{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Ackloo S"],"funding":["Structural Genomics Consortium","Innovative Medicines Initiative","Pfizer","Bayer","Bristol-Myers Squibb Canada","Genentech","Janssen Canada","Boehringer Ingelheim","Merck KGaA","Takeda Canada","Ontario Genomics Institute","NIGMS NIH HHS","NIH HHS"],"pagination":["1092-1112"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11770632"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["68(2)"],"pubmed_abstract":["Target class-focused drug discovery has a strong track record in pharmaceutical research, yet public domain data indicate that many members of protein families remain unliganded. Here we present a systematic approach to scale up the discovery and characterization of small molecule ligands for the WD40 repeat (WDR) protein family. We developed a comprehensive suite of protocols for protein production, crystallography, and biophysical, biochemical, and cellular assays. A pilot hit-finding campaign using DNA-encoded chemical library selection followed by machine learning (DEL-ML) to predict ligands from virtual libraries yielded first-in-class, drug-like ligands for 7 of the 16 WDR domains screened, thus demonstrating the broader ligandability of WDRs. This study establishes a template for ev"],"journal":["Journal of medicinal chemistry"],"pubmed_title":["A Target Class Ligandability Evaluation of WD40 Repeat-Containing Proteins."],"pmcid":["PMC11770632"],"funding_grant_id":["875510","P30 GM124165","S10 OD021527","1097737","OGI-196"],"pubmed_authors":["Cuozzo JW","Centrella PA","Zhang J","Ahmad S","Torng W","Thompson J","Watson I","Harms N","Barsyte-Lovejoy D","von Rechenberg M","Baghaie AJ","Santhakumar V","Edwards AM","Taylor RD","Dong A","Kramer T","Righetto GL","Kimani SW","Lento C","Schapira M","Li F","Disch JS","Green SR","Keefe AD","Loup J","Houliston S","Xu J","Kwak HA","Guilinger JP","Gibson E","Li Y","Silva M","Halabelian L","Slakman BL","Bolotokova A","Zeng H","Ghiabi P","Guie MA","Shrestha S","Hutchinson A","Liu J","Seitova A","Wilson DJ","Gilmer J","Arrowsmith CH","Ackloo S","Szewczyk M","Loppnau P","Underkoffler C","Perveen S","Dumas A","Wolf E","Riley P","Sigel EA","Machado RAC","Chau I","Herasymenko O","Kearnes S","Yadav M","Beldar S","Dehghani-Tafti S","Goldman B","Clark MA","Kutera M","Arnautova YA","Sintchak MD","Feng JA","Yazdi AK","Zhang Y","Walsh RT","Brown PJ","Mulhern CJ"],"additional_accession":[]},"is_claimable":false,"name":"A Target Class Ligandability Evaluation of WD40 Repeat-Containing Proteins.","description":"Target class-focused drug discovery has a strong track record in pharmaceutical research, yet public domain data indicate that many members of protein families remain unliganded. Here we present a systematic approach to scale up the discovery and characterization of small molecule ligands for the WD40 repeat (WDR) protein family. We developed a comprehensive suite of protocols for protein production, crystallography, and biophysical, biochemical, and cellular assays. A pilot hit-finding campaign using DNA-encoded chemical library selection followed by machine learning (DEL-ML) to predict ligands from virtual libraries yielded first-in-class, drug-like ligands for 7 of the 16 WDR domains screened, thus demonstrating the broader ligandability of WDRs. This study establishes a template for ev","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jan","modification":"2026-06-02T10:09:46.981Z","creation":"2025-04-03T23:26:46.402Z"},"accession":"S-EPMC11770632","cross_references":{"pubmed":["39495097"],"doi":["10.1021/acs.jmedchem.4c02010"]}}