Evidence map›Paper›PMID 34549951›Full record

ArticleACS nano2021

Toward Chemotactic Supramolecular Nanoparticles: From Autonomous Surface Motion Following Specific Chemical Gradients to Multivalency-Controlled Disassembly.

Chiara Lionello, Andrea Gardin, Annalisa Cardellini, Davide Bochicchio, Manisha Shivrayan, Ann Fernandez, S Thayumanavan, Giovanni M Pavan

Abstract read
In one paragraph

Article in ACS nano, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling.Proceedings of the National Academy of Sciences of the United States of America · 2023
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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

8 authors.

Chiara LionelloDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.ORCID 0000-0002-7491-8952
Andrea GardinDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.
Annalisa CardelliniDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.ORCID 0000-0002-6359-6118
Davide BochicchioDepartment of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, 6962 Lugano-Viganello, Switzerland.ORCID 0000-0002-3682-9086
Manisha ShivrayanDepartment of Chemistry, Center for Bioactive Delivery at the Institute for Applied Life Sciences, University of Massachusetts, Amherst, Massachusetts 01003, United States.
Ann FernandezDepartment of Chemistry, Center for Bioactive Delivery at the Institute for Applied Life Sciences, University of Massachusetts, Amherst, Massachusetts 01003, United States.ORCID 0000-0002-7139-0646
S ThayumanavanDepartment of Chemistry, Center for Bioactive Delivery at the Institute for Applied Life Sciences, University of Massachusetts, Amherst, Massachusetts 01003, United States.ORCID 0000-0002-6475-6726
Giovanni M PavanDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.ORCID 0000-0002-3473-8471

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nature designs chemotactic supramolecular structures that can selectively bind specific groups present on surfaces, autonomously scan them moving along density gradients, and react once a critical concentration is encountered. Since such properties are key in many biological functions, these also offer inspirations for designing artificial systems capable of similar bioinspired autonomous behaviors. One approach is to use soft molecular units that self-assemble in an aqueous solution generating nanoparticles (NPs) that display specific chemical groups on their surface, enabling multivalent interactions with complementarily functionalized surfaces. However, a first challenge is to explore the behavior of these assemblies at sufficiently high-resolution to gain insights on the molecular factors controlling their behaviors. Here, by coupling coarse-grained molecular models and advanced simulation approaches, we show that it is possible to study the (autonomous or driven) motion of self-assembled NPs on a receptor-grafted surface at submolecular resolution. As an example, we focus on self-assembled NPs composed of facially amphiphilic oligomers. We observe how tuning the multivalent interactions between the NP and the surface allows to control of the NP binding, its diffusion along chemical surface gradients, and ultimately, the NP reactivity at determined surface group densities.

Indexed as

NanoparticlesDiffusionModels, MolecularMotionautonomous motionchemotaxiscoarse-grainingmolecular simulationnanoparticlesself-assemblystimuli-responsive

Identifiers

PMID34549951
PMCPMC8552489

What OpenQuestion holds

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LicenceCC BY
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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.