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Canvass: A Crowd-Sourced, Natural-Product Screening Library for Exploring Biological Space
Author(s) -
Sara E. Kearney,
Gergely Zahoránszky-Kőhalmi,
Kyle R. Brimacombe,
Mark J. Henderson,
Caitlin Lynch,
Tongan Zhao,
Kanny K. Wan,
Zina Itkin,
Christopher P. Dillon,
Min Shen,
Dorian M. Cheff,
Tobie D. Lee,
Danielle Bougie,
Ken Chih-Chien Cheng,
Nathan P. Coussens,
Dorjbal Dorjsuren,
Richard T. Eastman,
Ruili Huang,
Michael J. Iannotti,
Karavadhi Surendra,
Carleen KlumppThomas,
Jacob S. Roth,
Srilatha Sakamuru,
Wei Sun,
Steven A. Titus,
Adam Yasgar,
Y Q Zhang,
Jinghua Zhao,
Rodrigo Andrade,
M. Kevin Brown,
Noah Z. Burns,
Jin Kun,
Emily Mevers,
Jon Clardy,
Jason A. Clement,
Peter A. Crooks,
Gregory D. Cuny,
Jake Ganor,
Jesus Moreno,
Lucas A. Morrill,
Elias Picazo,
Robert B. Susick,
Neil K. Garg,
Brian C. Goess,
Robert B. Grossman,
Chambers C. Hughes,
Jeffrey N. Johnston,
Madeleine M. Joullié,
A. Douglas Kinghorn,
David G. I. Kingston,
Michael J. Krische,
Ohyun Kwon,
Thomas J. Maimone,
Susruta Majumdar,
Katherine N. Maloney,
Enas Mohamed,
Brian T. Murphy,
Pavel Nagorny,
David E. Olson,
Larry E. Overman,
Lauren E. Brown,
John K. Snyder,
John A. Porco,
Fatima Rivas,
Samir A. Ross,
Richmond Sarpong,
Indrajeet Sharma,
Jared T. Shaw,
Zhengren Xu,
Ben Shen,
Wei Shi,
Corey R. J. Stephenson,
Alyssa L. Verano,
Derek S. Tan,
Yi Tang,
Richard E. Taylor,
Regan J. Thomson,
David A. Vosburg,
Jimmy Wu,
William M. Wuest,
Armen Zakarian,
Yufeng Zhang,
Tianjing Ren,
Zhong Zuo,
James Inglese,
Sam Michael,
Anton Simeonov,
Wei Zheng,
Paul Shinn,
Ajit Jadhav,
Matthew B. Boxer,
Matthew D. Hall,
Menghang Xia,
Rajarshi Guha,
Jason M. Rohde
Publication year - 2018
Publication title -
acs central science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.893
H-Index - 76
eISSN - 2374-7951
pISSN - 2374-7943
DOI - 10.1021/acscentsci.8b00747
Subject(s) - workflow , chemical space , computer science , natural product , cluster analysis , set (abstract data type) , computational biology , biochemical engineering , drug discovery , combinatorial chemistry , data science , chemistry , biology , database , biochemistry , artificial intelligence , engineering , programming language
Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (-)-2( S )-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening.

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