Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry

Kowalik, M.; Gothard, Chris M.; Drews, Aaron M.; Gothard, Nosheen A.; Weckiewicz, Alex; Fuller, Patrick E.; Grzybowski, Bartosz A.; Bishop, Kyle J. M.

doi:10.1002/anie.201202209

Cited by 124 publications

(131 citation statements)

References 9 publications

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“…The number of possible synthetic pathways can be astronomical having 10 19 routes of just 5 synthetic steps. Network analysis of Kowalik et al (2012) identified optimal synthetic pathways of single and multiple-target syntheses using a simulated annealing-based network optimization. These optimizations help in the synthesis of drug candidate variants for lead selection.…”

Section: The Use Of Molecular Network In Drug Designmentioning

confidence: 99%

Structure and dynamics of molecular networks: A novel paradigm of drug discovery

Csermely

Korcsmáros

Kiss

et al. 2013

Pharmacology & Therapeutics

809

661

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Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The “central hit strategy” selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The “network influence strategy” works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.

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Section: The Use Of Molecular Network In Drug Designmentioning

confidence: 99%

Structure and dynamics of molecular networks: A novel paradigm of drug discovery

Csermely

Korcsmáros

Kiss

et al. 2013

Pharmacology & Therapeutics

809

661

View full text Add to dashboard Cite

show abstract

“…In 1990 (Lawson and Kallies, 1990) observed that the Beilstein database forms an implicit network resulting in “a map of practically all known synthetic pathways from almost any starting material to almost any product.” In 2005 this idea was further developed by Fialkowski et al (2005) who first converted the Beilstein database into a network, called the NOC, and further investigated various properties of the NOC in a series of publications (Fialkowski et al, 2005; Bishop et al, 2006; Grzybowski et al, 2009; Gothard et al, 2012; Kowalik et al, 2012; Soh et al, 2012). The important feature of this network is that a computer with an effective network search algorithm is able to optimize a synthesis route very quickly.…”

Section: Methodsmentioning

confidence: 99%

Alternative methods of processing bio-feedstocks in formulated consumer product design

2014

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In this work new methods of processing bio-feedstocks in the formulated consumer products industry are discussed. Our current approach to formulated products design is based on heuristic knowledge of formulators that allows selecting individual compounds from a library of available materials with known properties. We speculate that most of the compounds (or functions) that make up the product to be designed can potentially be obtained from a few bio-sources. In this case, it may be possible to design a sequence of transformations required to convert feedstocks into products with desired properties, analogous to a metabolic pathway of a complex organism. We conceptualize some novel approaches to processing bio-feedstocks with the aim of bypassing the step of a fixed library of ingredients. Two approaches are brought forward: one making use of knowledge-based expert systems and the other making use of applications of metabolic engineering and dynamic combinatorial chemistry.

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“…3), "people said it was bullshit", he laughs. But that changed in 2012, when he and his team published a trio of landmark papers [4][5][6] showing Chematica in action. For example, the program discovered 4 a slew of 'one pot' syntheses in which reagents could be thrown into a vessel one after the other, without all the troublesome separation and purification of products after each step.…”

Section: Stronger Faster Cheapermentioning

confidence: 99%

Organic synthesis: The robo-chemist

Peplow¹

2014

Nature

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Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry

Cited by 124 publications

References 9 publications

Structure and dynamics of molecular networks: A novel paradigm of drug discovery

Structure and dynamics of molecular networks: A novel paradigm of drug discovery

Alternative methods of processing bio-feedstocks in formulated consumer product design

Organic synthesis: The robo-chemist

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