Evidence map›Paper›PMID 28876890›Full record

ArticleAccounts of chemical research2017

Bioorthogonal Cycloadditions: Computational Analysis with the Distortion/Interaction Model and Predictions of Reactivities.

Fang Liu, Yong Liang, K N Houk

Open access · greenAbstract read
In one paragraph

Article in Accounts of chemical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
9.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 190 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Fang LiuState Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing University , Nanjing 210023, China.ORCID 0000-0002-0046-8434
Yong LiangState Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing University , Nanjing 210023, China.
K N HoukDepartment of Chemistry and Biochemistry, University of California , Los Angeles, California 90095, United States.ORCID 0000-0002-8387-5261
University of California, Los Angeles · USNanjing University · CN

Funding

Bioorthogonal CycloadditionsR01GM109078 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HOUK, KENDALL N · 2015 to 2018
$1.1M
NIGMS NIH HHS R01 GM109078
6 · The paper itself

Abstract

Bioorthogonal chemistry has had a major impact on the study of biological processes in vivo. Biomolecules of interest can be tracked by using probes and reporters that do not react with cellular components and do not interfere with metabolic processes in living cells. Much time and effort has been devoted to the screening of potential bioorthogonal reagents experimentally. This Account describes how our groups have performed computational screening of reactivity and mutual orthogonality. Our collaborations with experimentalists have led to the development of new and useful reactions. Dozens of bioorthogonal cycloadditions have been reported in the literature in the past few years, but as interest in tracking multiple targets arises, our computational screening has gained importance for the discovery of new mutually orthogonal bioorthogonal cycloaddition pairs. The reactivities of strained alkenes and alkynes with common 1,3-dipoles such as azides, along with mesoionic sydnones and other novel 1,3-dipoles, have been explored. Studies of "inverse-electron-demand" dienes such as triazines and tetrazines that have been used in bioorthogonal Diels-Alder cycloadditions are described. The color graphics we have developed give a snapshot of whether reactions are fast enough for cellular applications (green), adequately reactive for labeling (yellow), or only useful for synthesis or do not occur at all (red). The colors of each box give an instant view of rates, while bar graphs provide an analysis of the factors that control reactivity. This analysis uses the distortion/interaction or activation strain model of cycloaddition reactivity developed independently by our group and that of F. Matthias Bickelhaupt in The Netherlands. The model analyzes activation barriers in terms of the energy required to distort the reactants to the transition state geometry. This energy, called the distortion energy or activation strain, constitutes the major component of the activation energy. The strong bonding interaction between the termini of the two reactants, which we call the interaction energy, overcomes the distortion energy and leads to the new bonds in the products. This Account describes how we have analyzed and predicted bioorthogonal cycloaddition reactivity using the distortion/interaction model and how our experimental collaborators have employed these insights to create new bioorthogonal cycloadditions. The graphics we use document and predict which combinations of cycloadditions will be useful in bioorthogonal chemistry and which pairs of reactions are mutually orthogonal. For example, the fast reaction of 5-phenyl-1,2,4-triazine and a thiacycloheptyne will not interfere with the other fast reaction of 3,6-diphenyl-1,2,4,5-tetrazine and a cyclopropene. No cross reactions will occur, as these are very slow reactions.

Indexed as

Computer SimulationCycloaddition ReactionModels, ChemicalCyclopropanesCyclopropanescyclopropene

Identifiers

PMID28876890
PMCPMC5675536
OpenAlexW2752175890

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.