Exactly half a century has passed since the launch of the first documented research project (1965 Dendral) on computer-assisted organic synthesis. Many more programs were created in the 1970s and 1980s but the enthusiasm of these pioneering days had largely dissipated by the 2000s, and the challenge of teaching the computer how to plan organic syntheses earned itself the reputation of a "mission impossible". This is quite curious given that, in the meantime, computers have "learned" many other skills that had been considered exclusive domains of human intellect and creativity-for example, machines can nowadays play chess better than human world champions and they can compose classical music pleasant to the human ear. Although there have been no similar feats in organic synthesis, this Review argues that to concede defeat would be premature. Indeed, bringing together the combination of modern computational power and algorithms from graph/network theory, chemical rules (with full stereo- and regiochemistry) coded in appropriate formats, and the elements of quantum mechanics, the machine can finally be "taught" how to plan syntheses of non-trivial organic molecules in a matter of seconds to minutes. The Review begins with an overview of some basic theoretical concepts essential for the big-data analysis of chemical syntheses. It progresses to the problem of optimizing pathways involving known reactions. It culminates with discussion of algorithms that allow for a completely de novo and fully automated design of syntheses leading to relatively complex targets, including those that have not been made before. Of course, there are still things to be improved, but computers are finally becoming relevant and helpful to the practice of organic-synthetic planning. Paraphrasing Churchill's famous words after the Allies' first major victory over the Axis forces in Africa, it is not the end, it is not even the beginning of the end, but it is the end of the beginning for the computer-assisted synthesis planning. The machine is here to stay.

The rule-based search of chemical space can generate an almost infinite number of molecules, but exploration of known molecules as a function of the minimum number of steps needed to build up the target graphs promises to uncover new motifs and transformations. Assembly theory is an approach to compare the intrinsic complexity and properties of molecules by the minimum number of steps needed to build up the target graphs. Here, we apply this approach to prebiotic chemistry, gene sequences, plasticizers, and opiates. This allows us to explore molecules connected to the assembly tree, rather than the entire space of molecules possible. Last, by developing a reassembly method, based on assembly trees, we found that in the case of the opiates, a new set of drug candidates could be generated that would not be accessible via conventional fragment-based drug design, thereby demonstrating how this approach might find application in drug discovery.

Seit der Einführung des ersten dokumentierten Forschungsprojekts (Dendral, 1965) zur rechnergestützten organischen Synthese ist ein halbes Jahrhundert vergangen. In den 1970er und 1980er Jahren wurden viele weitere Programme entwickelt, doch bis zu den 2000er Jahren war der Enthusiasmus dieser Pionierzeit weitgehend verschwunden, und wegen der schwierigen Aufgabe, die Planung organischer Synthesen in Computer einzugeben, erhielt sie den Ruf einer “Mission impossible”. Das ist recht merkwürdig angesichts der Tatsache, dass Computer in der Zwischenzeit viele andere Fähigkeiten “gelernt” haben, die als alleinige Domänen von Intellekt und Kreativität des Menschen betrachtet wurden – so können Rechner heutzutage besser Schach spielen als menschliche Weltmeister, und sie können klassische Musik komponieren, die für das menschliche Ohr angenehm ist. In der organischen Synthese hat es zwar keine vergleichbaren Leistungen gegeben, aber dieser Aufsatz behauptet, dass es verfrüht wäre, eine Niederlage einzugestehen. Tatsächlich kann dem Computer schließlich “beigebracht” werden, die Synthesen von komplizierten organischen Verbindungen in Sekunden‐ bis Minutenschnelle zu planen, indem die Kombination aus moderner Rechenleistung und Algorithmen aus der Graphen‐/Netzwerktheorie zusammengeführt wird mit in geeigneten Formaten codierten chemischen Regeln (mit vollständiger Stereo‐ und Regiochemie) und Elementen der Quantenmechanik. Der Aufsatz beginnt mit einem Überblick über theoretische Grundkonzepte, die essenziell sind für die Analyse der großen Datenmengen chemischer Synthesen. Im Anschluss daran wird auf die Optimierung von Synthesewegen unter Einbeziehung bekannter Reaktionen eingegangen. Einen Schwerpunkt bildet die anschließende Besprechung der Algorithmen, die eine vollständig neue und automatisierte Planung der Synthesen für komplizierte Zielverbindungen ermöglichen, darunter auch solche, die noch nicht hergestellt wurden. Es gibt natürlich noch Verbesserungsmöglichkeiten, letztendlich aber werden Computer für die praktische Planung der organischen Synthese wichtig und hilfreich sein. Churchills berühmte Worte nach dem ersten wichtigen Sieg der Alliierten über die Achsenmächte paraphrasierend, ist es für die computergestützte Syntheseplanung nicht das Ende, nicht einmal der Anfang vom Ende, sondern das Ende vom Anfang. Der Computer ist da und wird bleiben.

Computerized linguistic analyses have proven of immense value in comparing and searching through large text collections (“corpora”), including those deposited on the Internet – indeed, it would nowadays be hard to imagine browsing the Web without, for instance, search algorithms extracting most appropriate keywords from documents. This paper describes how such corpus-linguistic concepts can be extended to chemistry based on characteristic “chemical words” that span more than traditional functional groups and, instead, look at common structural fragments molecules share. Using these words, it is possible to quantify the diversity of chemical collections/databases in new ways and to define molecular “keywords” by which such collections are best characterized and annotated.

Analysis of the chemical-organic knowledge represented as a giant network reveals that it contains millions of reaction sequences closing into cycles. Without realizing it, independent chemists working at different times have jointly created examples of cyclic sequences that allow for the recovery of useful reagents and for the autoamplification of synthetically important molecules, those that mimic biological cycles, and those that can be operated one-pot.

Akin to electronic systems that can tune to and process signals of select frequencies, systems/networks of chemical reactions also “propagate” time‐varying concentration inputs in a frequency‐dependent manner. Whereas signals of low frequencies are transmitted, higher frequency inputs are dampened and converted into steady‐concentration outputs. Such behavior is observed in both idealized reaction chains as well as realistic signaling cascades, in the latter case explaining the experimentally observed responses of such cascades to input calcium oscillations. These and other results are supported by numerical simulations within the freely available Kinetix web application we developed to study chemical systems of arbitrary architectures, reaction kinetics, and boundary conditions.

Akin to electronic systems that can tune to and process signals of select frequencies, systems/networks of chemical reactions also “propagate” time‐varying concentration inputs in a frequency‐dependent manner. Whereas signals of low frequencies are transmitted, higher frequency inputs are dampened and converted into steady‐concentration outputs. Such behavior is observed in both idealized reaction chains as well as realistic signaling cascades, in the latter case explaining the experimentally observed responses of such cascades to input calcium oscillations. These and other results are supported by numerical simulations within the freely available Kinetix web application we developed to study chemical systems of arbitrary architectures, reaction kinetics, and boundary conditions.

Computer-Assisted Synthetic Planning: The End of the Beginning -[61 refs. + subrefs.]. -(SZYMKUC, S.; GAJEWSKA, E. P.; KLUCZNIK, T.; MOLGA, K.; DITTWALD, P.; STARTEK, M.; BAJCZYK, M.; GRZYBOWSKI*, B. A.; Angew. Chem., Int. Ed. 55 (2016) 20, 5904-5937, http://dx.