| EPSRC Reference: |
EP/N020669/1 |
| Title: |
Accurate free energy calculations for biomolecular catalysis of electron transfer |
| Principal Investigator: |
Rosta, Dr E |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Chemistry |
| Organisation: |
Kings College London |
| Scheme: |
First Grant - Revised 2009 |
| Starts: |
01 July 2016 |
Ends: |
30 September 2017 |
Value (£): |
100,972
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| EPSRC Research Topic Classifications: |
| Catalysis & Applied Catalysis |
Protein chemistry |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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18 Feb 2016
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EPSRC Physical Sciences Chemistry - February 2016
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Announced
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Summary on Grant Application Form |
Long- and short-range electron transfer (ET) between proteins is vital for all living systems, and plays an essential role in photosynthesis and bio-assimilation. ET is a central process for the transfer and storage of solar energy in advanced materials as well. Our understanding of the corresponding biological electron transport can inspire new approaches for developing and advancing energy efficient technologies. However, robust, accurate, and predictive underlying theoretical and computational models are still needed to determine structure, energetics and kinetics of ET processes in materials and biological systems.
We introduced a new analysis method, DHAM, which can be used to calculate rates and free energies from biased or unbiased simulation trajectories (Rosta and Hummer, JCTC 2015). The DHAM method is a generalisation of the current state-of-the-art weighted histogram analysis method (WHAM), which is widely used to obtain accurate free energies from biased molecular simulations. We showed that WHAM-computed free energies can exhibit significant errors, e.g. when analysing simulations under weak bias - a problem overcome by using DHAM. Our method is designed to determine a global Markov chain based on a maximum likelihood approach to analyse multiple simulation trajectories. We construct the Markov transition matrix along a discretized reaction coordinate, and obtain the corresponding stationary distribution to determine the free energy profile. Importantly, our formalism provides kinetic information of biased simulations. By building on this approach, my main aim is to develop a new method to study electron transfer.
As a first application, we will study the catalytic reaction of FNR, a central enzyme in the final step of the photosynthetic electron transfer processes using the energy of light to store high-energy electrons in the form of chemical bonds in NADPH. Our novel computational methods will provide accurate free energies as well as kinetic information about the dynamics of the photosynthetic systems. Importantly, it will allow us to understand the underlying mechanism, including the elusive coupled proton transfer steps that occur together with the electron transfer reactions in FNR.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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