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A structural systems biology approach for quantifying the systemic consequences of missense mutations in proteins.

Cheng TM, Goehring L, Jeffery L, Lu YE, Hayles J, Novák B, Bates PA - PLoS Comput. Biol. (2012)

Bottom Line: We present two case studies: (1) interpreting systemic perturbation for mutations within the cell cycle control mechanisms (G2 to mitosis transition) for yeast; (2) phenotypic classification of neuron-related human diseases associated with mutations within the mitogen-activated protein kinase (MAPK) pathway.We show that the application of simplified mathematical models is feasible for understanding the effects of small sequence changes on cellular behavior.Furthermore, we show that the systemic impact of missense mutations can be effectively quantified as a combination of protein stability change and pathway perturbation.

View Article: PubMed Central - PubMed

Affiliation: Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.

ABSTRACT
Gauging the systemic effects of non-synonymous single nucleotide polymorphisms (nsSNPs) is an important topic in the pursuit of personalized medicine. However, it is a non-trivial task to understand how a change at the protein structure level eventually affects a cell's behavior. This is because complex information at both the protein and pathway level has to be integrated. Given that the idea of integrating both protein and pathway dynamics to estimate the systemic impact of missense mutations in proteins remains predominantly unexplored, we investigate the practicality of such an approach by formulating mathematical models and comparing them with experimental data to study missense mutations. We present two case studies: (1) interpreting systemic perturbation for mutations within the cell cycle control mechanisms (G2 to mitosis transition) for yeast; (2) phenotypic classification of neuron-related human diseases associated with mutations within the mitogen-activated protein kinase (MAPK) pathway. We show that the application of simplified mathematical models is feasible for understanding the effects of small sequence changes on cellular behavior. Furthermore, we show that the systemic impact of missense mutations can be effectively quantified as a combination of protein stability change and pathway perturbation.

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The procedure of calculating SIF scores.(A) Identifying the target system for study. In this case we show the scheme of the G2-M model that regulates the G2 to mitosis transition in the cell cycle. (B) Mapping mutations onto their 3D structures (Cdk1 and CycB in this example) and associating them with the ODE parameters. Mutations located at or close to the active site (colored in blue) are considered to perturb the ODE rate constants that describe interactions between MPF and their regulating kinases wee1 and cdc25 (shown with blue circles). Mutations that are not in the functional sites (colored in red) are considered to perturb the ODE rate constants describing the rate of protein degradation (shown with red circles). Also, for each mutation we evaluate its ΔΔG that is considered as the perturbation of ODE parameters. (C) Calculating the CSpi that reflects the sensitivity of perturbing ODE parameters in terms of regulating the downstream reporter protein (MPF in the G2-M model). Here we show the perturbation on the degradation rate of MPF as an example: The green arrows mark the effect of perturbation on CycB concentration when cells enter mitosis, which is a result of MPF curve shifts (the red line represents wild type whereas orange and purple lines are mutant types). (D) Inferring the systemic consequences of mutations based on ΔΔG and CSpi. Mutations that have smaller or larger SIF scores are likely to have smaller or larger sizes at septation, respectively. The scale bars shown in the microscopic photos represent the average length of wild-type yeasts.
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pcbi-1002738-g001: The procedure of calculating SIF scores.(A) Identifying the target system for study. In this case we show the scheme of the G2-M model that regulates the G2 to mitosis transition in the cell cycle. (B) Mapping mutations onto their 3D structures (Cdk1 and CycB in this example) and associating them with the ODE parameters. Mutations located at or close to the active site (colored in blue) are considered to perturb the ODE rate constants that describe interactions between MPF and their regulating kinases wee1 and cdc25 (shown with blue circles). Mutations that are not in the functional sites (colored in red) are considered to perturb the ODE rate constants describing the rate of protein degradation (shown with red circles). Also, for each mutation we evaluate its ΔΔG that is considered as the perturbation of ODE parameters. (C) Calculating the CSpi that reflects the sensitivity of perturbing ODE parameters in terms of regulating the downstream reporter protein (MPF in the G2-M model). Here we show the perturbation on the degradation rate of MPF as an example: The green arrows mark the effect of perturbation on CycB concentration when cells enter mitosis, which is a result of MPF curve shifts (the red line represents wild type whereas orange and purple lines are mutant types). (D) Inferring the systemic consequences of mutations based on ΔΔG and CSpi. Mutations that have smaller or larger SIF scores are likely to have smaller or larger sizes at septation, respectively. The scale bars shown in the microscopic photos represent the average length of wild-type yeasts.

Mentions: The G2-M transition controls when a cell enters mitosis and determines the size of a cell at the point of division into two daughter cells. In fission yeast, Schizosaccharomyces pombe, this involves Cdk1, CycB, Wee1 and Cdc25. In the G2 phase, Cdk1 and CycB form a complex known as the mitosis promoting factor (MPF), which brings about the G2-M transition [11]. The activity of MPF is regulated by the protein kinase Wee1 [12] and the protein phosphatase Cdc25 [13], [14]: Wee1 inhibits the activity of MPF by phosphorylating Cdk1, and Cdk1 also exerts negative feedback on Wee1 by phosphorylating it. In addition, Cdc25 activates MPF by dephosphorylating Cdk1 and vice versa [15]. The Wee1-MPF-Cdc25 control system increases the ratio of active MPF over its inactive state and eventually promotes a cell into mitosis (Figure 1A).


A structural systems biology approach for quantifying the systemic consequences of missense mutations in proteins.

Cheng TM, Goehring L, Jeffery L, Lu YE, Hayles J, Novák B, Bates PA - PLoS Comput. Biol. (2012)

The procedure of calculating SIF scores.(A) Identifying the target system for study. In this case we show the scheme of the G2-M model that regulates the G2 to mitosis transition in the cell cycle. (B) Mapping mutations onto their 3D structures (Cdk1 and CycB in this example) and associating them with the ODE parameters. Mutations located at or close to the active site (colored in blue) are considered to perturb the ODE rate constants that describe interactions between MPF and their regulating kinases wee1 and cdc25 (shown with blue circles). Mutations that are not in the functional sites (colored in red) are considered to perturb the ODE rate constants describing the rate of protein degradation (shown with red circles). Also, for each mutation we evaluate its ΔΔG that is considered as the perturbation of ODE parameters. (C) Calculating the CSpi that reflects the sensitivity of perturbing ODE parameters in terms of regulating the downstream reporter protein (MPF in the G2-M model). Here we show the perturbation on the degradation rate of MPF as an example: The green arrows mark the effect of perturbation on CycB concentration when cells enter mitosis, which is a result of MPF curve shifts (the red line represents wild type whereas orange and purple lines are mutant types). (D) Inferring the systemic consequences of mutations based on ΔΔG and CSpi. Mutations that have smaller or larger SIF scores are likely to have smaller or larger sizes at septation, respectively. The scale bars shown in the microscopic photos represent the average length of wild-type yeasts.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475653&req=5

pcbi-1002738-g001: The procedure of calculating SIF scores.(A) Identifying the target system for study. In this case we show the scheme of the G2-M model that regulates the G2 to mitosis transition in the cell cycle. (B) Mapping mutations onto their 3D structures (Cdk1 and CycB in this example) and associating them with the ODE parameters. Mutations located at or close to the active site (colored in blue) are considered to perturb the ODE rate constants that describe interactions between MPF and their regulating kinases wee1 and cdc25 (shown with blue circles). Mutations that are not in the functional sites (colored in red) are considered to perturb the ODE rate constants describing the rate of protein degradation (shown with red circles). Also, for each mutation we evaluate its ΔΔG that is considered as the perturbation of ODE parameters. (C) Calculating the CSpi that reflects the sensitivity of perturbing ODE parameters in terms of regulating the downstream reporter protein (MPF in the G2-M model). Here we show the perturbation on the degradation rate of MPF as an example: The green arrows mark the effect of perturbation on CycB concentration when cells enter mitosis, which is a result of MPF curve shifts (the red line represents wild type whereas orange and purple lines are mutant types). (D) Inferring the systemic consequences of mutations based on ΔΔG and CSpi. Mutations that have smaller or larger SIF scores are likely to have smaller or larger sizes at septation, respectively. The scale bars shown in the microscopic photos represent the average length of wild-type yeasts.
Mentions: The G2-M transition controls when a cell enters mitosis and determines the size of a cell at the point of division into two daughter cells. In fission yeast, Schizosaccharomyces pombe, this involves Cdk1, CycB, Wee1 and Cdc25. In the G2 phase, Cdk1 and CycB form a complex known as the mitosis promoting factor (MPF), which brings about the G2-M transition [11]. The activity of MPF is regulated by the protein kinase Wee1 [12] and the protein phosphatase Cdc25 [13], [14]: Wee1 inhibits the activity of MPF by phosphorylating Cdk1, and Cdk1 also exerts negative feedback on Wee1 by phosphorylating it. In addition, Cdc25 activates MPF by dephosphorylating Cdk1 and vice versa [15]. The Wee1-MPF-Cdc25 control system increases the ratio of active MPF over its inactive state and eventually promotes a cell into mitosis (Figure 1A).

Bottom Line: We present two case studies: (1) interpreting systemic perturbation for mutations within the cell cycle control mechanisms (G2 to mitosis transition) for yeast; (2) phenotypic classification of neuron-related human diseases associated with mutations within the mitogen-activated protein kinase (MAPK) pathway.We show that the application of simplified mathematical models is feasible for understanding the effects of small sequence changes on cellular behavior.Furthermore, we show that the systemic impact of missense mutations can be effectively quantified as a combination of protein stability change and pathway perturbation.

View Article: PubMed Central - PubMed

Affiliation: Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.

ABSTRACT
Gauging the systemic effects of non-synonymous single nucleotide polymorphisms (nsSNPs) is an important topic in the pursuit of personalized medicine. However, it is a non-trivial task to understand how a change at the protein structure level eventually affects a cell's behavior. This is because complex information at both the protein and pathway level has to be integrated. Given that the idea of integrating both protein and pathway dynamics to estimate the systemic impact of missense mutations in proteins remains predominantly unexplored, we investigate the practicality of such an approach by formulating mathematical models and comparing them with experimental data to study missense mutations. We present two case studies: (1) interpreting systemic perturbation for mutations within the cell cycle control mechanisms (G2 to mitosis transition) for yeast; (2) phenotypic classification of neuron-related human diseases associated with mutations within the mitogen-activated protein kinase (MAPK) pathway. We show that the application of simplified mathematical models is feasible for understanding the effects of small sequence changes on cellular behavior. Furthermore, we show that the systemic impact of missense mutations can be effectively quantified as a combination of protein stability change and pathway perturbation.

Show MeSH