Rep"},{"key":"11700_CR4","doi-asserted-by":"publisher","first-page":"41487","DOI":"10.1038\/srep41487","volume":"7","author":"W Yi","year":"2017","unstructured":"Yi W et al (2017) Identification of a novel selective PPARgamma ligand with a unique binding mode and improved therapeutic profile in vitro. Sci Rep 7:41487","journal-title":"Sci Rep"},{"issue":"1","key":"11700_CR5","doi-asserted-by":"publisher","first-page":"19207","DOI":"10.1038\/s41598-025-03387-9","volume":"15","author":"AM Ibrahim","year":"2025","unstructured":"Ibrahim AM et al (2025) Design and synthesis of a novel quinoline thiazolidinedione hybrid as a potential antidiabetic PPARgamma modulator. Sci Rep 15(1):19207","journal-title":"Sci Rep"},{"key":"11700_CR6","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.737776","volume":"11","author":"T Chi","year":"2021","unstructured":"Chi T et al (2021) PPAR-gamma modulators as current and potential cancer treatments. Front Oncol 11:737776","journal-title":"Front Oncol"},{"issue":"Suppl 3","key":"11700_CR7","doi-asserted-by":"publisher","first-page":"S17","DOI":"10.1038\/sj.ijo.0802494","volume":"27","author":"DE Moller","year":"2003","unstructured":"Moller DE, Berger JP (2003) Role of PPARs in the regulation of obesity-related insulin sensitivity and inflammation. Int J Obes Relat Metab Disord 27(Suppl 3):S17-21","journal-title":"Int J Obes Relat Metab Disord"},{"issue":"6","key":"11700_CR8","doi-asserted-by":"publisher","first-page":"395","DOI":"10.4093\/dmj.2013.37.6.395","volume":"37","author":"C Corzo","year":"2013","unstructured":"Corzo C, Griffin PR (2013) Targeting the peroxisome proliferator-activated receptor-gamma to counter the inflammatory milieu in obesity. Diabetes Metab J 37(6):395\u2013403","journal-title":"Diabetes Metab J"},{"key":"11700_CR9","doi-asserted-by":"publisher","first-page":"473","DOI":"10.3389\/fendo.2018.00473","volume":"9","author":"X Ma","year":"2018","unstructured":"Ma X, Wang D, Zhao W, Xu L (2018) Deciphering the roles of PPARgamma in adipocytes via dynamic change of transcription complex. Front Endocrinol Lausanne 9:473","journal-title":"Front Endocrinol Lausanne"},{"issue":"11","key":"11700_CR10","doi-asserted-by":"publisher","first-page":"6102","DOI":"10.1073\/pnas.96.11.6102","volume":"96","author":"JL Oberfield","year":"1999","unstructured":"Oberfield JL et al (1999) A peroxisome proliferator-activated receptor gamma ligand inhibits adipocyte differentiation. Proc Natl Acad Sci U S A 96(11):6102\u20136106","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"3","key":"11700_CR11","doi-asserted-by":"publisher","first-page":"159","DOI":"10.4251\/wjgo.v2.i3.159","volume":"2","author":"Y Dai","year":"2010","unstructured":"Dai Y, Wang WH (2010) Peroxisome proliferator-activated receptor gamma and colorectal cancer. World J Gastrointest Oncol 2(3):159\u2013164","journal-title":"World J Gastrointest Oncol"},{"key":"11700_CR12","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2023.1184794","volume":"14","author":"J Sun","year":"2023","unstructured":"Sun J, Yu L, Qu X, Huang T (2023) The role of peroxisome proliferator-activated receptors in the tumor microenvironment, tumor cell metabolism, and anticancer therapy. Front Pharmacol 14:1184794","journal-title":"Front Pharmacol"},{"key":"11700_CR13","doi-asserted-by":"publisher","first-page":"4481354","DOI":"10.1155\/2023\/4481354","volume":"2023","author":"DH Li","year":"2023","unstructured":"Li DH, Liu XK, Tian XT, Liu F, Yao XJ, Dong JF (2023) PPARG: a promising therapeutic target in breast cancer and regulation by natural drugs. PPAR Res 2023:4481354","journal-title":"PPAR Res"},{"issue":"1","key":"11700_CR14","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1186\/s12885-024-11985-5","volume":"24","author":"L Schockel","year":"2024","unstructured":"Schockel L et al (2024) PPARG activation promotes the proliferation of colorectal cancer cell lines and enhances the antiproliferative effect of 5-fluorouracil. BMC Cancer 24(1):234","journal-title":"BMC Cancer"},{"issue":"5","key":"11700_CR15","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1038\/nm.3159","volume":"19","author":"M Ahmadian","year":"2013","unstructured":"Ahmadian M et al (2013) PPARgamma signaling and metabolism: the good, the bad and the future. Nat Med 19(5):557\u2013566","journal-title":"Nat Med"},{"key":"11700_CR16","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/818945","volume":"2009","author":"A Leonardini","year":"2009","unstructured":"Leonardini A, Laviola L, Perrini S, Natalicchio A, Giorgino F (2009) Cross-talk between PPARgamma and insulin signaling and modulation of insulin sensitivity. PPAR Res 2009:818945","journal-title":"PPAR Res"},{"key":"11700_CR17","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1146\/annurev-physiol-021909-135846","volume":"72","author":"JM Olefsky","year":"2010","unstructured":"Olefsky JM, Glass CK (2010) Macrophages, inflammation, and insulin resistance. Annu Rev Physiol 72:219\u2013246","journal-title":"Annu Rev Physiol"},{"issue":"10","key":"11700_CR18","doi-asserted-by":"publisher","first-page":"1258","DOI":"10.1016\/j.str.2007.07.014","volume":"15","author":"JB Bruning","year":"2007","unstructured":"Bruning JB et al (2007) Partial agonists activate PPARgamma using a helix 12 independent mechanism. Structure 15(10):1258\u20131271","journal-title":"Structure"},{"key":"11700_CR19","doi-asserted-by":"publisher","first-page":"3571","DOI":"10.1038\/ncomms4571","volume":"5","author":"TS Hughes","year":"2014","unstructured":"Hughes TS et al (2014) An alternate binding site for PPARgamma ligands. Nat Commun 5:3571","journal-title":"Nat Commun"},{"issue":"9","key":"11700_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2021.103052","volume":"24","author":"J Mao","year":"2021","unstructured":"Mao J et al (2021) Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models. iScience 24(9):103052","journal-title":"iScience"},{"key":"11700_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmgm.2024.108742","volume":"129","author":"S Haider","year":"2024","unstructured":"Haider S et al (2024) Uncovering PPAR-gamma agonists: an integrated computational approach driven by machine learning. J Mol Graph Model 129:108742","journal-title":"J Mol Graph Model"},{"issue":"3","key":"11700_CR22","doi-asserted-by":"publisher","first-page":"961","DOI":"10.1021\/acs.jpcb.5c06470","volume":"130","author":"Y Liu","year":"2026","unstructured":"Liu Y, Liu W, Na R, Zhao X (2026) Discovery of PPARgamma partial agonists for treatment of type 2 diabetes based on an integrated virtual screening strategy that combines fragment molecular orbital calculations, machine learning, molecular docking, interaction fingerprint filtering, and molecular dynamics simulations. J Phys Chem B 130(3):961\u2013979","journal-title":"J Phys Chem B"},{"key":"11700_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiolchem.2024.108142","volume":"112","author":"S Dawn","year":"2024","unstructured":"Dawn S et al (2024) Exploring fingerprints for antidiabetic therapeutics related to peroxisome proliferator-activated receptor gamma (PPARgamma) modulators: a chemometric modeling approach. Comput Biol Chem 112:108142","journal-title":"Comput Biol Chem"},{"issue":"4","key":"11700_CR24","doi-asserted-by":"publisher","first-page":"3305","DOI":"10.1007\/s11030-025-11118-5","volume":"29","author":"SA Amin","year":"2025","unstructured":"Amin SA, Sessa L, Gayen S, Piotto S (2025) PPARgamma modulator predictor (PGMP_v1): chemical space exploration and computational insights for enhanced type 2 diabetes mellitus management. Mol Divers 29(4):3305\u20133321","journal-title":"Mol Divers"},{"key":"11700_CR25","doi-asserted-by":"crossref","unstructured":"Pradhan T, Gupta O, Chawla G (2025) Rational in silico design of PPARgamma agonists for type 2 diabetes: an integrated study using pharmacophore modeling, 3D-QSAR, molecular docking, MD simulations, DFT, and toxicity prediction. Mol Divers","DOI":"10.1007\/s11030-025-11395-0"},{"key":"11700_CR26","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.cbpa.2019.10.003","volume":"56","author":"T Rodrigues","year":"2020","unstructured":"Rodrigues T, Bernardes GJL (2020) Machine learning for target discovery in drug development. Curr Opin Chem Biol 56:16\u201322","journal-title":"Curr Opin Chem Biol"},{"issue":"2","key":"11700_CR27","doi-asserted-by":"publisher","first-page":"2015","DOI":"10.1007\/s11030-025-11297-1","volume":"30","author":"M Adhish","year":"2026","unstructured":"Adhish M, Manjubala I (2026) PPGBioPred: a webserver for predicting the bioactivity of compounds against PPARgamma involved in the negative regulation of the Wnt\/beta-catenin signaling pathway. Mol Divers 30(2):2015\u20132036","journal-title":"Mol Divers"},{"issue":"5","key":"11700_CR28","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1080\/1062936X.2025.2514061","volume":"36","author":"SA Amin","year":"2025","unstructured":"Amin SA, Chakraborty G, Tarafdar R, Sessa L, Das I, Piotto S (2025) Structural insights and molecular profiling of a large set of diverse compounds targeting PPARgamma: from comprehensive cheminformatics approach to tool development. SAR QSAR Environ Res 36(5):443\u2013461","journal-title":"SAR QSAR Environ Res"},{"key":"11700_CR29","unstructured":"Trevisan V (2022) Using SHAP values to explain how your machine learning model works. vol. 2023, ed: Towards Data Science"},{"issue":"D1","key":"11700_CR30","doi-asserted-by":"publisher","first-page":"D930","DOI":"10.1093\/nar\/gky1075","volume":"47","author":"D Mendez","year":"2019","unstructured":"Mendez D et al (2019) ChEMBL: towards direct deposition of bioassay data. Nucleic Acids Res 47(D1):D930\u2013D940","journal-title":"Nucleic Acids Res"},{"key":"11700_CR31","unstructured":"RDKit: Open-source cheminformatics. ed."},{"issue":"6","key":"11700_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmb.2024.168853","volume":"437","author":"P Charoenkwan","year":"2025","unstructured":"Charoenkwan P, Chumnanpuen P, Schaduangrat N, Shoombuatong W (2025) Stack-AVP: a stacked ensemble predictor based on multi-view information for fast and accurate discovery of antiviral peptides. J Mol Biol 437(6):168853","journal-title":"J Mol Biol"},{"key":"11700_CR33","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.ymeth.2024.12.005","volume":"234","author":"P Charoenkwan","year":"2025","unstructured":"Charoenkwan P, Chumnanpuen P, Schaduangrat N, Shoombuatong W (2025) Deepstack-ACE: a deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides. Methods 234:131\u2013140","journal-title":"Methods"},{"issue":"1","key":"11700_CR34","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1186\/s12859-023-05463-1","volume":"24","author":"P Charoenkwan","year":"2023","unstructured":"Charoenkwan P, Kongsompong S, Schaduangrat N, Chumnanpuen P, Shoombuatong W (2023) TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides. BMC Bioinformatics 24(1):356","journal-title":"BMC Bioinformatics"},{"key":"11700_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2024.07.033","volume":"162","author":"P Charoenkwan","year":"2025","unstructured":"Charoenkwan P, Schaduangrat N, Manavalan B, Shoombuatong W (2025) M3S-ALG: improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy. Future Gener Comput Syst 162:107455","journal-title":"Future Gener Comput Syst"},{"issue":"8","key":"11700_CR36","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0290538","volume":"18","author":"P Charoenkwan","year":"2023","unstructured":"Charoenkwan P, Waramit S, Chumnanpuen P, Schaduangrat N, Shoombuatong W (2023) TROLLOPE: a novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus. PLoS ONE 18(8):e0290538","journal-title":"PLoS ONE"},{"issue":"1","key":"11700_CR37","first-page":"57","volume":"17","author":"MF Sanner","year":"1999","unstructured":"Sanner MF (1999) Python: a programming language for software integration and development. J Mol Graph Model 17(1):57\u201361","journal-title":"J Mol Graph Model"},{"key":"11700_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2024.101944","volume":"28","author":"J Adamczyk","year":"2024","unstructured":"Adamczyk J, Ludynia P (2024) Scikit-fingerprints: easy and efficient computation of molecular fingerprints in Python. SoftwareX 28:101944","journal-title":"SoftwareX"},{"issue":"1","key":"11700_CR39","doi-asserted-by":"publisher","first-page":"16435","DOI":"10.1038\/s41598-022-20143-5","volume":"12","author":"N Schaduangrat","year":"2022","unstructured":"Schaduangrat N, Anuwongcharoen N, Moni MA, Lio\u2019 P, Charoenkwan P, Shoombuatong W (2022) StackPR is a new computational approach for large-scale identification of progesterone receptor antagonists using the stacking strategy. Sci Rep 12(1):16435","journal-title":"Sci Rep"},{"issue":"6","key":"11700_CR40","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbab172","volume":"22","author":"P Charoenkwan","year":"2021","unstructured":"Charoenkwan P, Chiangjong W, Nantasenamat C, Hasan MM, Manavalan B, Shoombuatong W (2021) StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides. Brief Bioinform 22(6):bbab172","journal-title":"Brief Bioinform"},{"key":"11700_CR41","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.ymeth.2021.12.001","volume":"204","author":"P Charoenkwan","year":"2022","unstructured":"Charoenkwan P, Nantasenamat C, Hasan MM, Moni MA, Manavalan B, Shoombuatong W (2022) StackDPPIV: a novel computational approach for accurate prediction of dipeptidyl peptidase IV (DPP-IV) inhibitory peptides. Methods 204:189\u2013198","journal-title":"Methods"},{"key":"11700_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105704","author":"P Charoenkwan","year":"2022","unstructured":"Charoenkwan P, Schaduangrat N, Moni MA, Manavalan B, Shoombuatong W (2022) SAPPHIRE: a stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. Comput Biol Med (Oxf). https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105704","journal-title":"Comput Biol Med (Oxf)"},{"key":"11700_CR43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/ijms21072629","volume":"21","author":"P Charoenkwan","year":"2020","unstructured":"Charoenkwan P, Schaduangrat N, Nantasenamat C, Piacham T, Shoombuatong W (2020) iQSP: a sequence-based tool for the prediction and analysis of quorum sensing peptides via Chou\u2019s 5-steps rule and informative physicochemical properties. Int J Mol Sci 21:1","journal-title":"Int J Mol Sci"},{"key":"11700_CR44","first-page":"p. 176","volume-title":"Density estimation for statistics and data analysis","author":"BW Silverman","year":"1998","unstructured":"Silverman BW (1998) Density estimation for statistics and data analysis, 1st ed. Taylor and Francis Group, New York, p 176","edition":"1st ed"},{"key":"11700_CR45","unstructured":"Diener MJ (2010) Cohen's d"},{"issue":"1","key":"11700_CR46","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"YHY Benjamini","year":"1995","unstructured":"Benjamini YHY (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B Stat Methodol 57(1):289\u2013300","journal-title":"J R Stat Soc B Stat Methodol"},{"issue":"8","key":"11700_CR47","doi-asserted-by":"publisher","first-page":"1742","DOI":"10.1021\/ci200179y","volume":"51","author":"Y Hu","year":"2011","unstructured":"Hu Y, Stumpfe D, Bajorath J (2011) Lessons learned from molecular scaffold analysis. J Chem Inf Model 51(8):1742\u20131753","journal-title":"J Chem Inf Model"},{"issue":"15","key":"11700_CR48","doi-asserted-by":"publisher","first-page":"2887","DOI":"10.1021\/jm9602928","volume":"39","author":"GW Bemis","year":"1996","unstructured":"Bemis GW, Murcko MA (1996) The properties of known drugs. 1. Molecular frameworks. J Med Chem 39(15):2887\u20132893","journal-title":"J Med Chem"},{"issue":"D1","key":"11700_CR49","doi-asserted-by":"publisher","first-page":"D691","DOI":"10.1093\/nar\/gkae1093","volume":"53","author":"EF Poynton","year":"2025","unstructured":"Poynton EF et al (2025) The natural products atlas 3.0: extending the database of microbially derived natural products. Nucleic Acids Res 53(D1):D691\u2013D699","journal-title":"Nucleic Acids Res"},{"key":"11700_CR50","doi-asserted-by":"publisher","DOI":"10.1186\/1758-2946-3-33","volume":"3","author":"NM O'Boyle","year":"2011","unstructured":"O\u2019Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open babel: an open chemical toolbox. J Cheminform 3:33","journal-title":"J Cheminform"},{"issue":"1","key":"11700_CR51","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1186\/s13321-023-00721-z","volume":"15","author":"N Schaduangrat","year":"2023","unstructured":"Schaduangrat N, Anuwongcharoen N, Charoenkwan P, Shoombuatong W (2023) DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists. J Cheminform 15(1):50","journal-title":"J Cheminform"},{"issue":"1","key":"11700_CR52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-022-20143-5","volume":"12","author":"N Schaduangrat","year":"2022","unstructured":"Schaduangrat N, Anuwongcharoen N, Moni MA, Lio P, Charoenkwan P, Shoombuatong W (2022) StackPR is a new computational approach for large-scale identification of progesterone receptor antagonists using the stacking strategy. Sci Rep 12(1):1\u201316","journal-title":"Sci Rep"},{"issue":"1","key":"11700_CR53","doi-asserted-by":"publisher","first-page":"22994","DOI":"10.1038\/s41598-023-50393-w","volume":"13","author":"N Schaduangrat","year":"2023","unstructured":"Schaduangrat N, Homdee N, Shoombuatong W (2023) StackER: a novel SMILES-based stacked approach for the accelerated and efficient discovery of ERalpha and ERbeta antagonists. Sci Rep 13(1):22994","journal-title":"Sci Rep"},{"issue":"3","key":"11700_CR54","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1016\/j.str.2005.01.010","volume":"13","author":"MF Sanner","year":"2005","unstructured":"Sanner MF (2005) A component-based software environment for visualizing large macromolecular assemblies. Structure 13(3):447\u2013462","journal-title":"Structure"},{"issue":"8","key":"11700_CR55","doi-asserted-by":"publisher","first-page":"3891","DOI":"10.1021\/acs.jcim.1c00203","volume":"61","author":"J Eberhardt","year":"2021","unstructured":"Eberhardt J, Santos-Martins D, Tillack AF, Forli S (2021) AutoDock Vina 1.2.0: new docking methods, expanded force field, and Python bindings. J Chem Inf Model 61(8):3891\u20133898","journal-title":"J Chem Inf Model"},{"issue":"21","key":"11700_CR56","doi-asserted-by":"publisher","first-page":"5980","DOI":"10.1016\/j.bmcl.2013.08.029","volume":"23","author":"MD Shultz","year":"2013","unstructured":"Shultz MD (2013) Setting expectations in molecular optimizations: strengths and limitations of commonly used composite parameters. Bioorg Med Chem Lett 23(21):5980\u20135991","journal-title":"Bioorg Med Chem Lett"},{"issue":"5","key":"11700_CR57","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1038\/nrd3701","volume":"11","author":"MM Hann","year":"2012","unstructured":"Hann MM, Keseru GM (2012) Finding the sweet spot: the role of nature and nurture in medicinal chemistry. Nat Rev Drug Discov 11(5):355\u2013365","journal-title":"Nat Rev Drug Discov"},{"issue":"11","key":"11700_CR58","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1038\/nrd2445","volume":"6","author":"PD Leeson","year":"2007","unstructured":"Leeson PD, Springthorpe B (2007) The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov 6(11):881\u2013890","journal-title":"Nat Rev Drug Discov"},{"issue":"3","key":"11700_CR59","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1038\/nrd3367","volume":"10","author":"MP Gleeson","year":"2011","unstructured":"Gleeson MP, Hersey A, Montanari D, Overington J (2011) Probing the links between in vitro potency, ADMET and physicochemical parameters. Nat Rev Drug Discov 10(3):197\u2013208","journal-title":"Nat Rev Drug Discov"},{"issue":"2","key":"11700_CR60","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1038\/nrd4163","volume":"13","author":"AL Hopkins","year":"2014","unstructured":"Hopkins AL, Keseru GM, Leeson PD, Rees DC, Reynolds CH (2014) The role of ligand efficiency metrics in drug discovery. Nat Rev Drug Discov 13(2):105\u2013121","journal-title":"Nat Rev Drug Discov"},{"issue":"6","key":"11700_CR61","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1021\/cn100008c","volume":"1","author":"TT Wager","year":"2010","unstructured":"Wager TT, Hou X, Verhoest PR, Villalobos A (2010) Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci 1(6):435\u2013449","journal-title":"ACS Chem Neurosci"},{"key":"11700_CR62","unstructured":"S R (2025) Desmond molecular dynamics system. In: D. E. S. Research, Ed., ed. New York: Maestro-Desmond Interoperability Tools, Schr\u00f6dinger"},{"issue":"8","key":"11700_CR63","doi-asserted-by":"publisher","first-page":"3696","DOI":"10.1021\/acs.jctc.5b00255","volume":"11","author":"JA Maier","year":"2015","unstructured":"Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C (2015) ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput 11(8):3696\u20133713","journal-title":"J Chem Theory Comput"},{"issue":"3","key":"11700_CR64","doi-asserted-by":"publisher","first-page":"1983","DOI":"10.1021\/acs.jctc.8b01039","volume":"15","author":"D Vassetti","year":"2019","unstructured":"Vassetti D, Pagliai M, Procacci P (2019) Assessment of GAFF2 and OPLS-AA general force fields in combination with the water models TIP3P, SPCE, and OPC3 for the solvation free energy of druglike organic molecules. J Chem Theory Comput 15(3):1983\u20131995","journal-title":"J Chem Theory Comput"},{"issue":"16","key":"11700_CR65","doi-asserted-by":"publisher","first-page":"1623","DOI":"10.1002\/jcc.10128","volume":"23","author":"A Jakalian","year":"2002","unstructured":"Jakalian A, Jack DB, Bayly CI (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem 23(16):1623\u20131641","journal-title":"J Comput Chem"},{"key":"11700_CR66","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmcr.2024.100160","author":"AMS Basak","year":"2024","unstructured":"Basak AMS, Matore BW, Roy PP, Singh J (2024) Thiazolidinedione an auspicious scaffold as PPAR-\u03b3 agonist: its possible mechanism to manoeuvre against insulin resistant diabetes mellitus. Eur J Med Chem Rep. https:\/\/doi.org\/10.1016\/j.ejmcr.2024.100160","journal-title":"Eur J Med Chem Rep"},{"key":"11700_CR67","doi-asserted-by":"publisher","DOI":"10.1016\/j.metabol.2024.156097","volume":"163","author":"F Chen","year":"2025","unstructured":"Chen F, Ma L, Liu Q, Zhou Z, Yi W (2025) Recent advances and therapeutic applications of PPARgamma-targeted ligands based on the inhibition mechanism of Ser273 phosphorylation. Metabolism 163:156097","journal-title":"Metabolism"},{"issue":"22","key":"11700_CR68","doi-asserted-by":"publisher","first-page":"23705","DOI":"10.1021\/acs.jmedchem.5c02192","volume":"68","author":"JL King","year":"2025","unstructured":"King JL, Smithers L, Vrielink A, Lesterhuis WJ, Piggott MJ (2025) A new era for PPARgamma: covalent ligands and therapeutic applications. J Med Chem 68(22):23705\u201323750","journal-title":"J Med Chem"},{"key":"11700_CR69","doi-asserted-by":"publisher","DOI":"10.1038\/srep34792","volume":"6","author":"D Capelli","year":"2016","unstructured":"Capelli D et al (2016) Structural basis for PPAR partial or full activation revealed by a novel ligand binding mode. Sci Rep 6:34792","journal-title":"Sci Rep"},{"issue":"1","key":"11700_CR70","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.str.2011.10.018","volume":"20","author":"TS Hughes","year":"2012","unstructured":"Hughes TS et al (2012) Ligand and receptor dynamics contribute to the mechanism of graded PPARgamma agonism. Structure 20(1):139\u2013150","journal-title":"Structure"},{"key":"11700_CR71","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11030-025-11297-1","volume":"30","author":"M Adhish","year":"2025","unstructured":"Adhish M, Manjubala I (2025) PPGBioPred: a webserver for predicting the bioactivity of compounds against PPAR\u03b3 involved in the negative regulation of the Wnt\/\u03b2-catenin signaling pathway. Mol Divers 30:1\u201322","journal-title":"Mol Divers"},{"issue":"11","key":"11700_CR72","doi-asserted-by":"publisher","first-page":"2941","DOI":"10.1021\/acs.jnatprod.6b00801","volume":"79","author":"Z Cheng","year":"2016","unstructured":"Cheng Z et al (2016) Versiquinazolines A-K, fumiquinazoline-type alkaloids from the gorgonian-derived fungus Aspergillus versicolor LZD-14-1. J Nat Prod 79(11):2941\u20132952","journal-title":"J Nat Prod"},{"issue":"4","key":"11700_CR73","doi-asserted-by":"publisher","first-page":"1082","DOI":"10.1021\/acs.jnatprod.9b01096","volume":"83","author":"CJ Li","year":"2020","unstructured":"Li CJ et al (2020) Potential antidiabetic fumiquinazoline alkaloids from the marine-derived fungus Scedosporium apiospermum F41\u20131. J Nat Prod 83(4):1082\u20131091","journal-title":"J Nat Prod"},{"issue":"4","key":"11700_CR74","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1021\/acs.orglett.8b04107","volume":"21","author":"H Liu","year":"2019","unstructured":"Liu H et al (2019) Cytorhizins A-D, four highly structure-combined benzophenones from the endophytic fungus Cytospora rhizophorae. Org Lett 21(4):1063\u20131067","journal-title":"Org Lett"},{"issue":"6698","key":"11700_CR75","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1038\/25931","volume":"395","author":"RT Nolte","year":"1998","unstructured":"Nolte RT et al (1998) Ligand binding and co-activator assembly of the peroxisome proliferator-activated receptor-gamma. Nature 395(6698):137\u2013143","journal-title":"Nature"},{"key":"11700_CR76","doi-asserted-by":"publisher","first-page":"34661","DOI":"10.1038\/srep34661","volume":"6","author":"Y Jin","year":"2016","unstructured":"Jin Y, Han Y, Khadka DB, Zhao C, Lee KY, Cho WJ (2016) Discovery of isoquinolinoquinazolinones as a novel class of potent PPARgamma antagonists with anti-adipogenic effects. Sci Rep 6:34661","journal-title":"Sci Rep"},{"issue":"1","key":"11700_CR77","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1007\/s12039-020-01813-1","volume":"132","author":"L Santos-Ballardo","year":"2020","unstructured":"Santos-Ballardo L et al (2020) Synthesis, biological evaluation and molecular docking of 3-substituted quinazoline-2,4(1H, 3H)-diones. J Chem Sci 132(1):100","journal-title":"J Chem Sci"},{"key":"11700_CR78","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1016\/j.fitote.2018.08.021","volume":"130","author":"C Qi","year":"2018","unstructured":"Qi C et al (2018) Terrusnolides A-D, new butenolides with anti-inflammatory activities from an endophytic Aspergillus from Tripterygium wilfordii. Fitoterapia 130:134\u2013139","journal-title":"Fitoterapia"},{"issue":"3","key":"11700_CR79","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1016\/j.bbrc.2017.03.106","volume":"486","author":"D Wang","year":"2017","unstructured":"Wang D et al (2017) Activation of PPAR\u03b3 inhibits pro-inflammatory cytokines production by upregulation of miR-124 in\u00a0vitro and in\u00a0vivo. Biochem Biophys Res Commun 486(3):726\u2013731","journal-title":"Biochem Biophys Res Commun"},{"issue":"8","key":"11700_CR80","doi-asserted-by":"publisher","first-page":"1067","DOI":"10.1136\/gut.2005.089946","volume":"55","author":"G Rogler","year":"2006","unstructured":"Rogler G (2006) Significance of anti-inflammatory effects of PPARgamma agonists? Gut 55(8):1067\u20131069","journal-title":"Gut"},{"issue":"1","key":"11700_CR81","doi-asserted-by":"publisher","first-page":"E174","DOI":"10.1152\/ajpendo.90632.2008","volume":"297","author":"AH Remels","year":"2009","unstructured":"Remels AH et al (2009) PPARgamma inhibits NF-kappaB-dependent transcriptional activation in skeletal muscle. Am J Physiol Endocrinol Metab 297(1):E174\u2013E183","journal-title":"Am J Physiol Endocrinol Metab"},{"issue":"1","key":"11700_CR82","doi-asserted-by":"publisher","first-page":"18390","DOI":"10.1038\/s41598-024-68992-6","volume":"14","author":"S Cheng","year":"2024","unstructured":"Cheng S et al (2024) Paeonol alleviates ulcerative colitis by modulating PPAR-gamma and nuclear factor-kappaB activation. Sci Rep 14(1):18390","journal-title":"Sci Rep"},{"issue":"24","key":"11700_CR83","doi-asserted-by":"publisher","first-page":"13919","DOI":"10.1073\/pnas.241410198","volume":"98","author":"HE Xu","year":"2001","unstructured":"Xu HE et al (2001) Structural determinants of ligand binding selectivity between the peroxisome proliferator-activated receptors. Proc Natl Acad Sci USA 98(24):13919\u201313924","journal-title":"Proc Natl Acad Sci USA"},{"key":"11700_CR84","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/816856","volume":"2015","author":"AJ Kroker","year":"2015","unstructured":"Kroker AJ, Bruning JB (2015) Review of the structural and dynamic mechanisms of PPARgamma partial agonism. PPAR Res 2015:816856","journal-title":"PPAR Res"},{"issue":"4","key":"11700_CR85","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1210\/me.2002-0217","volume":"17","author":"JP Berger","year":"2003","unstructured":"Berger JP et al (2003) Distinct properties and advantages of a novel peroxisome proliferator-activated protein [gamma] selective modulator. Mol Endocrinol 17(4):662\u2013676","journal-title":"Mol Endocrinol"}],"container-title":["Molecular Diversity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11030-026-11700-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11030-026-11700-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11030-026-11700-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T17:03:11Z","timestamp":1787936591000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11030-026-11700-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,28]]},"references-count":85,"alternative-id":["11700"],"URL":"https:\/\/doi.org\/10.1007\/s11030-026-11700-5","relation":{},"ISSN":["1573-501X"],"issn-type":[{"value":"1573-501X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,28]]},"assertion":[{"value":"1 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Conflict of interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}