{"doi":"10.1016/j.ejmech.2025.118486","title":"Targeting neuroinflammation by activation of the sigma-1 receptor (S1R) and inhibition of butyrylcholinesterase (hBChE) leads to highly potent anti-amnesic compounds in an Alzheimer's disease mouse model","abstract":"ABSTRACT Alzheimer's disease (AD) is a neurodegenerative disorder for which no effective preventative or curative treatment has yet been identified. Due to the multifactorial nature and complex pathophysiology of the disease, we developed a multi-target ligand that both inhibits human butyrylcholinesterase ( h BChE), a key enzyme linked to β-amyloid plaque formation, and activates the sigma-1 receptor (S1R), which modulates neuroinflammatory and protective pathways. To this end, a series of isoindolines were designed and synthesized, and their biological activity was evaluated. The most promising compound, 7c , exhibited significant dual activity, achieving nanomolar IC 50 values against h BChE and potent S1R activation. Subsequent in vivo studies in an Aβ 25-35 mouse model revealed an improvement in cognitive deficits in both short- and long-term memory at an effective dose of 0.01 mg/kg in WT Swiss-OF1 mice. This dose is 10-fold lower compared to single-target compounds 7a and 7b of this isoindoline series. The lack of neuroprotective effects in BChE knock-out (KO) mice confirmed the involvement of BChE inhibition for compounds 7c effects in WT mice. Further combinatorial studies employing a two-drug combination demonstrated synergy in the neuroprotective effect of the two targets.","journal":"European Journal of Medicinal Chemistry","year":2025,"id":525039,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9575,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":856343,"name":"Lucie Crouzier","orcid":"0000-0001-8534-8337","position":1,"is_corresponding":false},{"id":1399806,"name":"Tina Gehrig","orcid":null,"position":2,"is_corresponding":false},{"id":1399807,"name":"Alix Flake","orcid":null,"position":3,"is_corresponding":false},{"id":1399808,"name":"E. Schaller","orcid":null,"position":4,"is_corresponding":false},{"id":1097130,"name":"Johann Meunier","orcid":"0000-0003-1320-9391","position":5,"is_corresponding":false},{"id":1399215,"name":"Christelle Bertrand‐Gaday","orcid":"0000-0003-0461-2402","position":6,"is_corresponding":false},{"id":1399216,"name":"Arnaud Chatonnet","orcid":"0000-0002-4057-3896","position":7,"is_corresponding":false},{"id":1399217,"name":"Liga Zvejniece","orcid":"0000-0003-4576-2386","position":8,"is_corresponding":false},{"id":1399218,"name":"Christoph Sotriffer","orcid":"0000-0003-4713-4068","position":9,"is_corresponding":false},{"id":467037,"name":"Tangui Maurice","orcid":"0000-0002-4074-6793","position":10,"is_corresponding":false},{"id":1399219,"name":"Michael Decker","orcid":"0000-0002-6773-6245","position":11,"is_corresponding":false},{"id":1399214,"name":"Kora Reichau","orcid":"0000-0003-3919-7667","position":0,"is_corresponding":true}],"reference_count":74,"raw_metadata":null,"created_at":"2026-07-19T02:50:16.562292Z","pmid":"41547241","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}