Project acronym FORCEMAP
Project Intramolecular force mapping of enzymes in action: the role of strain in motor mechanisms
Researcher (PI) András Málnási-Csizmadia
Host Institution (HI) EOTVOS LORAND TUDOMANYEGYETEM
Call Details Starting Grant (StG), LS1, ERC-2007-StG
Summary A fundamental but unexplored problem in biology is whether and how enzymes use mechanical strain during their functioning. It is now evident that the knowledge of atomic structures and chemical interactions is not sufficient to understand the intricate mechanisms underlying enzyme specificity and efficiency. Several lines of evidence suggest that mechanical effects play crucial roles in enzyme activity. Therefore we aim to create detailed force maps that reveal how the intramolecular distribution of mechanical strains changes during the enzyme cycle and how these rearrangements drive the enzyme processes. The applicability of current nanotechniques for the investigation of this problem is limited because they do not allow simultaneous measurement of mechanical and enzymatic parameters. Thus we seek to open new avenues of research by developing site-specific sensors and passive or photoinducible molecular springs to measure force-dependent chemical/structural changes with high spatiotemporal resolution in myosin. Since force perturbations occur very rapidly, we are able to combine experimental studies with quasi-realistic in silico simulations to describe the physical background of enzyme function. We expect that our research will yield fundamental insights into the role of intramolecular strains in enzymes and thus greatly aid the design and control of enzyme processes (specificity, activity, regulation). Our studies may also lead to new paradigms in the understanding of motor systems.
Summary
A fundamental but unexplored problem in biology is whether and how enzymes use mechanical strain during their functioning. It is now evident that the knowledge of atomic structures and chemical interactions is not sufficient to understand the intricate mechanisms underlying enzyme specificity and efficiency. Several lines of evidence suggest that mechanical effects play crucial roles in enzyme activity. Therefore we aim to create detailed force maps that reveal how the intramolecular distribution of mechanical strains changes during the enzyme cycle and how these rearrangements drive the enzyme processes. The applicability of current nanotechniques for the investigation of this problem is limited because they do not allow simultaneous measurement of mechanical and enzymatic parameters. Thus we seek to open new avenues of research by developing site-specific sensors and passive or photoinducible molecular springs to measure force-dependent chemical/structural changes with high spatiotemporal resolution in myosin. Since force perturbations occur very rapidly, we are able to combine experimental studies with quasi-realistic in silico simulations to describe the physical background of enzyme function. We expect that our research will yield fundamental insights into the role of intramolecular strains in enzymes and thus greatly aid the design and control of enzyme processes (specificity, activity, regulation). Our studies may also lead to new paradigms in the understanding of motor systems.
Max ERC Funding
750 000 €
Duration
Start date: 2008-09-01, End date: 2014-08-31
Project acronym NETWORK EVOLUTION
Project Integrated evolutionary analyses of genetic and drug interaction networks in yeast
Researcher (PI) Csaba Pal
Host Institution (HI) MAGYAR TUDOMANYOS AKADEMIA SZEGEDIBIOLOGIAI KUTATOKOZPONT
Call Details Starting Grant (StG), LS5, ERC-2007-StG
Summary The ability of cellular systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process both at the molecular and evolutionary level. There are both physiological and evolutionary reasonings why mutations often have limited impact on cellular growth. First, perturbations that hit one target often have no effect on the overall performance of a complex system (such as metabolic networks), as perturbations can be adjusted by reorganizing fluxes in metabolic networks, or changing regulation and expression of genes. Second, due to the fast evolvability of microbes, the effect of a perturbation can readily be alleviated by the evolution of compensatory mutations at other sites of the network. Understanding the extent of intrinsic and evolved robustness in cellular systems demands integrated analyses that combine functional genomics and computational systems biology with microbial evolutionary experiments. In collaboration with several leading research teams in the field, we plan to investigate the following issues. First, we will ask how accurately genome-scale metabolic network models can predict the impact of genetic deletions and other non-heritable perturbations. Second, to understand how the impact of genetic and drug perturbations can be mitigated during evolution, we will pursue a large-scale lab evolutionary protocol, and compare the results with predictions of computational models. Our work may suggest avenues of research on the general rules of acquired drug resistance in microbes.
Summary
The ability of cellular systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process both at the molecular and evolutionary level. There are both physiological and evolutionary reasonings why mutations often have limited impact on cellular growth. First, perturbations that hit one target often have no effect on the overall performance of a complex system (such as metabolic networks), as perturbations can be adjusted by reorganizing fluxes in metabolic networks, or changing regulation and expression of genes. Second, due to the fast evolvability of microbes, the effect of a perturbation can readily be alleviated by the evolution of compensatory mutations at other sites of the network. Understanding the extent of intrinsic and evolved robustness in cellular systems demands integrated analyses that combine functional genomics and computational systems biology with microbial evolutionary experiments. In collaboration with several leading research teams in the field, we plan to investigate the following issues. First, we will ask how accurately genome-scale metabolic network models can predict the impact of genetic deletions and other non-heritable perturbations. Second, to understand how the impact of genetic and drug perturbations can be mitigated during evolution, we will pursue a large-scale lab evolutionary protocol, and compare the results with predictions of computational models. Our work may suggest avenues of research on the general rules of acquired drug resistance in microbes.
Max ERC Funding
1 280 000 €
Duration
Start date: 2008-07-01, End date: 2013-06-30
