How to calculate pH-dependent binding rates for receptor–ligand systems based on thermodynamic simulations with different binding motifs

Ray, Sourav; Sunkara, Vikram; Schütte, Christof; Weber, Marcus

doi:10.1080/08927022.2020.1839660

Cited by 8 publications

(15 citation statements)

References 41 publications

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“…Sulfur atoms of these two cysteine residues are at a distance of 0.987 nm in the native rat MOR crystal structure according to Protein Data Bank (PDB) [25], code 6DDF [26]. Significantly, CYS 292 6.47 is also in proximity of HIS 297 6.52 , which is crucial for the interaction of the binding pocket of the receptor with opioid ligands [7,26]. Hence, it is of special interest to examine ligand binding and activation of the MOR without and with the additional CYS 292 6.47 -CYS 321 7.38 DSB in the receptor, as depicted in Fig.…”

Section: Results From MD Simulationsmentioning

confidence: 99%

“…The receptor-ligand complexes were inserted into the 1-palmitoyl-2-oleoyl-sn glycerol-3-phosphatidyl choline (POPC) bilayer models using the CHAMM-GUI Membrane Builder [39]. Similar to [7], MD simulations were performed with GRO-MACS 2019.6 [40], using the CHARMM36m force-field for the ligands [41], receptor [42] and lipids [43]. The CHARMM TIP3P water model [44] was used as an explicit solvent.…”

Section: A1 MD Simulationsmentioning

confidence: 99%

“…In [7], it has been shown by means of MD simulations that the ligand binding affinity varies for different ligands and pH values. Based on these results, we chose the following different values of k 1 for different ligand/pH combinations: k 1 = 1.25× 10 −2 s −1 for fentanyl and pH 6.5, k 1 = 2.5 × 10 −2 s −1 for fentanyl/pH 7.4, k 1 = 2.5 × 10 −2 s −1 for NFEPP/pH 6.5, and k 1 = 5 × 10 −4 s −1 for NFEPP/pH 7.4.…”

Section: Parameter Estimationmentioning

confidence: 99%

“…The ligand positions itself between these two residues. Thus, the interaction of the binding region of the MOR with the ligand was assessed by measuring its distance with regard to the crucial ASP 147 3.32 and HIS 297 6.52 residues of the binding region [7].…”

Section: Receptor-ligand Interactionmentioning

confidence: 99%

“…Up to now, the effects of NFEPP and fentanyl were mathematically analysed at the level of their binding rates at relevant amino acid residues accessible from the extracellular side of MOR [2,7]. To get a more complete picture, we herein present a model of the intracellular second messenger pathways relevant to pain and analgesia.…”

Section: Introductionmentioning

confidence: 99%

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Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

Ray

Thies

Sunkara

et al. 2021

Preprint

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We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. Uniquely, this design was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present a novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels associated with parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for NFEPP and fentanyl ligands at different pH values. We found markedly reduced calcium channel inhibition induced by NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl, and enhanced constitutive G-protein activation but lower probability of ligand binding with increasing radical concentrations. By means of molecular dynamics simulations, we also assessed qualitative changes of reaction rates due to additional disulfide bridges inside the GPCR binding pocket. The results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.

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Section: Results From MD Simulationsmentioning

confidence: 99%

Section: A1 MD Simulationsmentioning

confidence: 99%

Section: Parameter Estimationmentioning

confidence: 99%

Section: Receptor-ligand Interactionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

Ray

Thies

Sunkara

et al. 2021

Preprint

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Efficient estimation of transition rates as functions of pH

Donati,

Weber

2023

Proc Appl Math and Mech

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Extracting the kinetic properties of a system whose dynamics depend on the pH of the environment with which it exchanges energy and atoms requires sampling the grand canonical ensemble. As an alternative, we present a novel strategy that requires simulating only the most recurrent canonical ensembles that compose the grand canonical ensemble. The simulations are used to estimate the grand canonical distribution for a specific pH value by reweighting and to construct the transition rate matrix by discretizing the Fokker–Planck equation by square root approximation and robust Perron cluster cluster analysis. As an application, we have studied the tripeptide Ala‐Asp‐Ala.

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Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

Thies

Sunkara

Ray

et al. 2023

Sci Rep

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We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. The design process of NFEPP was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present an additional and novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels and their dependence on parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for the ligands NFEPP and fentanyl at different pH values and radical concentrations. We observe markedly reduced binding affinity and calcium channel inhibition for NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl. For increasing radical concentrations, we find enhanced constitutive G-protein activation but reduced ligand binding affinity. Assessing the different effects, the results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.

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How to calculate pH-dependent binding rates for receptor–ligand systems based on thermodynamic simulations with different binding motifs

Cited by 8 publications

References 41 publications

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

Efficient estimation of transition rates as functions of pH

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

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