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Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases.

Mariani S, Dell'Orco D, Felline A, Raimondi F, Fanelli F - PLoS Comput. Biol. (2013)

Bottom Line: Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype.Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site.Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.

ABSTRACT
A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEγ binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

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Flash responses from wild type, GαGTPG38D+/−, and GαGTPG38D−/− rods.Experimental (A, B, C) versus simulated (D, E, F) responses to flashes of increasing intensities from wild type GαGTPWT+/+ (A, D), heterozygous GαGTPG38D+/− (B, E) and homozygous GαGTPG38D−/− (C, F) rods are shown. Experimental data, i.e. published in Moussaif et al. [8] and provided by Marie E. Burns, refer to mice rods exposed to flashes ranging from 5 to 97000 photons µm−2 (A and B) or from 650 to 94000 photons µm−2 (C). Simulated responses derive from the model of an amphibian rod stimulated with the same light intensities as in vitro recordings. The pathological GαGTPG38D+/− and GαGTPG38D−/− models were generated by changes in the kinetic parameters kP1, kP2 and kRGS1 as described in the text. The dissimilar species justify the time scale difference between in vitro and in silico experiments. The responses were normalized with respect to the maximum photocurrent. G. Normalized simulated light response amplitude is plotted as a function of flash strength. For comparison to in vitro data, see Figure 5B in Moussaif et al. [8]. Flash intensities are the same as in D, E and F.
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pcbi-1003207-g003: Flash responses from wild type, GαGTPG38D+/−, and GαGTPG38D−/− rods.Experimental (A, B, C) versus simulated (D, E, F) responses to flashes of increasing intensities from wild type GαGTPWT+/+ (A, D), heterozygous GαGTPG38D+/− (B, E) and homozygous GαGTPG38D−/− (C, F) rods are shown. Experimental data, i.e. published in Moussaif et al. [8] and provided by Marie E. Burns, refer to mice rods exposed to flashes ranging from 5 to 97000 photons µm−2 (A and B) or from 650 to 94000 photons µm−2 (C). Simulated responses derive from the model of an amphibian rod stimulated with the same light intensities as in vitro recordings. The pathological GαGTPG38D+/− and GαGTPG38D−/− models were generated by changes in the kinetic parameters kP1, kP2 and kRGS1 as described in the text. The dissimilar species justify the time scale difference between in vitro and in silico experiments. The responses were normalized with respect to the maximum photocurrent. G. Normalized simulated light response amplitude is plotted as a function of flash strength. For comparison to in vitro data, see Figure 5B in Moussaif et al. [8]. Flash intensities are the same as in D, E and F.

Mentions: We presented a dynamical model of the phototransduction signaling network made up of ordinary differential equations, which describe the reactions and their kinetic parameters [14]. The working model used in this study includes also the dynamic scaffolding reactions between dark rhodopsin and Gt [15]. Herein, such model was further extended to describe the heterozygous (GαGTPG38D+/−) and homozygous (GαGTPG38D−/−) mutated conditions of GαGTPG38D. This was accomplished by introducing the mutated G protein as an explicit new molecule and adding all the relative reactions in the phototransduction cascade, which concerned the GαGTPWT+/+ status (Table 1, see Methods). The output of mathematical simulations (i.e. change in photocurrent with respect to dark value, ΔJ) was analyzed and compared with the photoresponses of rods from wild type and transgenic mice (Figure 3A, 3B, and 3C). It is worth noting that, due to the significant difference in the species between in vitro (i.e. mammals, Figure 3A, 3B, and 3C) and in silico (i.e. amphibian rods [14], Figure 3D, 3E, and 3F) experiments, the time scales of the photoresponses is different, thus allowing for semi-quantitative comparisons.


Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases.

Mariani S, Dell'Orco D, Felline A, Raimondi F, Fanelli F - PLoS Comput. Biol. (2013)

Flash responses from wild type, GαGTPG38D+/−, and GαGTPG38D−/− rods.Experimental (A, B, C) versus simulated (D, E, F) responses to flashes of increasing intensities from wild type GαGTPWT+/+ (A, D), heterozygous GαGTPG38D+/− (B, E) and homozygous GαGTPG38D−/− (C, F) rods are shown. Experimental data, i.e. published in Moussaif et al. [8] and provided by Marie E. Burns, refer to mice rods exposed to flashes ranging from 5 to 97000 photons µm−2 (A and B) or from 650 to 94000 photons µm−2 (C). Simulated responses derive from the model of an amphibian rod stimulated with the same light intensities as in vitro recordings. The pathological GαGTPG38D+/− and GαGTPG38D−/− models were generated by changes in the kinetic parameters kP1, kP2 and kRGS1 as described in the text. The dissimilar species justify the time scale difference between in vitro and in silico experiments. The responses were normalized with respect to the maximum photocurrent. G. Normalized simulated light response amplitude is plotted as a function of flash strength. For comparison to in vitro data, see Figure 5B in Moussaif et al. [8]. Flash intensities are the same as in D, E and F.
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pcbi-1003207-g003: Flash responses from wild type, GαGTPG38D+/−, and GαGTPG38D−/− rods.Experimental (A, B, C) versus simulated (D, E, F) responses to flashes of increasing intensities from wild type GαGTPWT+/+ (A, D), heterozygous GαGTPG38D+/− (B, E) and homozygous GαGTPG38D−/− (C, F) rods are shown. Experimental data, i.e. published in Moussaif et al. [8] and provided by Marie E. Burns, refer to mice rods exposed to flashes ranging from 5 to 97000 photons µm−2 (A and B) or from 650 to 94000 photons µm−2 (C). Simulated responses derive from the model of an amphibian rod stimulated with the same light intensities as in vitro recordings. The pathological GαGTPG38D+/− and GαGTPG38D−/− models were generated by changes in the kinetic parameters kP1, kP2 and kRGS1 as described in the text. The dissimilar species justify the time scale difference between in vitro and in silico experiments. The responses were normalized with respect to the maximum photocurrent. G. Normalized simulated light response amplitude is plotted as a function of flash strength. For comparison to in vitro data, see Figure 5B in Moussaif et al. [8]. Flash intensities are the same as in D, E and F.
Mentions: We presented a dynamical model of the phototransduction signaling network made up of ordinary differential equations, which describe the reactions and their kinetic parameters [14]. The working model used in this study includes also the dynamic scaffolding reactions between dark rhodopsin and Gt [15]. Herein, such model was further extended to describe the heterozygous (GαGTPG38D+/−) and homozygous (GαGTPG38D−/−) mutated conditions of GαGTPG38D. This was accomplished by introducing the mutated G protein as an explicit new molecule and adding all the relative reactions in the phototransduction cascade, which concerned the GαGTPWT+/+ status (Table 1, see Methods). The output of mathematical simulations (i.e. change in photocurrent with respect to dark value, ΔJ) was analyzed and compared with the photoresponses of rods from wild type and transgenic mice (Figure 3A, 3B, and 3C). It is worth noting that, due to the significant difference in the species between in vitro (i.e. mammals, Figure 3A, 3B, and 3C) and in silico (i.e. amphibian rods [14], Figure 3D, 3E, and 3F) experiments, the time scales of the photoresponses is different, thus allowing for semi-quantitative comparisons.

Bottom Line: Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype.Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site.Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.

ABSTRACT
A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEγ binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

Show MeSH
Related in: MedlinePlus