TY - JOUR
T1 - Targeting RNA with Small Molecules
T2 - Identification of Selective, RNA-Binding Small Molecules Occupying Drug-Like Chemical Space
AU - Rizvi, Noreen F.
AU - Santa Maria, John P.
AU - Nahvi, Ali
AU - Klappenbach, Joel
AU - Klein, Daniel J.
AU - Curran, Patrick J.
AU - Richards, Matthew P.
AU - Chamberlin, Chad
AU - Saradjian, Peter
AU - Burchard, Julja
AU - Aguilar, Rodrigo
AU - Lee, Jeannie T.
AU - Dandliker, Peter J.
AU - Smith, Graham F.
AU - Kutchukian, Peter
AU - Nickbarg, Elliott B.
N1 - Funding Information:
Rizvi Noreen F. 1 * Santa Maria John P. Jr. 1 * Nahvi Ali 2 Klappenbach Joel 1 Klein Daniel J. 2 Curran Patrick J. 1 Richards Matthew P. 1 Chamberlin Chad 1 Saradjian Peter 1 Burchard Julja 1 Aguilar Rodrigo 3 Lee Jeannie T. 3 Dandliker Peter J. 1 Smith Graham F. 1 Kutchukian Peter 1 Nickbarg Elliott B. 1 1 Merck & Co., Inc., Boston, MA, USA 2 Merck & Co., Inc., West Point, PA, USA 3 Department of Molecular Biology, Massachusetts General Hospital; Department of Genetics, The Blavatnik Institute, Harvard Medical School, Boston, MA, USA Peter Kutchukian, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USA. Email: [email protected] Elliott B. Nickbarg, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USA. Email: [email protected] * These authors contributed equally to this work. 11 2019 2472555219885373 19 3 2019 13 9 2019 24 9 2019 © 2019 Society for Laboratory Automation and Screening 2019 Society for Laboratory Automation and Screening Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA–small molecule interactions that was generated was compared with that for protein–small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts. RNA noncoding RNA drug screening drug target mass spectrometry edited-state corrected-proof The authors would like to thank Anne Mai Wasserman and Kerrie Spencer for their advice and support of this research. Supplemental material is available online with this article. Authors’ Note Julja Burchard is currently affiliated with Sera Prognostics, Inc., Salt Lake City, UT, USA. Graham F. Smith is currently affiliated with AstraZeneca, Drug Safety and Metabolism, IMED Biotech Unit, Cambridge, UK. Declaration of Conflicting Interests The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: All authors except R.A. and J.T.L. are current or former employees of Merck & Co., Inc., and may hold stock or other financial interests in Merck & Co. Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: J.T.L. received support from a Merck MINt award, and R.A. was funded by a Pew Latin American Fellowship. All other authors were supported by Merck & Co., Inc.
Publisher Copyright:
© 2019 Society for Laboratory Automation and Screening.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA–small molecule interactions that was generated was compared with that for protein–small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts.
AB - Although the potential value of RNA as a target for new small molecule therapeutics is becoming increasingly credible, the physicochemical properties required for small molecules to selectively bind to RNA remain relatively unexplored. To investigate the druggability of RNAs with small molecules, we have employed affinity mass spectrometry, using the Automated Ligand Identification System (ALIS), to screen 42 RNAs from a variety of RNA classes, each against an array of chemically diverse drug-like small molecules (~50,000 compounds) and functionally annotated tool compounds (~5100 compounds). The set of RNA–small molecule interactions that was generated was compared with that for protein–small molecule interactions, and naïve Bayesian models were constructed to determine the types of specific chemical properties that bias small molecules toward binding to RNA. This set of RNA-selective chemical features was then used to build an RNA-focused set of ~3800 small molecules that demonstrated increased propensity toward binding the RNA target set. In addition, the data provide an overview of the specific physicochemical properties that help to enable binding to potential RNA targets. This work has increased the understanding of the chemical properties that are involved in small molecule binding to RNA, and the methodology used here is generally applicable to RNA-focused drug discovery efforts.
KW - drug screening
KW - drug target
KW - mass spectrometry
KW - noncoding RNA
KW - RNA
UR - http://www.scopus.com/inward/record.url?scp=85072362396&partnerID=8YFLogxK
U2 - 10.1177/2472555219885373
DO - 10.1177/2472555219885373
M3 - Article
C2 - 31701793
AN - SCOPUS:85072362396
SN - 2472-5552
VL - 25
SP - 384
EP - 396
JO - SLAS Discovery
JF - SLAS Discovery
IS - 4
ER -