- M. D. Altmanet al., Cyclic Di-Nucleotide Compounds as STING
Agonists, WO2017/027646A1 (2017). - F. H. Arnold, Directed Evolution: Bringing New Chemistry to
Life.Angew. Chem. Int. Ed. 57 ,4143–4148 (2018).
doi:10.1002/anie.201708408; pmid: 29064156 - S. P. France, L. J. Hepworth, N. J. Turner, S. L. Flitsch,
Constructing Biocatalytic Cascades: In Vitro and in Vivo
Approaches to de Novo Multi-Enzyme Pathways.ACS Catal. 7 ,
710 – 724 (2017). doi:10.1021/acscatal.6b02979 - E. M. Sletten, C. R. Bertozzi, Bioorthogonal chemistry: Fishing
for selectivity in a sea of functionality.Angew. Chem. Int. Ed.
48 , 6974–6998 (2009). doi:10.1002/anie.200900942;
pmid: 19714693 - P. Stropet al., Location matters: Site of conjugation modulates
stability and pharmacokinetics of antibody drug conjugates.
Chem. Biol. 20 , 161–167 (2013). doi:10.1016/
j.chembiol.2013.01.010; pmid: 23438745 - J. I. MacDonald, H. K. Munch, T. Moore, M. B. Francis, One-step
site-specific modification of native proteins with 2-
pyridinecarboxyaldehydes.Nat. Chem. Biol. 11 , 326– 331
(2015). doi:10.1038/nchembio.1792; pmid: 25822913 - S. Bloomet al., Decarboxylative alkylation for site-selective
bioconjugation of native proteins via oxidation potentials.
Nat. Chem. 10 , 205–211 (2018). doi:10.1038/nchem.2888;
pmid: 29359756 - N. Oka, M. Yamamoto, T. Sato, T. Wada, Solid-phase synthesis
of stereoregular oligodeoxyribonucleoside phosphorothioates
using bicyclic oxazaphospholidine derivatives as monomer
units.J. Am. Chem. Soc. 130 , 16031–16037 (2008).
doi:10.1021/ja805780u; pmid: 18980312 - N. Iwamotoet al., Control of phosphorothioate stereochemistry
substantially increases the efficacy of antisense
oligonucleotides.Nat. Biotechnol. 35 , 845–851 (2017).
doi:10.1038/nbt.3948; pmid: 28829437 - C. Heinis, T. Rutherford, S. Freund, G. Winter, Phage-encoded
combinatorialchemical libraries based on bicyclic peptides.
Nat. Chem. Biol. 5 , 502–507 (2009). doi:10.1038/
nchembio.184; pmid: 19483697 - C. J. Hipolito, H. Suga, Ribosomal production and in vitro
selection of natural product-like peptidomimetics: The FIT and
RaPID systems.Curr. Opin. Chem. Biol. 16 , 196–203 (2012).
doi:10.1016/j.cbpa.2012.02.014; pmid: 22401851 - M. Shevlin, Practical High-Throughput Experimentation for
Chemists.ACS Med. Chem. Lett. 8 , 601–607 (2017).
doi:10.1021/acsmedchemlett.7b00165; pmid: 28626518 - K. D. Collins, T. Gensch, F. Glorius, Contemporary screening
approaches to reaction discovery and development.
Nat. Chem. 6 , 859–871 (2014). doi:10.1038/nchem.2062;
pmid: 25242480 - C. K. Chunget al., Asymmetric Hydrogen Bonding Catalysis for
the Synthesis of Dihydroquinazoline-Containing Antiviral,
Letermovir.J. Am. Chem. Soc. 139 , 10637–10640 (2017).
doi:10.1021/jacs.7b05806; pmid: 28737937- H. Liet al., Enantioselective Synthesis of Hemiaminals via
Pd-Catalyzed C-N Coupling with Chiral Bisphosphine Mono-
oxides.J. Am. Chem. Soc. 137 , 13728–13731 (2015).
doi:10.1021/jacs.5b05934; pmid: 26414910 - S. W. Krska, D. A. DiRocco, S. D. Dreher, M. Shevlin, The
Evolution of Chemical High-Throughput Experimentation To
Address Challenging Problems in Pharmaceutical Synthesis.
Acc. Chem. Res. 50 , 2976–2985 (2017). doi:10.1021/acs.
accounts.7b00428; pmid: 29172435 - T. Cernaket al., Microscale High-Throughput Experimentation
as an Enabling Technology in Drug Discovery: Application in
the Discovery of (Piperidinyl)pyridinyl-1H-benzimidazole
Diacylglycerol Acyltransferase 1 Inhibitors.J. Med. Chem. 60 ,
3594 – 3605 (2017). doi:10.1021/acs.jmedchem.6b01543;
pmid: 28252959 - P. S. Kutchukianet al., Chemistry informer libraries:
Achemoinformatics enabled approach to evaluate and
advance synthetic methods.Chem. Sci. 7 , 2604–2613 (2016).
doi:10.1039/C5SC04751J; pmid: 28660032 - K. D. Collins, F. Glorius, A robustness screen for the rapid
assessment of chemical reactions.Nat. Chem. 5 , 597– 601
(2013). doi:10.1038/nchem.1669; pmid: 23787750 - J. Richardson, J. C. Ruble, E. A. Love, S. Berritt, A Method
for Identifying and Developing Functional Group Tolerant Catalytic
Reactions: Application to the Buchwald-Hartwig Amination.
J. Org. Chem. 82 , 3741–3750 (2017). doi:10.1021/acs.
joc.7b00201; pmid: 28245358 - A. Buitrago Santanillaet al., Nanomole-scale high-throughput
chemistry for the synthesis of complex molecules.
Science 347 ,49–53 (2015). doi:10.1126/science.1259203;
pmid: 25554781 - D. Pereraet al., A platform for automated nanomole-scale
reaction screening and micromole-scale synthesis in flow.
Science 359 , 429–434 (2018). doi:10.1126/science.aap9112;
pmid: 29371464 - S. Linet al., Mapping the dark space of chemical reactions
with extended nanomole synthesis and MALDI-TOF MS.
Science 361 , eaar6236 (2018). doi:10.1126/science.aar6236;
pmid: 29794218 - N. J. Gesmundoet al., Nanoscale synthesis and affinity
ranking.Nature 557 , 228–232 (2018). doi:10.1038/
s41586-018-0056-8; pmid: 29686415 - M. Orlandi, F. D. Toste, M. S. Sigman, Multidimensional
Correlations in Asymmetric Catalysis through Parameterization
of Uncatalyzed Transition States.Angew. Chem. Int. Ed. 56 ,
14080 – 14084 (2017). doi:10.1002/anie.201707644;
pmid: 28902441 - D. T. Ahneman, J. G. Estrada, S. Lin, S. D. Dreher, A. G. Doyle,
Predicting reaction performance in C-N cross-coupling using
machine learning.Science 360 , 186 – 190 (2018). doi:10.1126/
science.aar5169; pmid: 29449509- J. M. Granda, L. Donina, V. Dragone, D.-L. Long, L. Cronin,
Controlling an organic synthesis robot with machine learning to
search for new reactivity.Nature 559 , 377–381 (2018).
doi:10.1038/s41586-018-0307-8; pmid: 30022133 - R. N. Straker, Q. Peng, A. Mekareeya, R. S. Paton,
E. A. Anderson, Computational ligand design in enantio- and
diastereoselective ynamide [5+2] cycloisomerization.
Nat. Commun. 7 , 10109 (2016). doi:10.1038/ncomms10109;
pmid: 26728968 - D. A. DiRoccoet al., A multifunctional catalyst that
stereoselectively assembles prodrugs.Science 356 , 426– 430
(2017). doi:10.1126/science.aam7936; pmid: 28450641 - Y. Guan, S. E. Wheeler, Automated Quantum Mechanical
Predictions of Enantioselectivity in a Rhodium-Catalyzed
Asymmetric Hydrogenation.Angew. Chem. Int. Ed. 56 ,
9101 – 9105 (2017). doi:10.1002/anie.201704663;
pmid: 28586140 - B. Liuet al., Retrosynthetic Reaction Prediction Using
Neural Sequence-to-Sequence Models.ACS Cent. Sci. 3 ,
1103 – 1113 (2017). doi:10.1021/acscentsci.7b00303;
pmid: 29104927 - C. W. Coley, L. Rogers, W. H. Green, K. F. Jensen, Computer-
Assisted Retrosynthesis Based on Molecular Similarity.
ACS Cent. Sci. 3 , 1237–1245 (2017). doi:10.1021/
acscentsci.7b00355; pmid: 29296663 - M. H. S. Segler, M. Preuss, M. P. Waller, Planning chemical
syntheses with deep neural networks and symbolic AI.
Nature 555 , 604–610 (2018). doi:10.1038/nature25978;
pmid: 29595767 - C. W. Coley, R. Barzilay, T. S. Jaakkola, W. H. Green,
K. F. Jensen, Prediction of Organic Reaction Outcomes Using
Machine Learning.ACS Cent. Sci. 3 , 434–443 (2017).
doi:10.1021/acscentsci.7b00064; pmid: 28573205
76.D. T. Ahneman, J. G. Estrada, S. Lin, S. D. Dreher, A. G. Doyle,
Predicting reaction performance in C-N cross-coupling using
machine learning.Science 360 , 186–190 (2018). doi:10.1126/
science.aar5169; pmid: 29449509
ACKNOWLEDGMENTS
We thank M. Kress, J. Hale, L.-C. Campeau, D. Schultz, S. Krska,
D. DiRocco, and A. Walji for their critical review of the manuscript;
C. T. Liu for preparation of Fig. 1; and D. MacMillan, R. Sarpong,
M. Gaunt, F. Arnold, and G. Dong for their participation in the
Disruptive Chemistry Summit at Merck. The authors declare no
competing financial interests.10.1126/science.aat0805Camposet al.,Science 363 , eaat0805 (2019) 18 January 2019 8of8
RESEARCH | REVIEW
on January 19, 2019^http://science.sciencemag.org/Downloaded from