This is an unedited manuscript that has been accepted for publication. Nature Research are providing this early version of the manuscript as a service to our authors and readers. The manuscript will undergo copyediting, typesetting and a proof review before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

Computational planning of the synthesis of complex natural products


Teaching computers to plan multistep organic syntheses has been a challenge for over 50 years1–7. Since early pioneering contributions, including programs such as LHASA1,7 (with reaction choices at each step made by human operator), the field has progressed greatly and there are now multiple software platforms6,8–13 capable of completely autonomous planning. Still, these programs ‘think’ only one step at a time and have so far been limited to relatively simple targets whose syntheses could, arguably, be designed by human chemists within minutes and without computer’s help. To date, no algorithm has been able to design plausible routes to complex natural products for which significantly more far-sighted, multi-step planning is necessary14,15 and for which one cannot rely on closely related literature precedents. Here we demonstrate that such route choices are possible, provided that the machine’s knowledge of organic chemistry and data-based artificial intelligence routines are augmented with causal relationships16,17, allowing it to strategize over multiple synthetic steps. With these improvements, results of a Turing-like test administered to synthesis experts indicate that the routes designed by computer become largely indistinguishable from those designed by humans. Three computer-designed syntheses of natural products were successfully validated in the lab. Taken together, these results indicate that automated synthetic planning at an expert level is finally becoming feasible, pending continued improvements to the reaction-knowledge base and further code optimization.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Author information



Corresponding authors

Correspondence to Karol Molga or Jacek Młynarski or Milan Mrksich or Bartosz A. Grzybowski.

Supplementary information

Supplementary Information

This file contains additional synthetic, spectroscopic, chromatographic, and statistical details and includes Supplementary Figures 1-89.

Supplementary Data

This zipped folder contains 3 files. The pseudocode for the multistep retrosynthetic design, pathway generation and retrieval can be found in the PSEUDOCODE_Aug2.pdf file. An example of one of the reaction rules as coded in Chematica is provided in the RULE.pdf file. Additional details of the software’s availability and execution are given in the README_Aug2.pdf file.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mikulak-Klucznik, B., Gołębiowska, P., Bayly, A.A. et al. Computational planning of the synthesis of complex natural products. Nature (2020).

Download citation


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing