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Chemosensors
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State-of-the-Art in Chemical Sensors Modelling and Theoretical Statements
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State-of-the-Art in Chemical Sensors Modelling and Theoretical Statements (Closed)

A topical collection in Chemosensors (ISSN 2227-9040).

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Editors

Dr. Eleonora Alfinito

E-Mail Website
Collection Editor
Department of Mathematics and Physics “E. De Giorgi”, University of Salento, Via Arnesano, I-73100 Lecce, Italy
Interests: proteotronics; biosensors; electronic transport in biological matter; modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Rosella Cataldo

E-Mail Website
Collection Editor
Department of Mathematics and Physics “E. De Giorgi”, University of Salento, Via Arnesano, I-73100 Lecce, Italy
Interests: CFD; proteotronics: electrical properties of biomolecule; biomedical image analysis

Topical Collection Information

Dear colleagues,

The dramatic growth in the interest toward chemical sensors based on aptamers, chemical aptasensors, requires one to take stock of the situation, recollecting ideas and information about the state-of-the-art and possible developments. To complement experiments with appropriate modelling is the most effective way to speed up progress. Aptamers, as opposed to proteins, are small biomolecules which, in principle, allow massive calculations, such as those necessary in molecular dynamics and density functional theory, useful, for example, to envision their structure and to predict the docking with the target or to design the best strategy for functionalization on an appropriate substrate. On the other side, aptamer extreme flexibility, which is a very remarkable feature in supporting their high affinity, makes both structure prediction and the envision of binding scenarios (conformational selection, induced fit, etc.) very challenging.  Furthermore, even more novel kinds of modified aptamers have been developed with improved affinity with respect to the original sequences—a satisfactory and complete description of their performances, the role of modifications in increasing affinity require a sort of theoretical investigation yet to come. Aptasensors are, finally, chemical sensors and, for them, some standard issues concerning the interpretation of dose–response, linear and dynamical regime, impedance and amperometric data, diffusion, charge transport and so on deserve attention and consolidation. Feasibility and proof of concept studies are also welcome.

Prof. Dr. Eleonora Alfinito
Dr. Rosella Cataldo
Collection Editors

If you want to learn more information or need any advice, you can contact the Section Managing Editor Tammy Zhang via <[email protected]> directly.

Manuscript Submission Information

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Keywords

  • affinity
  • binding scenarios
  • computational modelling
  • density functional theory
  • docking
  • folding
  • impedance models
  • molecular dynamics
  • proof-of-concept

Published Papers (4 papers)

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2022

Jump to: 2021

12 pages, 3095 KiB  
Article
Studies on the Interaction of Rose Bengal with the Human Serum Albumin Protein under Spectroscopic and Docking Simulations Aspects in the Characterization of Binding Sites
by Maurício I. Yoguim, Giulia S. Grandini, Luiza de C. Bertozo, Ignez Caracelli, Valdecir F. Ximenes and Aguinaldo R. de Souza
Chemosensors 2022, 10(11), 440; https://doi.org/10.3390/chemosensors10110440 - 25 Oct 2022
Cited by 5 | Viewed by 1722
Abstract
Rose Bengal (RB) is a xanthene dye used as a sensitizer to convert triplet (3O2) to singlet oxygen (1O2). This photophysical property makes it one of the most used dyes in photodynamic therapy. Thus, understanding [...] Read more.
Rose Bengal (RB) is a xanthene dye used as a sensitizer to convert triplet (3O2) to singlet oxygen (1O2). This photophysical property makes it one of the most used dyes in photodynamic therapy. Thus, understanding its interaction with biomacromolecules can provide helpful information about its mode of action and application. The protein chosen for this study was human serum albumin (HSA), which has nine binding sites for fatty acids (FA), and at least three sites for interactions of drugs (DS). The complexation of HSA with RB caused a maximum bathochromic shift in its absorption. From this displacement and the application of the Benesi–Hildebrand model, the ligand–protein association constant (3.90 ± 0.08 × 105 M−1) was obtained. Applying the Job’s Plot method resulted in a 6:1 (ligand-protein) stoichiometry. The determination of preferred binding sites was performed by measuring the association constant in the presence of drugs for which their binding sites in HSA are already well established, such as warfarin (DS1), ibuprofen (DS2 and FA6), digitoxin (DS3), diazepam (DS2), and diflunisal (DS2 and FA6). From these studies, it was found that RB is able to bind at DS1, DS3, and FA6 sites but not at DS2. Subsequently, molecular docking studies using the 2BX8 and 2BXE crystallographic structures were performed and corroborated the experimental results. The lowest energy poses were −52.13, −58.79, and −67.55 kcal mol−1 at DS1, DS3, and FA6, respectively. Conversely, DS2 was the lower affinity binding site. In conclusion, HSA has a high affinity for RB, being able to bind up to six dye molecules. Full article
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16 pages, 48194 KiB  
Communication
Chalcone-Based Colorimetric Chemosensor for Detecting Ni2+
by Sungjin Moon and Cheal Kim
Chemosensors 2022, 10(5), 151; https://doi.org/10.3390/chemosensors10050151 - 20 Apr 2022
Cited by 8 | Viewed by 3242
Abstract
The first chalcone-based colorimetric chemosensor DPP (sodium (E)-2,4-dichloro-6-(3-oxo-3-(pyridine-2-yl)prop-1-en-1-yl)phenolate) was synthesized for detecting Ni2+ in near-perfect water. The synthesis of DPP was validated by using 1H, 13C NMR and ESI-MS. DPP selectively sensed Ni2+ through the color variation [...] Read more.
The first chalcone-based colorimetric chemosensor DPP (sodium (E)-2,4-dichloro-6-(3-oxo-3-(pyridine-2-yl)prop-1-en-1-yl)phenolate) was synthesized for detecting Ni2+ in near-perfect water. The synthesis of DPP was validated by using 1H, 13C NMR and ESI-MS. DPP selectively sensed Ni2+ through the color variation from yellow to purple. Detection limit of DPP for Ni2+ was calculated to be 0.36 μM (3σ/slope), which is below the standard (1.2 μM) set by the United States Environmental Protection Agency (EPA).The binding ratio of DPP to Ni2+ was determined as a 1:1 by using a Job plot and ESI-mass. The association constant of DPP and Ni2+ was calculated as 1.06 × 104 M−1 by the non-linear fitting analysis. In real samples, the sensing application of DPP for Ni2+ was successfully performed. DPP-coated paper-supported strips could also be used for detecting Ni2+. The binding mechanism of DPP to Ni2+ was proposed by ESI-MS, Job plot, UV-vis, FT-IR spectroscopy, and DFT calculations. Full article
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22 pages, 5568 KiB  
Review
Smartphone-Operated Wireless Chemical Sensors: A Review
by Somasundaram Chandra Kishore, Kanagesan Samikannu, Raji Atchudan, Suguna Perumal, Thomas Nesakumar Jebakumar Immanuel Edison, Muthulakshmi Alagan, Ashok K. Sundramoorthy and Yong Rok Lee
Chemosensors 2022, 10(2), 55; https://doi.org/10.3390/chemosensors10020055 - 30 Jan 2022
Cited by 29 | Viewed by 6730
Abstract
Wireless chemical sensors have been developed as a result of advances in chemical sensing and wireless communication technology. Because of their mobility and widespread availability, smartphones have been extensively combined with sensors such as hand-held detectors, sensor chips, and test strips for biochemical [...] Read more.
Wireless chemical sensors have been developed as a result of advances in chemical sensing and wireless communication technology. Because of their mobility and widespread availability, smartphones have been extensively combined with sensors such as hand-held detectors, sensor chips, and test strips for biochemical detection. Smartphones are frequently used as controllers, analyzers, and displayers for quick, authentic, and point-of-care monitoring, which may considerably streamline the design and lower the cost of sensing systems. This study looks at the most recent wireless and smartphone-supported chemical sensors. The review is divided into four different topics that emphasize the basic types of wireless smartphone-operated chemical sensors. According to a study of 114 original research publications published during recent years, market opportunities for wireless and smartphone-supported chemical sensor systems include environmental monitoring, healthcare and medicine, food quality, sport, and fitness. The issues and illustrations for each of the primary chemical sensors relevant to many application areas are covered. In terms of performance, the advancement of technologies related to chemical sensors will result in smaller and more lightweight, cost-effective, versatile, and durable devices. Given the limitations, we suggest that wireless and smartphone-supported chemical sensor systems play a significant role in the sensor Internet of Things. Full article
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2021

Jump to: 2022

15 pages, 4307 KiB  
Article
Drift Compensation on Massive Online Electronic-Nose Responses
by Jianhua Cao, Tao Liu, Jianjun Chen, Tao Yang, Xiuxiu Zhu and Hongjin Wang
Chemosensors 2021, 9(4), 78; https://doi.org/10.3390/chemosensors9040078 - 11 Apr 2021
Cited by 15 | Viewed by 3011
Abstract
Gas sensor drift is an important issue of electronic nose (E-nose) systems. This study follows this concern under the condition that requires an instant drift compensation with massive online E-nose responses. Recently, an active learning paradigm has been introduced to such condition. However, [...] Read more.
Gas sensor drift is an important issue of electronic nose (E-nose) systems. This study follows this concern under the condition that requires an instant drift compensation with massive online E-nose responses. Recently, an active learning paradigm has been introduced to such condition. However, it does not consider the “noisy label” problem caused by the unreliability of its labeling process in real applications. Thus, we have proposed a class-label appraisal methodology and associated active learning framework to assess and correct the noisy labels. To evaluate the performance of the proposed methodologies, we used the datasets from two E-nose systems. The experimental results show that the proposed methodology helps the E-noses achieve higher accuracy with lower computation than the reference methods do. Finally, we can conclude that the proposed class-label appraisal mechanism is an effective means of enhancing the robustness of active learning-based E-nose drift compensation. Full article
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