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Membranes
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Biomimetic Liquid Chromatographic and In Silico Studies of Molecule-Biomembranes Interactions
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Biomimetic Liquid Chromatographic and In Silico Studies of Molecule-Biomembranes Interactions

A special issue of Membranes (ISSN 2077-0375). This special issue belongs to the section "Biological Membrane Functions".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 3544

Special Issue Editor

Dr. Anna Sobańska

E-Mail Website
Guest Editor
Department of Analytical Chemistry, Faculty of Pharmacy, Medical University of Lodz, Łódź, Poland
Interests: QSAR; liquid chromatography; ADMET studies in silico and in vitro; environmental toxicology; spectroscopy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Chromatographic techniques in which a separation process is designed to mimic the membrane-solute interactions are of utmost importance, especially in medicinal and pharmaceutical chemistry and in environmental studies.

We are pleased to invite you to submit manuscripts to the Special Issue of Membranes whose aim is to present recent developments in the field of chromatographic studies related to solute-membrane interactions.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

  • Preparation and/or characterization of novel stationary or mobile phases for biomimetic liquid chromatography
  • Applications of biomimetic chromatography (e.g., IAM chromatography, TLC, HPLC, chromatography with micellar or microemulsion mobile phases, electrochromatographic techniques) to studies of properties and phenomena related to solute-biomembrane interactions:
    • physico-chemical properties of compounds
    • bioactivity, ADMET processes in humans and animals, studies of biomembrane permeability
    • environmental impact of compounds (bioconcentration, bioaccumulation, biomagnification, mobility in soil, environmental persistence)
  • Applications of in silico/QSAR studies to model the ability of molecules to cross biological barriers. 

I look forward to receiving your contributions.

Dr. Anns Sobańska
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Membranes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Immobilized Artificial Membrane (IAM) chromatography
  • biomimetic chromatography
  • ADMET Studies
  • solute-biomembrane interactions
  • biomembrane permeability
  • IAM chromatographic bioconcentration bioaccumulation studies
  • IAM chromatographic soil mobility studies

Published Papers (3 papers)

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Research

18 pages, 2937 KiB  
Article
Chromatographic Data in Statistical Analysis of BBB Permeability Indices
by Karolina Wanat and Elżbieta Brzezińska
Membranes 2023, 13(7), 623; https://doi.org/10.3390/membranes13070623 - 26 Jun 2023
Viewed by 906
Abstract
Blood–brain barrier (BBB) permeability is an essential phenomena when considering the treatment of neurological disorders as well as in the case of central nervous system (CNS) adverse effects caused by peripherally acting drugs. The presented work contains statistical analyses and the correlation assessment [...] Read more.
Blood–brain barrier (BBB) permeability is an essential phenomena when considering the treatment of neurological disorders as well as in the case of central nervous system (CNS) adverse effects caused by peripherally acting drugs. The presented work contains statistical analyses and the correlation assessment of the analyzed group of active pharmaceutical ingredients (APIs) with their BBB-permeability data collected from the literature (such as computational log BB; Kp,uu,brain, and CNS+/− groups). A number of regression models were constructed in order to observe the connections between the APIs’ physicochemical properties in combination with their retention data from the chromatographic experiments (TLC and HPLC) and the indices of bioavailability in the CNS. Conducted analyses confirm that descriptors significant in BBB permeability modeling are hydrogen bond acceptors and donors, physiological charge, or energy of the lowest unoccupied molecular orbital. These molecular descriptors were the basis, along with the chromatographic data from the TLC in log BB regression analyses. Normal-phase TLC data showed a significant contribution to the creation of the log BB regression model using the multiple linear regression method. The model using them showed a good predictive value at the level of R2 = 0.87. Models for Kp,uu,brain resulted in lower statistics: R2 = 0.56 for the group of 23 APIs with the participation of k IAM. Full article
(This article belongs to the Special Issue Biomimetic Liquid Chromatographic and In Silico Studies of Molecule-Biomembranes Interactions)
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18 pages, 3566 KiB  
Article
Electrodialysis Deacidification of Acid Hydrolysate in Hemicellulose Saccharification Process: Membrane Fouling Identification and Mechanisms
by Xitao Luo, Lingling Sun, Qinghui Shou, Xiangfeng Liang and Huizhou Liu
Membranes 2023, 13(3), 256; https://doi.org/10.3390/membranes13030256 - 21 Feb 2023
Cited by 1 | Viewed by 1084
Abstract
Acid saccharification of hemicelluloses offers promising pathways to sustainably diversify the revenue of the lignocellulose biorefinery industry. Electrodialysis to separate inorganic acids from acid hydrolysate in the hemicellulose saccharification process could realize the recovery of sulfuric acid, and significantly reduced the chemical consumption [...] Read more.
Acid saccharification of hemicelluloses offers promising pathways to sustainably diversify the revenue of the lignocellulose biorefinery industry. Electrodialysis to separate inorganic acids from acid hydrolysate in the hemicellulose saccharification process could realize the recovery of sulfuric acid, and significantly reduced the chemical consumption than the traditional ion exchange resins method. In this work, the deacidification of corncob acid hydrolysate was conducted by a homemade electrodialysis apparatus. The results showed that: (1) more than 99% of acid can be removed through the electrodialysis process; (2) A non-negligible membrane fouling occurred during the electrodialysis process, which aggravated with the repeated batch running The final global system resistance rose from 15.8 Ω (1st batch) to 43.9 Ω (10th batch), and the treatment ending time was delayed from 120 min (1st batch) to 162 min (10th batch); (4) About 90% of protein, 70% of ferulate acid, and 80% of p-coumarate acid precipitated from the corncob acid hydrolysate during the electrodialysis process. The zeta potential of corncob acid hydrolysate changed from a positive value to a negative value, and an isoelectric point around pH 2.3 was reached. HSQC, FTTR, and GPC, along with SEM and EDS analysis, revealed that the fouling layers mostly consisted of hydrolysates of protein and lignin. The result of HSQC indicated that the membrane foulant may exist in the form of lignin–carbohydrate complexes, as the lignin component of the membrane foulant is in the form of p-coumarate and ferulate. From the result of FTIR, a strong chemical bonding, such as a covalent linkage, existed between the lignin and protein in the membrane foulant. Throughout the electrodialysis process, the increased pH decreased the stability of colloidal particles, including lignin and proteins. Destabilized colloidal particles started to self-aggregate and form deposits on the anion exchange membrane’s surface. Over time, these deposits covered the entire membrane surface and the spaces between the membranes. Eventually, they attached to the surface of the cation exchange membrane. In the end, a suggestion to control and minimize membrane fouling in this process was discussed: lower pH as a process endpoint and a post-treatment method. Full article
(This article belongs to the Special Issue Biomimetic Liquid Chromatographic and In Silico Studies of Molecule-Biomembranes Interactions)
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17 pages, 2138 KiB  
Article
Affinity of Compounds for Phosphatydylcholine-Based Immobilized Artificial Membrane—A Measure of Their Bioconcentration in Aquatic Organisms
by Anna W. Sobańska
Membranes 2022, 12(11), 1130; https://doi.org/10.3390/membranes12111130 - 11 Nov 2022
Cited by 2 | Viewed by 1098
Abstract
The BCF (bioconcentration factor) of solutes in aquatic organisms is an important parameter because many undesired chemicals enter the ecosystem and affect the wildlife. Chromatographic retention factor log kwIAM obtained from immobilized artificial membrane (IAM) HPLC chromatography with buffered, aqueous mobile [...] Read more.
The BCF (bioconcentration factor) of solutes in aquatic organisms is an important parameter because many undesired chemicals enter the ecosystem and affect the wildlife. Chromatographic retention factor log kwIAM obtained from immobilized artificial membrane (IAM) HPLC chromatography with buffered, aqueous mobile phases and calculated molecular descriptors obtained for a group of 120 structurally unrelated compounds were used to generate useful models of log BCF. It was established that log kwIAM obtained in the conditions described in this study is not sufficient as a sole predictor of bioconcentration. Simple, potentially useful models based on log kwIAM and a selection of readily available, calculated descriptors and accounting for over 88% of total variability were generated using multiple linear regression (MLR), partial least squares (PLS) regression and artificial neural networks (ANN). The models proposed in the study were tested on an external group of 120 compounds and on a group of 40 compounds with known experimental log BCF values. It was established that a relatively simple MLR model containing four independent variables leads to satisfying BCF predictions and is more intuitive than PLS or ANN models. Full article
(This article belongs to the Special Issue Biomimetic Liquid Chromatographic and In Silico Studies of Molecule-Biomembranes Interactions)
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