Suzanne Ackloo, Fengling Li, Magda Szewczyk, Almagul Seitova, Peter Loppnau, Hong Zeng, Jin Xu, Shabbir Ahmad, Yelena A Arnautova, A J Baghaie, Serap Beldar, Albina Bolotokova, Paolo A Centrella, Irene Chau, Matthew A Clark, John W Cuozzo, Saba Dehghani-Tafti, Jeremy S Disch, Aiping Dong, Antoine Dumas, Jianwen A Feng, Pegah Ghiabi, Elisa Gibson, Justin Gilmer, Brian Goldman, Stuart R Green, Marie-Aude Guié, John P Guilinger, Nathan Harms, Oleksandra Herasymenko, Scott Houliston, Ashley Hutchinson, Steven Kearnes, Anthony D Keefe, Serah W Kimani, Trevor Kramer, Maria Kutera, Haejin A Kwak, Cristina Lento, Yanjun Li, Jenny Liu, Joachim Loup, Raquel A C Machado, Christopher J Mulhern, Sumera Perveen, Germanna L Righetto, Patrick Riley, Suman Shrestha, Eric A Sigel, Madhushika Silva, Michael D Sintchak, Belinda L Slakman, Rhys D Taylor, James Thompson, Wen Torng, Carl Underkoffler, Moritz von Rechenberg, Ryan T Walsh, Ian Watson, Derek J Wilson, Esther Wolf, Manisha Yadav, Aliakbar K Yazdi, Junyi Zhang, Ying Zhang, Vijayaratnam Santhakumar, Aled M Edwards, Dalia Barsyte-Lovejoy, Matthieu Schapira, Peter J Brown, Levon Halabelian, Cheryl H Arrowsmith
{"title":"含 WD40 重复蛋白的目标类配体性评估。","authors":"Suzanne Ackloo, Fengling Li, Magda Szewczyk, Almagul Seitova, Peter Loppnau, Hong Zeng, Jin Xu, Shabbir Ahmad, Yelena A Arnautova, A J Baghaie, Serap Beldar, Albina Bolotokova, Paolo A Centrella, Irene Chau, Matthew A Clark, John W Cuozzo, Saba Dehghani-Tafti, Jeremy S Disch, Aiping Dong, Antoine Dumas, Jianwen A Feng, Pegah Ghiabi, Elisa Gibson, Justin Gilmer, Brian Goldman, Stuart R Green, Marie-Aude Guié, John P Guilinger, Nathan Harms, Oleksandra Herasymenko, Scott Houliston, Ashley Hutchinson, Steven Kearnes, Anthony D Keefe, Serah W Kimani, Trevor Kramer, Maria Kutera, Haejin A Kwak, Cristina Lento, Yanjun Li, Jenny Liu, Joachim Loup, Raquel A C Machado, Christopher J Mulhern, Sumera Perveen, Germanna L Righetto, Patrick Riley, Suman Shrestha, Eric A Sigel, Madhushika Silva, Michael D Sintchak, Belinda L Slakman, Rhys D Taylor, James Thompson, Wen Torng, Carl Underkoffler, Moritz von Rechenberg, Ryan T Walsh, Ian Watson, Derek J Wilson, Esther Wolf, Manisha Yadav, Aliakbar K Yazdi, Junyi Zhang, Ying Zhang, Vijayaratnam Santhakumar, Aled M Edwards, Dalia Barsyte-Lovejoy, Matthieu Schapira, Peter J Brown, Levon Halabelian, Cheryl H Arrowsmith","doi":"10.1021/acs.jmedchem.4c02010","DOIUrl":null,"url":null,"abstract":"<p><p>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 evaluation of protein family wide ligandability and provides an extensive resource of WDR protein biochemical and chemical tools, knowledge, and protocols to discover potential therapeutics for this highly disease-relevant, but underexplored target class.</p>","PeriodicalId":46,"journal":{"name":"Journal of Medicinal Chemistry","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Target Class Ligandability Evaluation of WD40 Repeat-Containing Proteins.\",\"authors\":\"Suzanne Ackloo, Fengling Li, Magda Szewczyk, Almagul Seitova, Peter Loppnau, Hong Zeng, Jin Xu, Shabbir Ahmad, Yelena A Arnautova, A J Baghaie, Serap Beldar, Albina Bolotokova, Paolo A Centrella, Irene Chau, Matthew A Clark, John W Cuozzo, Saba Dehghani-Tafti, Jeremy S Disch, Aiping Dong, Antoine Dumas, Jianwen A Feng, Pegah Ghiabi, Elisa Gibson, Justin Gilmer, Brian Goldman, Stuart R Green, Marie-Aude Guié, John P Guilinger, Nathan Harms, Oleksandra Herasymenko, Scott Houliston, Ashley Hutchinson, Steven Kearnes, Anthony D Keefe, Serah W Kimani, Trevor Kramer, Maria Kutera, Haejin A Kwak, Cristina Lento, Yanjun Li, Jenny Liu, Joachim Loup, Raquel A C Machado, Christopher J Mulhern, Sumera Perveen, Germanna L Righetto, Patrick Riley, Suman Shrestha, Eric A Sigel, Madhushika Silva, Michael D Sintchak, Belinda L Slakman, Rhys D Taylor, James Thompson, Wen Torng, Carl Underkoffler, Moritz von Rechenberg, Ryan T Walsh, Ian Watson, Derek J Wilson, Esther Wolf, Manisha Yadav, Aliakbar K Yazdi, Junyi Zhang, Ying Zhang, Vijayaratnam Santhakumar, Aled M Edwards, Dalia Barsyte-Lovejoy, Matthieu Schapira, Peter J Brown, Levon Halabelian, Cheryl H Arrowsmith\",\"doi\":\"10.1021/acs.jmedchem.4c02010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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A Target Class Ligandability Evaluation of WD40 Repeat-Containing Proteins.
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 evaluation of protein family wide ligandability and provides an extensive resource of WDR protein biochemical and chemical tools, knowledge, and protocols to discover potential therapeutics for this highly disease-relevant, but underexplored target class.
期刊介绍：
The Journal of Medicinal Chemistry is a prestigious biweekly peer-reviewed publication that focuses on the multifaceted field of medicinal chemistry. Since its inception in 1959 as the Journal of Medicinal and Pharmaceutical Chemistry, it has evolved to become a cornerstone in the dissemination of research findings related to the design, synthesis, and development of therapeutic agents.
The Journal of Medicinal Chemistry is recognized for its significant impact in the scientific community, as evidenced by its 2022 impact factor of 7.3. This metric reflects the journal's influence and the importance of its content in shaping the future of drug discovery and development. The journal serves as a vital resource for chemists, pharmacologists, and other researchers interested in the molecular mechanisms of drug action and the optimization of therapeutic compounds.
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