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Details of Grant 

EPSRC Reference: EP/K005472/1
Title: Reliable computational prediction of molecular assembly
Principal Investigator: Popelier, Professor P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Chemistry
Organisation: University of Manchester, The
Scheme: EPSRC Fellowship
Starts: 01 October 2013 Ends: 31 December 2019 Value (£): 1,249,809
EPSRC Research Topic Classifications:
Chemical Structure Gas & Solution Phase Reactions
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
26 Sep 2012 EPSRC Physical Sciences Chemistry - September 2012 Announced
21 Nov 2012 EPSRC Physical Sciences Fellowships Interview Panel 21st and 22nd Nov Announced
Summary on Grant Application Form

An important modern frontier of research in the physical sciences is the proper understanding and control over molecular assembly. The Grand Challenge of "Directed Assembly of Extended Structures with Targeted Properties" tackles this frontier from various angles. I focus on the angle of chemical computing, which has established itself as an independent source of information, complementary to experiment. There is a need, of ever increasing urgency, for accurate and hence more reliable prediction of interaction energies between molecules. The structure and dynamics of molecular assemblies sensitively depend on most subtle energy changes. This is why the scientific challenge of accurate energy prediction is still as acute as ever. If energy is correctly predicted then everything else follows: realistic structures, dynamics and properties. I propose a novel approach, drastically different to the current paradigm.

Matter at ambient conditions is governed by a master equation called the Schrödinger equation, which returns the interaction energy of a molecular assembly. Solving this master equation accurately for sizeable molecular aggregates is very expensive or even impossible with current computer power. Force fields, however, can provide this interaction energy, and do so many orders of magnitude faster. A force field is a formula that delivers the energy of a molecular system as a direct function of the system's atomic coordinates. This formula contains many parameters, specific to the system at hand. The challenge is to design a force field that is reliable. The best and only long term strategy is to map the force field as faithfully as possible onto the solution of the Schrödinger equation, both in terms of energy and the wave function. With exascale computers around the corner and GPU technology recently overtaking CPUs, it is pivotal and timely to invest into more realistic force fields.

Here I aim to offer biomolecular modelling a completely new route to designing a force field, with much more truthful electrostatics. We propose the completed construction of the first ever (high-rank) multipolar force field for flexible molecules, with both intra- and intermolecular polarisation. This is crucial for molecular assembly and recognition, as well as the realistic modelling of hydrogen bonding. Molecular systems, in the presence of the strong and inhomogeneous electric fields caused by ions, will also be modelled realistically for the first time.

The true predictive power of a force field depends on the reliability of the information transfer of small molecules (or molecular clusters) to large molecules. Only if this transferability is high, a force field will make reliable predictions. The main idea behind our force field, called QCTFF, is to construct "knowledgeable" atoms. These atoms are drawn from small molecules and made to interact in order to predict properties of large molecules. They are 3D fragments of electron density, with a finite volume. These atoms have sharp boundaries, which endows them with a "malleable" character. Their precise shape responds to the immediate environment of the molecule they are part of. A machine learning method then captures how these atoms change their multipole moments in response to the positions of their neighbours. We have successfully reached the proof-of-concept stage of this novel idea and now I intend to fully exploit it.

Although QCTFF is generic, its application is biased towards proteins, ions and water. Only a fellowship can deliver the ambitious but feasible goal of creating this transformative enabling technology towards life science applications. This technology will also serve as a robust platform from which to develop an innovative novel force field, to study reactions in solution and in enzymes, as well as crystal nucleation. The radical and innovating decisions taken at the outset of QCTFF's design are the best guarantee for its long lasting success.
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Organisation Website: http://www.man.ac.uk