scholarly journals EPR studies of intermolecular interactions and competitive binding of drugs in a drug–BSA binding model

2016 ◽  
Vol 18 (32) ◽  
pp. 22531-22539 ◽  
Author(s):  
Y. Akdogan ◽  
M. Emrullahoglu ◽  
D. Tatlidil ◽  
M. Ucuncu ◽  
G. Cakan-Akdogan

EPR spectroscopy is a very promising technique to understand the details of drug binding and competitive drug binding to proteins.

2019 ◽  
Vol 116 (19) ◽  
pp. 9598-9603 ◽  
Author(s):  
Vijay Singh ◽  
Nicolle R. Murphy ◽  
Vijay Balasubramanian ◽  
Joel D. Mainland

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): Only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to 12 monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive-binding model.


2014 ◽  
Vol 11 (94) ◽  
pp. 20131173 ◽  
Author(s):  
C. M. Groh ◽  
M. E. Hubbard ◽  
P. F. Jones ◽  
P. M. Loadman ◽  
N. Periasamy ◽  
...  

The ability to predict how far a drug will penetrate into the tumour microenvironment within its pharmacokinetic (PK) lifespan would provide valuable information about therapeutic response. As the PK profile is directly related to the route and schedule of drug administration, an in silico tool that can predict the drug administration schedule that results in optimal drug delivery to tumours would streamline clinical trial design. This paper investigates the application of mathematical and computational modelling techniques to help improve our understanding of the fundamental mechanisms underlying drug delivery, and compares the performance of a simple model with more complex approaches. Three models of drug transport are developed, all based on the same drug binding model and parametrized by bespoke in vitro experiments. Their predictions, compared for a ‘tumour cord’ geometry, are qualitatively and quantitatively similar. We assess the effect of varying the PK profile of the supplied drug, and the binding affinity of the drug to tumour cells, on the concentration of drug reaching cells and the accumulated exposure of cells to drug at arbitrary distances from a supplying blood vessel. This is a contribution towards developing a useful drug transport modelling tool for informing strategies for the treatment of tumour cells which are ‘pharmacokinetically resistant’ to chemotherapeutic strategies.


2018 ◽  
Author(s):  
Vijay Singh ◽  
Nicolle R. Murphy ◽  
Vijay Balasubramanian ◽  
Joel D. Mainland

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to twelve monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive binding model.


2019 ◽  
Vol 85 (6) ◽  
Author(s):  
Jack Xiaoyu Chen ◽  
Harrison Steel ◽  
Yin-Hu Wu ◽  
Yun Wang ◽  
Jiabao Xu ◽  
...  

ABSTRACT A simple aspirin-inducible system has been developed and characterized in Escherichia coli by employing the Psal promoter and SalR regulation system originally from Acinetobacter baylyi ADP1. Mutagenesis at the DNA binding domain (DBD) and chemical recognition domain (CRD) of the SalR protein in A. baylyi ADP1 suggests that the effector-free form, SalRr, can compete with the effector-bound form, SalRa, binding the Psal promoter and repressing gene transcription. The induction of the Psal promoter was compared in two different gene circuit designs: a simple regulation system (SRS) and positive autoregulation (PAR). Both regulatory circuits were induced in a dose-dependent manner in the presence of 0.05 to 10 µM aspirin. Overexpression of SalR in the SRS circuit reduced both baseline leakiness and the strength of the Psal promoter. The PAR circuit forms a positive feedback loop that fine-tunes the level of SalR. A mathematical simulation based on the SalRr/SalRa competitive binding model not only fit the observed experimental results in SRS and PAR circuits but also predicted the performance of a new gene circuit design for which weak expression of SalR in the SRS circuit should significantly improve induction strength. The experimental result is in good agreement with this prediction, validating the SalRr/SalRa competitive binding model. The aspirin-inducible systems were also functional in probiotic strain E. coli Nissle 1917 and SimCells produced from E. coli MC1000 ΔminD. These well-characterized and modularized aspirin-inducible gene circuits would be useful biobricks for synthetic biology. IMPORTANCE An aspirin-inducible SalR/Psal regulation system, originally from Acinetobacter baylyi ADP1, has been designed for E. coli strains. SalR is a typical LysR-type transcriptional regulator (LTTR) family protein and activates the Psal promoter in the presence of aspirin or salicylate in the range of 0.05 to 10 µM. The experimental results and mathematical simulations support the competitive binding model of the SalR/Psal regulation system in which SalRr competes with SalRa to bind the Psal promoter and affect gene transcription. The competitive binding model successfully predicted that weak SalR expression would significantly improve the inducible strength of the SalR/Psal regulation system, which is confirmed by the experimental results. This provides an important mechanism model to fine-tune transcriptional regulation of the LTTR family, which is the largest family of transcriptional regulators in the prokaryotic kingdom. In addition, the SalR/Psal regulation system was also functional in probiotic strain E. coli Nissle 1917 and minicell-derived SimCells, which would be a useful biobrick for environmental and medical applications.


2015 ◽  
Vol 17 (35) ◽  
pp. 22678-22685 ◽  
Author(s):  
D. Tatlidil ◽  
M. Ucuncu ◽  
Y. Akdogan

We exploit the direct measurements of spin labeled drugs to study drug binding to/release from protein using EPR spectroscopy.


2019 ◽  
Vol 176 (24) ◽  
pp. 4731-4744
Author(s):  
Victoria Georgi ◽  
Alexey Dubrovskiy ◽  
Stephan Steigele ◽  
Amaury E. Fernández‐Montalván

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