TY - JOUR
T1 - Efficient Syntheses of Diverse, Medicinally Relevant Targets Planned by Computer and Executed in the Laboratory
AU - Klucznik, Tomasz
AU - Mikulak-Klucznik, Barbara
AU - McCormack, Michael P.
AU - Lima, Heather
AU - Szymkuć, Sara
AU - Bhowmick, Manishabrata
AU - Molga, Karol
AU - Zhou, Yubai
AU - Rickershauser, Lindsey
AU - Gajewska, Ewa P.
AU - Toutchkine, Alexei
AU - Dittwald, Piotr
AU - Startek, Michał P.
AU - Kirkovits, Gregory J.
AU - Roszak, Rafał
AU - Adamski, Ariel
AU - Sieredzińska, Bianka
AU - Mrksich, Milan
AU - Trice, Sarah L.J.
AU - Grzybowski, Bartosz A.
N1 - Funding Information:
S.S., K.M., E.P.G., P.D., Y.Z., M.M., and B.A.G. thank the US Defense Advanced Research Projects Agency for generous support under the “Make-It” Award, 69461-CH-DRP #W911NF1610384. T.K., B.M.K., A.A., M.P.S., and B.S. gratefully acknowledge support from the Symfonia Award (#2014/12/W/ST5/00592) from the Polish National Science Center (NCN). R.R. was supported through the Merck funds and also the FUGA postdoctoral program from NCN (#2016/20/S/ST5/00361). B.A.G. also gratefully acknowledges personal support from the Institute for Basic Science Korea, Project Code IBS-R020-D1. We would like to thank Professor Phil Baran for providing helpful comments during preparation of the manuscript.
Funding Information:
S.S., K.M., E.P.G., P.D., Y.Z., M.M., and B.A.G. thank the US Defense Advanced Research Projects Agency for generous support under the “Make-It” Award, 69461-CH-DRP #W911NF1610384. T.K., B.M.K., A.A., M.P.S., and B.S. gratefully acknowledge support from the Symfonia Award (#2014/12/W/ST5/00592) from the Polish National Science Center (NCN). R.R. was supported through the Merck funds and also the FUGA postdoctoral program from NCN ( #2016/20/S/ST5/00361 ). B.A.G. also gratefully acknowledges personal support from the Institute for Basic Science Korea , Project Code IBS-R020-D1. We would like to thank Professor Phil Baran for providing helpful comments during preparation of the manuscript.
Publisher Copyright:
© 2018 The Authors
PY - 2018/3/8
Y1 - 2018/3/8
N2 - The Chematica program was used to autonomously design synthetic pathways to eight structurally diverse targets, including seven commercially valuable bioactive substances and one natural product. All of these computer-planned routes were successfully executed in the laboratory and offer significant yield improvements and cost savings over previous approaches, provide alternatives to patented routes, or produce targets that were not synthesized previously. Although computers have demonstrated the ability to challenge humans in various games of strategy, their use in the automated planning of organic syntheses remains unprecedented. As a result of the impact that such a tool could have on the synthetic community, the past half century has seen numerous attempts to create in silico chemical intelligence. However, there has not been a successful demonstration of a synthetic route designed by machine and then executed in the laboratory. Here, we describe an experiment where the software program Chematica designed syntheses leading to eight commercially valuable and/or medicinally relevant targets; in each case tested, Chematica significantly improved on previous approaches or identified efficient routes to targets for which previous synthetic attempts had failed. These results indicate that now and in the future, chemists can finally benefit from having an “in silico colleague” that constantly learns, never forgets, and will never retire. Multistep synthetic routes to eight structurally diverse and medicinally relevant targets were planned autonomously by the Chematica computer program, which combines expert chemical knowledge with network-search and artificial-intelligence algorithms. All of the proposed syntheses were successfully executed in the laboratory and offer substantial yield improvements and cost savings over previous approaches or provide the first documented route to a given target. These results provide the long-awaited validation of a computer program in practically relevant synthetic design.
AB - The Chematica program was used to autonomously design synthetic pathways to eight structurally diverse targets, including seven commercially valuable bioactive substances and one natural product. All of these computer-planned routes were successfully executed in the laboratory and offer significant yield improvements and cost savings over previous approaches, provide alternatives to patented routes, or produce targets that were not synthesized previously. Although computers have demonstrated the ability to challenge humans in various games of strategy, their use in the automated planning of organic syntheses remains unprecedented. As a result of the impact that such a tool could have on the synthetic community, the past half century has seen numerous attempts to create in silico chemical intelligence. However, there has not been a successful demonstration of a synthetic route designed by machine and then executed in the laboratory. Here, we describe an experiment where the software program Chematica designed syntheses leading to eight commercially valuable and/or medicinally relevant targets; in each case tested, Chematica significantly improved on previous approaches or identified efficient routes to targets for which previous synthetic attempts had failed. These results indicate that now and in the future, chemists can finally benefit from having an “in silico colleague” that constantly learns, never forgets, and will never retire. Multistep synthetic routes to eight structurally diverse and medicinally relevant targets were planned autonomously by the Chematica computer program, which combines expert chemical knowledge with network-search and artificial-intelligence algorithms. All of the proposed syntheses were successfully executed in the laboratory and offer substantial yield improvements and cost savings over previous approaches or provide the first documented route to a given target. These results provide the long-awaited validation of a computer program in practically relevant synthetic design.
KW - Chematica
KW - artificial intelligence
KW - chemical networks and graphs
KW - computer-assisted synthesis
KW - large-scale calculations
KW - organic synthesis
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U2 - 10.1016/j.chempr.2018.02.002
DO - 10.1016/j.chempr.2018.02.002
M3 - Article
AN - SCOPUS:85043498559
SN - 2451-9294
VL - 4
SP - 522
EP - 532
JO - Chem
JF - Chem
IS - 3
ER -