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Catalyst: Curtailing the scalable supply of fentanyl by using chemical AI

CHEM 2024年第5期10卷 1319-1326页

作者： Mikulak-Klucznik, Barbara Klucznik, Tomasz Beker, Wiktor Moskal, Martyna Grzybowski, Bartosz A. Allchemy Inc Highland IN USA Polish Acad Sci Inst Organ Chem Ul Kasprzaka 44-52 PL-01224 Warsaw Poland UNIST IBS Ctr Algorithm & Robotized Synth CARS 50 UNIST Gil Ulsan 689798 South Korea UNIST Dept Chem 50 UNIST Gil Ulsan 44919 Ulju Gun South Korea

The authors are organic chemists and AI specialists who have worked on the development of chemical AI for over a decade now and brought to the public synthesis-design platforms such as originally synthetic-organic chemists and Bartosz's former graduate students at the Institute of Organic Chemistry of the Polish Academy of Sciences. Wiktor and Martyna are chemical AI specialists at Allchemy. All four are recipients of numerous student and doctoral prizes in Poland. Bartosz is a distinguished professor of chemistry at UNIST and director of the ibs Center for algorithmic and robotized synthesis in Ulsan, South Korea. He has received several awards, of which the 2016 Feynman Prize and the 2022 Foundation for Polish Science Prize are closest to his heart. As a member of the scientific advisory board of the Organisation for the Prohibition of Chemical Weapons, he analyzes the ways in which AI could limit the proliferation of chemical weapons.

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Stirring-Controlled synthesis of Ultrastable, Fluorescent Silver Nanoclusters

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SMALL 2024年第42期20卷 e2400306页

作者： Cybulski, Olgierd Quintana, Cristobal Siek, Marta Grzybowski, Bartosz A. Inst Basic Sci IBS Ctr Algorithm & Robotized Synth CARS Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Chem Ulsan 44919 South Korea

This paper describes how macroscopic stirring of a reaction mixture can be used to produce nanostructures exhibiting properties not readily achievable via other protocols. In particular, it is shown that by simply adjusting the stirring rate, a standard glutathione-based method-to date, used to produce only marginally stable fluorescent silver nanoclusters, Ag NCs-can be boosted to yield nanoclusters retaining fluorescence for unprecedented periods of over 2 years. This enhancement derives not simply from increased homogenization of the reaction mixture but mainly from an appropriately timed delivery of oxygen from above the reaction mixture. In effect, oxygen serves as a reagent that dictates size, structure, stability, and functional properties of the growing nanoobjects.

关键词： fluorescent silver nanoclusters stirring transport phenomena

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Aerodynamically Levitated Droplets as Small-Scale Chemical Reactors and Liquid Microprinters

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ANGEWANDTE CHEMIE-INTERNATIONAL EDITION 2024年第39期63卷 e202318038页

作者： Jia, Yankai Sobolev, Yaroslav I. Cybulski, Olgierd Klucznik, Tomasz Quintana, Cristobal Ahumada, Juan Carlos Grzybowski, Bartosz A. Ulsan Natl Inst Sci & Technol IBS Ctr Algorithm & Robotized Synth CARS 50 UNIST Gil Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol Dept Chem 50 UNIST Gil Ulsan South Korea

A thin liquid film spread over the inner surface of a rapidly rotating vial creates an aerodynamic cushion on which one or multiple droplets of various liquids can levitate stably for days or even weeks. These levitating droplets can serve as wall-less ("airware") chemical reactors that can be merged without touching-by remote impulses-to initiate reactions or sequences of reactions at scales down to hundreds of nanomoles. Moreover, under external electric fields, the droplets can act as the world's smallest chemical printers, shedding regular trains of pL or even fL microdrops. In one modality, the levitating droplets operate as completely wireless aliquoting/titrating systems delivering pg quantities of reagents into the liquid in the rotating vial;in another modality, they print microdroplet arrays onto target surfaces. The "airware", levitated reactors are inexpensive to set up, remarkably stable to external disturbances and, for printing applications, require operating voltages much lower than in electrospray, electrowetting, or ink jet systems. Droplets of various solvents can levitate for days to weeks over the same or another liquid spread over the walls of a rotating vial. Individual or multiple droplets can be levitated, and can be used as "airware" reactors or as "wireless" chemical printers requiring no external connections to deliver into a reaction mixture fL volumes and pg quantities of reagents. image

关键词： Levitating droplets Small-scale reactions Wireless chemical printing Electrohydrodynamics

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Vascularized platforms for investigating cell communication via extracellular vesicles

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BIOMICROFLUIDICS 2024年第5期18卷 051504页

作者： Kim, Junyoung Ro, Jooyoung Cho, Yoon-Kyoung Ulsan Natl Inst Sci & Technol UNIST Dept Biomed Engn Ulsan 44919 South Korea Inst Basic Sci IBS Ctr Algorithm & Robotized Synth Ulsan 44919 South Korea

The vascular network plays an essential role in the maintenance of all organs in the body via the regulated delivery of oxygen and nutrients, as well as tissue communication via the transfer of various biological signaling molecules. It also serves as a route for drug administration and affects pharmacokinetics. Due to this importance, engineers have sought to create physiologically relevant and reproducible vascular systems in tissue, considering cell-cell and extracellular matrix interaction with structural and physical conditions in the microenvironment. Extracellular vesicles (EVs) have recently emerged as important carriers for transferring proteins and genetic material between cells and organs, as well as for drug delivery. Vascularized platforms can be an ideal system for studying interactions between blood vessels and EVs, which are crucial for understanding EV-mediated substance transfer in various biological situations. This review summarizes recent advances in vascularized platforms, standard and microfluidic-based techniques for EV isolation and characterization, and studies of EVs in vascularized platforms. It provides insights into EV-related (patho)physiological regulations and facilitates the development of EV-based therapeutics.

关键词： Blood vessels

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Organ-on-a-Chip Approach for Accelerating Blood-Brain Barrier Nanoshuttle Discovery

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ACS NANO 2024年第22期18卷 14388-14402页

作者： Choi, Jeong-Won Kim, Kyungha Mukhambetiyar, Karakoz Lee, Na Kyeong del Rio, Jonathan Sabate Joo, Jinmyoung Park, Chun Gwon Kwon, Taejoon Park, Tae-Eun Ulsan Natl Inst Sci & Technol UNIST Dept Biomed Engn Coll Informat & Biotechnol Ulsan 44919 South Korea Harvard Univ Harvard John A Paulson Sch Engn & Appl Sci Allston MA 02134 USA Sungkyunkwan Univ Inst Cross Disciplinary Studies ICS Dept Biomed Engn Suwon 16419 Gyeonggi South Korea Inst Basic Sci IBS Ctr Algorithm & Robotized Synth CARS Ulsan 44919 South Korea Inst Basic Sci Ctr Genom Integr Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol UNIST Grad Sch Hlth Sci & Technol Ulsan 44919 South Korea

Organ-on-a-chip, which recapitulates the dynamics of in vivo vasculature, has emerged as a promising platform for studying organ-specific vascular beds. However, its practical advantages in identifying vascular-targeted drug delivery systems (DDS) over traditional in vitro models remain underexplored. This study demonstrates the reliability and efficacy of the organ-on-a-chip in screening efficient DDS by comparing its performance with that of a conventional transwell, both designed to simulate the blood-brain barrier (BBB). The BBB nanoshuttles discovered through BBB Chip-based screening demonstrated superior functionality in vivo compared to those identified using transwell methods. This enhanced effectiveness is attributed to the BBB Chip's accurate replication of the structure and dynamics of the endothelial glycocalyx, a crucial protective layer within blood vessels, especially under shear stress. This capability of the BBB Chip has enabled the identification of molecular shuttles that efficiently exploit the endothelial glycocalyx, thereby enhancing transendothelial transport efficacy. Our findings suggest that organ-on-a-chip technology holds considerable promise for advancing research in vascular-targeted DDS due to its accurate simulation of molecular transport within endothelial systems.

关键词： organ-on-a-chip blood-brain barrier drug delivery system molecular shuttle screening endothelial glycocalyx

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Estimation of multicomponent reactions' yields from networks of mechanistic steps

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NATURE COMMUNICATIONS 2024年第1期15卷 10286页

作者： Szymkuc, Sara Wolos, Agnieszka Roszak, Rafal Grzybowski, Bartosz A. Allchemy Inc Highland IN 46322 USA Polish Acad Sci Inst Organ Chem Warsaw Poland Inst Basic Sci IBS Ctr Algorithm & Robotized Synth CARS Ulsan South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Chem Ulsan South Korea

This work describes estimation of yields of complex, multicomponent reactions (MCRs) based on the modeled networks of mechanistic steps spanning both the main reaction pathway as well as immediate and downstream side reactions. Because experimental values of the kinetic rate constants for individual mechanistic transforms are extremely sparse, these constants are approximated here using Mayr's nucleophilicity and electrophilicity parameters fine-tuned by correction terms grounded in linear free-energy relationships. With this formalism, the model trained on the mechanistic networks of only 20 - but mechanistically- and yield-diverse MCRs - transfers well to newly discovered MCRs that are based on markedly different mechanisms and types of individual mechanistic transforms. These results suggest that mechanistic-level approach to yield estimation may be a useful alternative to models that are derived from full-reaction data and lack information about yield-lowering side reactions. The ability to predict the yields of organic reactions is of tremendous value for synthetic chemistry, limiting the number of unproductive experiments. Here, the authors describe estimation of yields of complex, multicomponent reactions (MCRs) based on the modeled networks of mechanistic steps spanning both the main reaction pathway as well as immediate and downstream side reactions.

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Emergence of metabolic-like cycles in blockchain-orchestrated reaction networks

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CHEM 2024年第3期10卷 P952-970页

作者： Roszak, Rafak Wolos, Agnieszka Benke, Marcin Glen, Lukasz Konka, Jakub Jensen, Phillip Burgchardt, Pawek Zadlo-Dobrowolska, Anna Janiuk, Piotr Szymkuc, Sara Grzybowski, Bartosz A. Allchemy Highland IN 46322 USA Polish Acad Sci Inst Organ Chem Ul Kasprzaka 44-52 PL-01224 Warsaw Poland Golem Factory GmbH Gubelstr 11 CH-6300 Zug Switzerland Univ Warsaw Inst Informat Ul Banacha 2 PL-02097 Warsaw Poland UNIST IBS Ctr Algorithm & Robotized Synth 50 UNIST Gil Ulsan 689798 South Korea UNIST Dept Chem 50 UNIST Gil Ulsan 689798 South Korea

This theoretical work harnesses the power of an open-access, blockchain-based platform for distributed computing to generate the largest-known network of prebiotic reactions and then to trace within this network (1) synthetic routes to biotic molecules and (2) reaction cycles and their unions that could have defined some elements of primitive, non-enzymatic metabolism. The calculation of this network, spanning >4.9 billion plausible prebiotic reactions and >3.7 billion molecules, was orchestrated automatically over hundreds of machines worldwide, each machine bidding its dynamically adjustable computing power in return for Golem cryptocurrency tokens, which underlie this platform and are traded at major cryptocurrency exchanges. In a broader context, this work illustrates how (1) blockchain-based technology can find new productive uses outside of the financial/security sector, whereas (2) scientists can benefit from this technology by gaining access to computing resources they would normally not have at their disposal.

关键词： origins of life metabolic cycle self-replication emergence reaction networks blockchain computing

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Machine Learning algorithm Guides Catalyst Choices for Magnesium-Catalyzed Asymmetric Reactions

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ANGEWANDTE CHEMIE-INTERNATIONAL EDITION 2024年第37期63卷 e202318487页

作者： Baczewska, Paulina Kulczykowski, Michal Zambron, Bartosz Jaszczewska-Adamczak, Joanna Pakulski, Zbigniew Roszak, Rafal Grzybowski, Bartosz A. Mlynarski, Jacek Polish Acad Sci Inst Organ Chem Kasprzaka 44-52 PL-02224 Warsaw Poland Ulsan Natl Inst Sci & Technol Koreas Inst Basic Sci IBS Ctr Algorithm & Robotized Synth CARS 50 UNIST Gil Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol Dept Chem 50 UNIST Gil Ulsan 44919 South Korea

Organic-chemical literature encompasses large numbers of catalysts and reactions they can effect. Many of these examples are published merely to document the catalysts' scope but do not necessarily guarantee that a given catalyst is "optimal"-in terms of yield or enantiomeric excess-for a particular reaction. This paper describes a Machine Learning model that aims to improve such catalyst-reaction assignments based on the carefully curated literature data. As we show here for the case of asymmetric magnesium catalysis, this model achieves relatively high accuracy and offers out of-the-box predictions successfully validated by experiment, e.g., in synthetically demanding asymmetric reductions or Michael additions. A carefully curated dataset of reactions catalyzed by magnesium-based catalysts underlies a Machine-Learning model guiding the choices of catalysts "optimal" for reactions unseen during training. When this model is tested by experiment, it suggests catalysts that yield higher ee values, replace rare-earth-metal catalysts, or improve the efficiency of stereoselective transformations relevant to drug discovery. image

关键词： Asymmetric catalysis Magnesium Machine Learning Neural networks

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Light-Driven, Dynamic Assembly of Micron-To-Centimeter Parts, Micromachines and Microbot Swarms

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ADVANCED SCIENCE 2024年第32期11卷 e2402263页

作者： Polev, Konstantin Paneru, Govind Visyn, Valentin Cybulski, Olgierd Lach, Slawomir Kolygina, Diana V. Edel, Evelyn Grzybowski, Bartosz A. Inst Basic Sci IBS Ctr Algorithm & Robotized Synth CARS Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Biomed Engn Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Phys Ulsan 44949 South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Chem Ulsan 44919 South Korea

This work describes light-driven assembly of dynamic formations and functional particle swarms controlled by appropriately programmed light patterns. The system capitalizes on the use of a fluidic bed whose low thermal conductivity assures that light-generated heat remains "localized" and sets strong convective flows in the immediate vicinity of the particles being irradiated. In this way, even low-power laser light or light from a desktop slide projector can be used to organize dynamic formations of objects spanning four orders of magnitude in size (from microns to centimeters) and over nine orders of magnitude in terms of mass. These dynamic assemblies include open-lattice structures with individual particles performing intricate translational and/or rotational motions, density-gradient particle arrays, nested architectures of mechanical components (e.g., planetary gears), or swarms of light-actuated microbots controlling assembly of other objects. Particles sized from microns to centimeters and placed on a fluidic bed characterized by low thermal conductivity can be manipulated and controlled by low power light. The image shows complex "planetary" motions of an ensemble of 12 parts: The rotary motions of the orbits and of the individual particles are indicated by curved, dashed arrows. image

关键词： dynamic assembly functional architectures light swarms

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Computational prediction of complex cationic rearrangement outcomes

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NATURE 2024年第7995期625卷 508-515页

作者： Klucznik, Tomasz Syntrivanis, Leonidas-Dimitrios Bas, Sebastian Mikulak-Klucznik, Barbara Moskal, Martyna Szymkuc, Sara Mlynarski, Jacek Gadina, Louis Beker, Wiktor Burke, Martin D. Tiefenbacher, Konrad Grzybowski, Bartosz A. Allchemy Highland IN 46322 USA Polish Acad Sci Inst Organ Chem Warsaw Poland Univ Illinois Sch Chem Sci Roger Adams Lab Urbana IL 61820 USA Univ Basel Dept Chem Basel Switzerland Jagiellonian Univ Fac Chem Krakow Poland Univ Illinois Dept Biochem Urbana IL 61820 USA Univ Illinois Beckman Inst Adv Sci & Technol Urbana IL 61820 USA Univ Illinois Carl R Woese Inst Genom Biol Inst Urbana Champaign IL 61820 USA Univ Illinois Carle Illinois Coll Med Urbana IL 61820 USA Swiss Fed Inst Technol Dept Biosyst Sci & Engn Basel Switzerland IBS CARS Ctr Algorithm & Robotized Synth Ulsan South Korea UNIST Dept Chem Ulsan South Korea

Recent years have seen revived interest in computer-assisted organic synthesis1,2. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field1,3-7, including examples leading to advanced natural products6,7. Such methods typically operate on full, literature-derived 'substrate(s)-to-product' reaction rules and cannot be easily extended to the analysis of reaction mechanisms. Here we show that computers equipped with a comprehensive knowledge-base of mechanistic steps augmented by physical-organic chemistry rules, as well as quantum mechanical and kinetic calculations, can use a reaction-network approach to analyse the mechanisms of some of the most complex organic transformations: namely, cationic rearrangements. Such rearrangements are a cornerstone of organic chemistry textbooks and entail notable changes in the molecule's carbon skeleton8-12. The algorithm we describe and deploy at https://***/ generates, within minutes, networks of possible mechanistic steps, traces plausible step sequences and calculates expected product distributions. We validate this algorithm by three sets of experiments whose analysis would probably prove challenging even to highly trained chemists: (1) predicting the outcomes of tail-to-head terpene (THT) cyclizations in which substantially different outcomes are encoded in modular precursors differing in minute structural details;(2) comparing the outcome of THT cyclizations in solution or in a supramolecular capsule;and (3) analysing complex reaction mixtures. Our results support a vision in which computers no longer just manipulate known reaction types1-7 but will help rationalize and discover new, mechanistically complex transformations. Computers equipped with a comprehensive knowledge-base of mechanistic steps augmented by physical-organic chemistry rules, as well as quantum mechanical and kinetic calculations, can use a reaction-network approach to ana

关键词： Biosynthesis Cheminformatics Natural product synthesis

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