{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T05:51:35Z","timestamp":1775713895854,"version":"3.50.1"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003725","name":"the National Research Foundation of Korea","doi-asserted-by":"crossref","award":["RS-2023-00208567"],"award-info":[{"award-number":["RS-2023-00208567"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Comput Aided Mol Des"],"DOI":"10.1007\/s10822-026-00803-8","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T02:32:25Z","timestamp":1775701945000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Computational framework to quantify synergistic ligand activity in insulin secretion and resistance pathways in type 2 diabetes"],"prefix":"10.1007","volume":"40","author":[{"given":"Junyu","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Xunbin","family":"Wei","sequence":"additional","affiliation":[]},{"given":"Meiling","family":"Lui","sequence":"additional","affiliation":[]},{"given":"Sunmin","family":"Park","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,4,9]]},"reference":[{"issue":"1","key":"803_CR1","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1038\/s41392-024-01951-9","volume":"9","author":"X Lu","year":"2024","unstructured":"Lu X et al (2024) Type 2 diabetes mellitus in adults: pathogenesis, prevention and therapy. Signal Transduct Target Therapy 9(1):262","journal-title":"Signal Transduct Target Therapy"},{"issue":"3","key":"803_CR2","doi-asserted-by":"publisher","first-page":"130","DOI":"10.4239\/wjd.v14.i3.130","volume":"14","author":"PV Dludla","year":"2023","unstructured":"Dludla PV et al (2023) Pancreatic \u03b2-cell dysfunction in type 2 diabetes: implications of inflammation and oxidative stress. World J Diabetes 14(3):130\u2013146","journal-title":"World J Diabetes"},{"issue":"2","key":"803_CR3","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1074\/jbc.M508307200","volume":"281","author":"S Park","year":"2006","unstructured":"Park S et al (2006) Exendin-4 uses Irs2 signaling to mediate pancreatic beta cell growth and function. J Biol Chem 281(2):1159\u20131168","journal-title":"J Biol Chem"},{"issue":"1","key":"803_CR4","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1038\/s41392-024-01931-z","volume":"9","author":"Z Zheng","year":"2024","unstructured":"Zheng Z et al (2024) Glucagon-like peptide-1 receptor: mechanisms and advances in therapy. Signal Transduct Target Therapy 9(1):234","journal-title":"Signal Transduct Target Therapy"},{"issue":"S3","key":"803_CR5","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1111\/dom.15663","volume":"26","author":"CJ Bailey","year":"2024","unstructured":"Bailey CJ (2024) Metformin: therapeutic profile in the treatment of type 2 diabetes. Diabetes Obes Metab 26(S3):3\u201319","journal-title":"Diabetes Obes Metab"},{"key":"803_CR6","doi-asserted-by":"publisher","first-page":"1244432","DOI":"10.3389\/fendo.2023.1244432","volume":"14","author":"Z Xie","year":"2023","unstructured":"Xie Z et al (2023) Comparison of the efficacy and safety of 10 glucagon-like peptide-1 receptor agonists as add-on to metformin in patients with type 2 diabetes: a systematic review. Front Endocrinol 14:1244432","journal-title":"Front Endocrinol"},{"issue":"3","key":"803_CR7","doi-asserted-by":"publisher","first-page":"e30532","DOI":"10.1002\/jcb.30532","volume":"125","author":"A Gupta","year":"2024","unstructured":"Gupta A, Purohit R (2024) Identification of potent BRD4-BD1 inhibitors using classical and steered molecular dynamics based free energy analysis. J Cell Biochem 125(3):e30532","journal-title":"J Cell Biochem"},{"key":"803_CR8","doi-asserted-by":"publisher","first-page":"138580","DOI":"10.1016\/j.ijbiomac.2024.138580","volume":"287","author":"A Daroch","year":"2025","unstructured":"Daroch A, Purohit R (2025) MDbDMRP: a novel molecular descriptor-based computational model to identify drug-miRNA relationships. Int J Biol Macromol 287:138580","journal-title":"Int J Biol Macromol"},{"issue":"2","key":"803_CR9","doi-asserted-by":"publisher","first-page":"306","DOI":"10.3390\/nu14020306","volume":"14","author":"S Rocha","year":"2022","unstructured":"Rocha S et al (2022) An in silico and an in vitro inhibition analysis of glycogen phosphorylase by flavonoids, styrylchromones, and pyrazoles. Nutrients 14(2):306","journal-title":"Nutrients"},{"key":"803_CR10","doi-asserted-by":"publisher","first-page":"1550158","DOI":"10.3389\/fphar.2025.1550158","volume":"16","author":"Q An","year":"2025","unstructured":"An Q et al (2025) New strategies to enhance the efficiency and precision of drug discovery. Front Pharmacol 16:1550158","journal-title":"Front Pharmacol"},{"issue":"7","key":"803_CR11","doi-asserted-by":"publisher","first-page":"3309","DOI":"10.1021\/acs.jcim.5c00135","volume":"65","author":"J Zhou","year":"2025","unstructured":"Zhou J et al (2025) Multitarget natural compounds for ischemic stroke treatment: integration of deep learning prediction and experimental validation. J Chem Inf Model 65(7):3309\u20133323","journal-title":"J Chem Inf Model"},{"issue":"10","key":"803_CR12","doi-asserted-by":"publisher","first-page":"11755","DOI":"10.1021\/acsomega.3c09171","volume":"9","author":"Firdos","year":"2024","unstructured":"Firdos et al (2024) (Re-)viewing role of intracellular glucose beyond extracellular regulation of glucose-stimulated insulin secretion by pancreatic cells. ACS Omega 9(10):11755\u201311768","journal-title":"ACS Omega"},{"issue":"1","key":"803_CR13","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.1038\/s41467-023-36680-0","volume":"14","author":"Y Zhang","year":"2023","unstructured":"Zhang Y et al (2023) THADA inhibition in mice protects against type 2 diabetes mellitus by improving pancreatic \u03b2-cell function and preserving \u03b2-cell mass. Nat Commun 14(1):1020","journal-title":"Nat Commun"},{"issue":"1","key":"803_CR14","doi-asserted-by":"publisher","first-page":"e2944","DOI":"10.1002\/dmrr.2944","volume":"34","author":"DS Kim","year":"2018","unstructured":"Kim DS et al (2018) High genetic risk scores for impaired insulin secretory capacity doubles the risk for type 2 diabetes in Asians and is exacerbated by Western-type diets. Diab\/Metab Res Rev 34(1):e2944","journal-title":"Diab\/Metab Res Rev"},{"key":"803_CR15","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1016\/j.csbj.2022.12.028","volume":"21","author":"G Minadakis","year":"2023","unstructured":"Minadakis G et al (2023) PathIN: an integrated tool for the visualization of pathway interaction networks. Comput Struct Biotechnol J 21:378\u2013387","journal-title":"Comput Struct Biotechnol J"},{"issue":"2","key":"803_CR16","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1021\/acs.jproteome.2c00651","volume":"22","author":"NT Doncheva","year":"2023","unstructured":"Doncheva NT et al (2023) Cytoscape stringApp 2.0: analysis and visualization of heterogeneous biological networks. J Proteome Res 22(2):637\u2013646","journal-title":"J Proteome Res"},{"issue":"12","key":"803_CR17","doi-asserted-by":"publisher","first-page":"10374","DOI":"10.1021\/acs.jmedchem.4c00838","volume":"67","author":"V Lembo","year":"2024","unstructured":"Lembo V, Bottegoni G (2024) Systematic investigation of dual-target-directed ligands. J Med Chem 67(12):10374\u201310385","journal-title":"J Med Chem"},{"issue":"1","key":"803_CR18","doi-asserted-by":"publisher","first-page":"7946","DOI":"10.1038\/s41467-024-52060-8","volume":"15","author":"L Isigkeit","year":"2024","unstructured":"Isigkeit L et al (2024) Automated design of multi-target ligands by generative deep learning. Nat Commun 15(1):7946","journal-title":"Nat Commun"},{"issue":"4","key":"803_CR19","doi-asserted-by":"publisher","first-page":"e61007","DOI":"10.1371\/journal.pone.0061007","volume":"8","author":"T Kalliokoski","year":"2013","unstructured":"Kalliokoski T et al (2013) Comparability of mixed IC\u2085\u2080 data - a statistical analysis. PLoS ONE 8(4):e61007","journal-title":"PLoS ONE"},{"issue":"12","key":"803_CR20","doi-asserted-by":"publisher","first-page":"4651","DOI":"10.1021\/acs.jcim.4c00825","volume":"64","author":"R Bhatt","year":"2024","unstructured":"Bhatt R, Koes DR, Durrant JD (2024) CENsible: interpretable insights into small-molecule binding with context explanation networks. J Chem Inf Model 64(12):4651\u20134660","journal-title":"J Chem Inf Model"},{"issue":"2","key":"803_CR21","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.cels.2019.01.003","volume":"8","author":"CT Meyer","year":"2019","unstructured":"Meyer CT et al (2019) Quantifying drug combination synergy along potency and efficacy axes. Cell Syst 8(2):97\u2013108e16","journal-title":"Cell Syst"},{"issue":"1","key":"803_CR22","first-page":"44","volume":"11","author":"L Zhong","year":"2024","unstructured":"Zhong L et al (2024) Network pharmacology and subsequent experimental validation reveal the synergistic myocardial protection mechanism of Salvia miltiorrhiza Bge. and Carthamus tinctorius L. J Tradit Chin Med Sci 11(1):44\u201354","journal-title":"J Tradit Chin Med Sci"},{"issue":"11","key":"803_CR23","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1016\/j.tips.2019.08.008","volume":"40","author":"P Sen","year":"2019","unstructured":"Sen P, Saha A, Dixit NM (2019) You cannot have your synergy and efficacy too. Trends Pharmacol Sci 40(11):811\u2013817","journal-title":"Trends Pharmacol Sci"},{"issue":"1","key":"803_CR24","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.metabol.2009.06.026","volume":"59","author":"S Park","year":"2010","unstructured":"Park S, Hong SM, Ahn IS (2010) Exendin-4 and exercise improve hepatic glucose homeostasis by promoting insulin signaling in diabetic rats. Metabolism 59(1):123\u2013133","journal-title":"Metabolism"},{"issue":"2","key":"803_CR25","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1097\/FJC.0000000000000481","volume":"70","author":"Q Fu","year":"2017","unstructured":"Fu Q et al (2017) Cross-talk between insulin signaling and G protein-coupled receptors. J Cardiovasc Pharmacol 70(2):74\u201386","journal-title":"J Cardiovasc Pharmacol"},{"issue":"1","key":"803_CR26","doi-asserted-by":"publisher","first-page":"e50128","DOI":"10.1371\/journal.pone.0050128","volume":"8","author":"H-S Kim","year":"2013","unstructured":"Kim H-S et al (2013) PPAR-\u03b3 activation increases insulin secretion through the up-regulation of the free fatty acid receptor GPR40 in pancreatic \u03b2-cells. PLoS ONE 8(1):e50128","journal-title":"PLoS ONE"},{"key":"803_CR27","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/j.jnutbio.2015.09.013","volume":"27","author":"S Park","year":"2016","unstructured":"Park S, Kim DS, Kang S (2016) Vitamin D deficiency impairs glucose-stimulated insulin secretion and increases insulin resistance by reducing PPAR-\u03b3 expression in nonobese Type 2 diabetic rats. J Nutr Biochem 27:257\u2013265","journal-title":"J Nutr Biochem"},{"issue":"2","key":"803_CR28","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1093\/ndt\/gfu405","volume":"31","author":"J Karalliedde","year":"2014","unstructured":"Karalliedde J, Gnudi L (2014) Diabetes mellitus, a complex and heterogeneous disease, and the role of insulin resistance as a determinant of diabetic kidney disease. Nephrol Dialysis Transpl 31(2):206\u2013213","journal-title":"Nephrol Dialysis Transpl"},{"issue":"15","key":"803_CR29","doi-asserted-by":"publisher","first-page":"2413","DOI":"10.1093\/bioinformatics\/btx162","volume":"33","author":"A Ianevski","year":"2017","unstructured":"Ianevski A et al (2017) SynergyFinder: a web application for analyzing drug combination dose-response matrix data. Bioinformatics 33(15):2413\u20132415","journal-title":"Bioinformatics"},{"key":"803_CR30","doi-asserted-by":"publisher","first-page":"106799","DOI":"10.1016\/j.jff.2025.106799","volume":"128","author":"PC Situmorang","year":"2025","unstructured":"Situmorang PC et al (2025) Harnessing phytochemicals to combat diabetes: insights into molecular pathways and therapeutic advances. J Funct Foods 128:106799","journal-title":"J Funct Foods"},{"issue":"18","key":"803_CR31","doi-asserted-by":"publisher","first-page":"1801","DOI":"10.2174\/1568026615666150506144814","volume":"15","author":"A Speck-Planche","year":"2015","unstructured":"Speck-Planche A, Cordeiro MN (2015) Multi-target QSAR approaches for modeling protein inhibitors. Simultaneous prediction of activities against biomacromolecules present in gram-negative bacteria. Curr Top Med Chem 15(18):1801\u20131813","journal-title":"Curr Top Med Chem"},{"issue":"1","key":"803_CR32","doi-asserted-by":"publisher","first-page":"14892","DOI":"10.1038\/ncomms14892","volume":"8","author":"W Cai","year":"2017","unstructured":"Cai W et al (2017) Domain-dependent effects of insulin and IGF-1 receptors on signalling and gene expression. Nat Commun 8(1):14892","journal-title":"Nat Commun"},{"issue":"11","key":"803_CR33","doi-asserted-by":"publisher","first-page":"1879","DOI":"10.3390\/buildings15111879","volume":"15","author":"E Medaa","year":"2025","unstructured":"Medaa E et al (2025) The synergy and accumulation model for analysis (SAMA): a novel approach to transforming risk analysis in construction with a focus on the deepwater horizon disaster case. Buildings 15(11):1879","journal-title":"Buildings"},{"issue":"W1","key":"803_CR34","doi-asserted-by":"publisher","first-page":"W739","DOI":"10.1093\/nar\/gkac382","volume":"50","author":"A Ianevski","year":"2022","unstructured":"Ianevski A, Giri AK, Aittokallio T (2022) SynergyFinder 3.0: an interactive analysis and consensus interpretation of multi-drug synergies across multiple samples. Nucleic Acids Res 50(W1):W739\u2013w743","journal-title":"Nucleic Acids Res"},{"key":"803_CR35","doi-asserted-by":"publisher","first-page":"102827","DOI":"10.1016\/j.sbi.2024.102827","volume":"86","author":"F Abbasi","year":"2024","unstructured":"Abbasi F, Rousu J (2024) New methods for drug synergy prediction: a mini-review. Curr Opin Struct Biol 86:102827","journal-title":"Curr Opin Struct Biol"},{"key":"803_CR36","doi-asserted-by":"publisher","first-page":"814412","DOI":"10.3389\/fgene.2022.814412","volume":"13","author":"T Jung","year":"2022","unstructured":"Jung T et al (2022) Integrative pathway analysis of SNP and metabolite data using a hierarchical structural component model. Front Genet 13:814412","journal-title":"Front Genet"},{"issue":"10","key":"803_CR37","doi-asserted-by":"publisher","first-page":"4829","DOI":"10.3390\/ijms26104829","volume":"26","author":"N Lee","year":"2025","unstructured":"Lee N et al (2025) Network pharmacology-guided evaluation of ginger and cornelian cherry extracts against depression and metabolic dysfunction in estrogen-deficient chronic stressed rats. Int J Mol Sci 26(10):4829","journal-title":"Int J Mol Sci"},{"issue":"3","key":"803_CR38","doi-asserted-by":"publisher","first-page":"1581","DOI":"10.1021\/acs.jctc.0c01327","volume":"17","author":"Y Yu","year":"2021","unstructured":"Yu Y et al (2021) CHARMM36 lipid force field with explicit treatment of long-range dispersion: parametrization and validation for phosphatidylethanolamine, phosphatidylglycerol, and ether lipids. J Chem Theory Comput 17(3):1581\u20131595","journal-title":"J Chem Theory Comput"},{"key":"803_CR39","doi-asserted-by":"publisher","first-page":"e59388","DOI":"10.7554\/eLife.59388","volume":"9","author":"EM Sanford","year":"2020","unstructured":"Sanford EM et al (2020) Gene regulation gravitates toward either addition or multiplication when combining the effects of two signals. eLife 9:e59388","journal-title":"eLife"},{"issue":"23","key":"803_CR40","doi-asserted-by":"publisher","first-page":"11443","DOI":"10.3390\/ijms262311443","volume":"26","author":"SI Kang","year":"2025","unstructured":"Kang SI et al (2025) Deep generative AI for multi-target therapeutic design: toward self-improving drug discovery framework. Int J Mol Sci 26(23):11443","journal-title":"Int J Mol Sci"},{"key":"803_CR41","doi-asserted-by":"publisher","first-page":"107270","DOI":"10.1016\/j.bpc.2024.107270","volume":"311","author":"V Grubelnik","year":"2024","unstructured":"Grubelnik V et al (2024) The role of anaplerotic metabolism of glucose and glutamine in insulin secretion: A model approach. Biophys Chem 311:107270","journal-title":"Biophys Chem"},{"issue":"9","key":"803_CR42","doi-asserted-by":"publisher","first-page":"2805","DOI":"10.1093\/bioinformatics\/btaa010","volume":"36","author":"X Zeng","year":"2020","unstructured":"Zeng X et al (2020) Network-based prediction of drug-target interactions using an arbitrary-order proximity embedded deep forest. Bioinformatics 36(9):2805\u20132812","journal-title":"Bioinformatics"},{"issue":"22","key":"803_CR43","doi-asserted-by":"publisher","first-page":"5406","DOI":"10.3390\/molecules29225406","volume":"29","author":"SP Rigby","year":"2024","unstructured":"Rigby SP (2024) Uses of molecular docking simulations in elucidating synergistic, additive, and\/or multi-target (SAM) effects of herbal medicines. Molecules 29(22):5406","journal-title":"Molecules"},{"issue":"1","key":"803_CR44","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1186\/s12859-024-05632-w","volume":"25","author":"TX Hui","year":"2024","unstructured":"Hui TX et al (2024) Robustness evaluations of pathway activity inference methods on gene expression data. BMC Bioinformatics 25(1):23","journal-title":"BMC Bioinformatics"},{"key":"803_CR45","doi-asserted-by":"publisher","first-page":"103202","DOI":"10.1016\/j.ebiom.2020.103202","volume":"63","author":"Q Pan","year":"2021","unstructured":"Pan Q et al (2021) A novel GLP-1 and FGF21 dual agonist has therapeutic potential for diabetes and non-alcoholic steatohepatitis. EBioMedicine 63:103202","journal-title":"EBioMedicine"},{"key":"803_CR46","doi-asserted-by":"publisher","first-page":"1301093","DOI":"10.3389\/fendo.2023.1301093","volume":"14","author":"X Xie","year":"2023","unstructured":"Xie X et al (2023) Benefits and risks of drug combination therapy for diabetes mellitus and its complications: a comprehensive review. Front Endocrinol 14:1301093","journal-title":"Front Endocrinol"},{"key":"803_CR47","doi-asserted-by":"publisher","first-page":"554961","DOI":"10.3389\/fphar.2020.554961","volume":"11","author":"FF Lillich","year":"2020","unstructured":"Lillich FF, Imig JD, Proschak E (2020) Multi-target approaches in metabolic syndrome. Front Pharmacol 11:554961","journal-title":"Front Pharmacol"},{"issue":"3","key":"803_CR48","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1007\/s00125-024-06339-6","volume":"68","author":"MR Shapiro","year":"2025","unstructured":"Shapiro MR et al (2025) Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes. Diabetologia 68(3):477\u2013494","journal-title":"Diabetologia"},{"issue":"9","key":"803_CR49","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.3390\/antiox14091065","volume":"14","author":"F He","year":"2025","unstructured":"He F et al (2025) Elucidating key components and mechanisms underlying the synergistic anti-type 2 diabetes effect of Morus alba L. and Siraitia grosvenorii combination: an integrated in vitro enzymology, untargeted metabolomics, and network pharmacology approach. Antioxidants 14(9):1065","journal-title":"Antioxidants"},{"issue":"6","key":"803_CR50","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1093\/bioinformatics\/btaa904","volume":"37","author":"M Wang","year":"2020","unstructured":"Wang M et al (2020) RobNorm: model-based robust normalization method for labeled quantitative mass spectrometry proteomics data. Bioinformatics 37(6):815\u2013821","journal-title":"Bioinformatics"},{"key":"803_CR51","doi-asserted-by":"publisher","first-page":"101547","DOI":"10.1016\/j.lanepe.2025.101547","volume":"61","author":"LM G\u00fcdemann","year":"2026","unstructured":"G\u00fcdemann LM et al (2026) Validation of an algorithm for selection of SGLT2 and DPP4 inhibitor therapies in people with type 2 diabetes across major UK ethnicity groups: a retrospective cohort study. Lancet Reg Health Eur 61:101547","journal-title":"Lancet Reg Health Eur"}],"container-title":["Journal of Computer-Aided Molecular Design"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10822-026-00803-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10822-026-00803-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10822-026-00803-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T05:15:29Z","timestamp":1775711729000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10822-026-00803-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,9]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["803"],"URL":"https:\/\/doi.org\/10.1007\/s10822-026-00803-8","relation":{},"ISSN":["1573-4951"],"issn-type":[{"value":"1573-4951","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,9]]},"assertion":[{"value":"14 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"97"}}