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Integrative and quantitative analysis of disease mutations in the RAS-RAF-MEK-ERK pathway and implications for personalized medicine
Published on Jul 18, 20161215 Views
The Ras/MAPK syndromes ('RASopathies') are a class of developmental disorders caused by germline mutations in 15 genes encoding proteins of the Ras/mitogen-activated protein kinase (MAPK) pathway. It
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Chapter list
Integrative and quantitative analysis of disease mutations in protein interaction networks and implications for personalized medicine00:00
Exploring the molecular and quantitative mechanisms02:54
Outline03:53
Quantitative information in protein-protein interaction (PPI) networks05:05
The effect of affinities, kinetic constants and network topology in PPI networks06:00
Epidermal growth factor (EGF) activates the RAS-RAF-MEKERK pathway07:02
Different network ‘wiring’ /feedbacks causes the different behaviour07:17
A simple computer model of ERK activation in HEK293 and RK13 cells08:48
Model predictions08:52
Interaction competition09:48
The effect of protein abundance perturbations and interaction competition10:08
How could interaction competition and protein concentration affect downstream signaling? - 111:21
How could interaction competition and protein concentration affect downstream signaling? - 212:02
A bioinformatics tool to distinguish mutually exclusive from compatible interactions in large-scale PPI12:37
Experimental methods to quantify protein abundances, affinities, and kinetic constants13:06
Why proteomics in times of deep RNA sequencing?13:36
High complexity of the proteome14:13
High dynamic range of the proteome14:44
Protein identification by mass spectrometry15:14
Human deep proteome mapping15:34
Human deep proteome mapping: where are we now? Complete?15:49
Antibody-based proteomics: only semi-quantitative abundances16:57
Quantitative Western blotting17:12
Combining different quantitative approaches to quantify 198 proteins in the ErbB signaling pathway19:02
Measuring protein interactions in vivo and in vitro20:27
Measuring protein affinities in vitro requires the expression and purification of proteins20:47
Two main methods to measure affinities and kinetic constants20:59
The effect of abundance variation at XOR network motifs21:46
Competition at the RasXOR node24:45
Experimental testing of competition at the Ras node25:13
Qualitative and quantitative effects of disease mutations25:50
General concepts of interaction (‘edge’) rewiring25:52
Examples how missense mutations can affect the network: a 3D structural perspective - 127:31
Examples how missense mutations can affect the network: a 3D structural perspective - 228:08
Examples how missense mutations can affect the network: a 3D structural perspective - 328:29
Examples how missense mutations can affect the network: a 3D structural perspective - 428:42
Examples how missense mutations can affect the network: a 3D structural perspective - 528:51
Examples how missense mutations can affect the network: a 3D structural perspective - 629:04
Example 1: RASopathyand cancer disease mutations29:18
What are the differences in mutations of the same protein causing different disease30:46
Location of mutations in different domains does not explain the difference between RASopathyand cancer mutations31:49
FoldX-based energy calculations of proteins32:42
Analysis of 956 missense mutations in RASopathiesand cancer - 132:53
Analysis of 956 missense mutations in RASopathiesand cancer - 233:02
Multiple effects of a mutation even for the same protein/ protein class33:13
Cancer mutations tend to have higher destabilization values (on average)33:47
Quantitative effects on protein stability34:20
Compensatory effects of mutations on different interaction partners35:11
Conclusions example 1: RASopathyvs cancer35:40
Example 2: Rhodopsin disease mutations35:53
Rhodopsin: involved in light perception in rod outer segment35:55
Analysis of 103 mutations in rhodopsin linked to RP36:26
Several consideration for studying the effect of missense mutations in rhodopsin36:49
For analyzing Region IV mutants37:47
Several consideration for studying the effect of missense mutations in rhodopsin - 137:51
Several consideration for studying the effect of missense mutations in rhodopsin - 237:54
Several consideration for studying the effect of missense mutations in rhodopsin - 338:34
Five structures of bovine rhodopsin were selected38:44
FoldXenergy results and involvement in other function - 138:47
FoldXenergy results and involvement in other function - 238:56
FoldXcalculations and comparing with phenotypic data39:36
Correlation of daytime vision loss and night blindness with FoldXenergy calculations39:38
Conclusions example 2: Rhodopsin mutations40:35
Example 3: BRAF mutations in cancer. Why V600E?40:37
The most common BRAF mutation is V600E and induces constitutive kinase activation40:38
Catalytic activity of kinases is usually tightly controlled41:24
Kinases are activated through mutations in the activation loop (activation segment)41:49
BRAF kinase activation though oncogenic mutations (e.g. V600E)42:09
Focus on the position Val600 in the kinase BRAF42:37
The V600E mutation causes a high destabilization of the inactive state43:21
Distinguishing driver from passenger mutations44:01
V600G behaves more like a RASopathymutation44:03
Different energy thresholds for germline and somatic mutations?44:28
Why different cancer frequencies for V600E, V600D and V600K? - 145:03
Why different cancer frequencies for V600E, V600D and V600K? - 245:36
Why different cancer frequencies for V600E, V600D and V600K? - 345:50
Experimentally validate the effect of BRAF mutations - 147:05
Experimentally validate the effect of BRAF mutations - 247:15
Why are no mutations at other positions in the hydrophobic pocket48:28
Conclusions/ Wrap up50:24
Acknowledgements51:26