Dataset Information

A photochemical method to evidence directional molecular motions.

ABSTRACT: Light driven synthetic molecular motors represent crucial building blocks for advanced molecular machines and their applications. A standing challenge is the development of very fast molecular motors able to perform rotations with kHz, MHz or even faster frequencies. Central to this challenge is the direct experimental evidence of directionality because analytical methods able to follow very fast motions rarely deliver precise geometrical insights. Here, a general photochemical method for elucidation of directional motions is presented. In a macrocyclization approach the molecular motor rotations are restricted and forced to proceed in two separate ~180° rotation-photoequilibria. Therefore, all four possible photoinduced rotation steps (clockwise and counterclockwise directions) can be quantified. Comparison of the corresponding quantum yields to the unrestricted motor delivers direct evidence for unidirectionality. This method can be used for any ultrafast molecular motor even in cases where no high energy intermediates are present during the rotation cycle.

SUBMITTER: Regen-Pregizer BL

PROVIDER: S-EPMC10390485 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A photochemical method to evidence directional molecular motions.

Regen-Pregizer Benjamin Lukas BL Ozcelik Ani A Mayer Peter P Hampel Frank F Dube Henry H

Nature communications 20230731 1

Light driven synthetic molecular motors represent crucial building blocks for advanced molecular machines and their applications. A standing challenge is the development of very fast molecular motors able to perform rotations with kHz, MHz or even faster frequencies. Central to this challenge is the direct experimental evidence of directionality because analytical methods able to follow very fast motions rarely deliver precise geometrical insights. Here, a general photochemical method for elucid ...[more]

PMID: 37524701

Similar Datasets

Project description:Influenza virus motility is based on cooperation between two viral spike proteins, hemagglutinin (HA) and neuraminidase (NA), and is a major determinant of virus infectivity. To translocate a virus particle on the cell surface, HA molecules exchange viral receptors and NA molecules accelerate the receptor exchange of HA. This type of virus motility was recently identified in influenza A virus (IAV). To determine if other influenza virus types have a similar receptor exchange mechanism-driven motility, we investigated influenza C virus (ICV) motility on a receptor-fixed glass surface. This system excludes receptor mobility, which makes it more desirable than a cell surface for demonstrating virus motility by receptor exchange. Like IAV, ICV was observed to move across the receptor-fixed surface. However, in contrast to the random movement of IAV, a filamentous ICV strain, Ann Arbor/1/50 (AA), moved in a straight line, in a directed manner, and at a constant rate, whereas a spherical ICV strain, Taylor/1233/47 (Taylor), moved randomly, similar to IAV. The AA and Taylor viruses each moved with a combination of gradual (crawling) and rapid (gliding) motions, but the distances of crawling and gliding for the AA virus were shorter than those of the Taylor virus. Our findings indicate that like IAV, ICV also has a motility that is driven by the receptor exchange mechanism. However, compared with IAV movement, filamentous ICV movement is highly regulated in both direction and speed. Control of ICV movement is based on its specific motility employing short crawling and gliding motions as well as its own filamentous morphology.IMPORTANCE Influenza virus enters into a host cell for infection via cellular endocytosis. Human influenza virus infects epithelial cells of the respiratory tract, the surfaces of which are hidden by abundant cilia that are inactive in endocytosis. An open question is the manner by which the virus migrates to endocytosis-active domains. In analyzing individual virus behaviors through single-virus tracking, we identified a novel function of the hemagglutinin and esterase of influenza C virus (ICV) as the motility machinery. Hemagglutinin iteratively exchanges a viral receptor, causing virus movement. Esterase degrades the receptors along the trajectory traveled by the virus and prevents the virus from moving backward, causing directional movement. We propose that ICV has a unique motile machinery directionally controlled via hemagglutinin sensing the receptor density manipulated by esterase.

Project description:BackgroundGenes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation.ResultsWe analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex) by adopting a measure of directional dependence based on a copula function. We have compared our results with those from other methods in the literature. Although microarray results show a transcriptional co-regulation pattern and do not imply that the gene products are physically interactive, this tight genetic connection may suggest that each gene product has either direct or indirect connections between the other gene products. Indeed, recent comprehensive analysis of a protein interaction map revealed that those histone genes are physically connected with each other, supporting the results obtained by our method.ConclusionThe results illustrate that our method can be an alternative to Bayesian networks in modeling gene interactions. One advantage of our approach is that dependence between genes is not assumed to be linear. Another advantage is that our approach can detect directional dependence. We expect that our study may help to design artificial drug candidates, which can block or activate biologically meaningful pathways. Moreover, our copula approach can be extended to investigate the effects of local environments on protein-protein interactions. The copula mutual information approach will help to propose the new variant of ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks): an algorithm for the reconstruction of gene regulatory networks.

Dataset Information

A photochemical method to evidence directional molecular motions.

Publications

A photochemical method to evidence directional molecular motions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets