A Study of the Interaction of a New Benzimidazole Schiff Base with Synthetic and Simulated Membrane Models of Bacterial and Mammalian Membranes

Aragón-Muriel, Alberto; Liscano, Yamil; Morales‐Morales, David; Polo-Cerón, Dorian; Oñate-Garzón, José

doi:10.3390/membranes11060449

Cited by 6 publications

(7 citation statements)

References 51 publications

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“…Benzene [149,415,417], Hexane [415] Other Lauryl Ether Sulfate [532], Dodecyl Sulfate [533], CyMe4-BTPhen [534], Acetone [420], DMSO [417,420,535], bis-(3-hydroxy-4-pyridinonato) zinc(II) complex [536], calix [4], resorcinarenes [537], dihydropyrimidine analogues [538], Choline carboxylates [539], Synthetic xanthophylls [540], Triton X-100 [541,542], Benzoic acid [284,287,387], Methane [379], Borneol [282,543], Osthole [282,543], Isopulegol [544], Benzylpiperidine [545], Benzimidazole derivatives [546], Aldehydes [547] Inorganic…”

Section: Application Xenobioticmentioning

confidence: 99%

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

2021

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We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard “lock and key” paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

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Section: Application Xenobioticmentioning

confidence: 99%

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

2021

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“…Thus, several studies support that increasing the charge on a peptide sequence improves antimicrobial activity [11]. On the other hand, the hydrophobicity found for peptide ∆M2 does not exceed the threshold of 50%, indicating that the peptide does not have high hemolytic activity for mammalian cells and its antimicrobial activity is not diminished [15,30].…”

Section: Physicochemical Parametersmentioning

confidence: 93%

“…Because of the complexity, structure, and functionality of real membranes, as well as various lipid-lipid and lipid-protein interactions, artificial membrane models are used to study the effect of peptides on membranes [15]. The application of biophysical techniques such as infrared spectroscopy (FT-IR) to study changes in the vibrations of functional groups of phospholipids in a membrane model as a result of peptide interaction was employed in other studies [16,17].…”

Section: Introductionmentioning

confidence: 99%

Integrating In Vitro and In Silico Analysis of a Cationic Antimicrobial Peptide Interaction with Model Membranes of Colistin-Resistant Pseudomonas aeruginosa Strains

et al. 2022

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Bacterial antibiotic resistance is a serious global public health concern. Infections caused by colistin-resistant Pseudomonas aeruginosa (CRPa) strains represent a serious threat due to their considerable morbidity and mortality rates, since most of the current empirical antibiotic therapies are ineffective against these strains. Accordingly, cationic antimicrobial peptides (CAMPs) have emerged as promising alternatives to control resistant bacteria. In this study, the interaction of a CAMP derived from cecropin D-like (∆M2) with model membranes mimicking bacterial biomembranes of wild-type (WTPa) strains of P. aeruginosa and CRPa was evaluated through in vitro and in silico approaches. In vitro interaction was determined by infrared spectroscopy, whereas in silico molecular dynamics was performed to predict specific interactions between amino acids of ∆M2 and lipids of model membrane systems. Experimental analysis showed this peptide interacted with the lipids of bacterial-like model membranes of WTPa and CRPa. In both cases, an increase in the concentration of peptides induced an increase in the phase transition temperature of the lipid systems. On the other hand, the peptides in solution underwent a transition from a random to a helical secondary structure after interacting with the membranes mostly favored in the CRPa system. The α-helix structure percentage for ΔM2 interacting with WTPa and CRPa lipid systems was 6.4 and 33.2%, respectively. Finally, molecular dynamics showed ∆M2 to have the most affinities toward the phospholipids palmitoyl-oleyl-phosphatidylglycerol (POPG) and palmitoyl-oleoyl-phosphatidylethanolamine (POPE) that mimic membranes of WTPa and CRPa, respectively. This work provides clues for elucidating the membrane-associated mechanism of action of ∆M2 against colistin-susceptible and -resistant strains of Pseudomonas aeruginosa.

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“…If the concentration of R|L is smaller than the concentration of both the free proteins and the final complexes, it is a good approximation [18] to neglect the variation in time of R|L in Equation (10), leading to the most commonly used relation (8). Accordingly, the generation of a receptor-ligand complex can be considered to occur immediately once the receptor-ligand distance is sufficiently small.…”

Section: Modeling Receptor-ligand Kineticsmentioning

confidence: 99%

Modeling Receptor Motility along Advecting Lipid Membranes

et al. 2022

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This work aims to overview multiphysics mechanobiological computational models for receptor dynamics along advecting cell membranes. Continuum and statistical models of receptor motility are the two main modeling methodologies identified in reviewing the state of the art. Within the former modeling class, a further subdivision based on different biological purposes and processes of proteins’ motion is recognized; cell adhesion, cell contractility, endocytosis, and receptor relocations on advecting membranes are the most relevant biological processes identified in which receptor motility is pivotal. Numerical and/or experimental methods and approaches are highlighted in the exposure of the reviewed works provided by the literature, pertinent to the topic of the present manuscript. With a main focus on the continuum models of receptor motility, we discuss appropriate multiphyisics laws to model the mass flux of receptor proteins in the reproduction of receptor relocation and recruitment along cell membranes to describe receptor–ligand chemical interactions, and the cell’s structural response. The mass flux of receptor modeling is further supported by a discussion on the methodology utilized to evaluate the protein diffusion coefficient developed over the years.

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A Study of the Interaction of a New Benzimidazole Schiff Base with Synthetic and Simulated Membrane Models of Bacterial and Mammalian Membranes

Cited by 6 publications

References 51 publications

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

Integrating In Vitro and In Silico Analysis of a Cationic Antimicrobial Peptide Interaction with Model Membranes of Colistin-Resistant Pseudomonas aeruginosa Strains

Modeling Receptor Motility along Advecting Lipid Membranes

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