23 July, Chris Cave-Ayland: Hybrid quantum and classical free energy methods in computational drug optimisation

All the way from the chemistry department, in the spirit of inter-disciplinarily, Chris Cave-Ayland is coming to give a talk on something refreshingly different! 


Abstract:
A long-term aim of the pharmceutical industry is the development for computer
based approaches for the development of new drugs. There are a range of approaches
to this problem the most rigourous of which are known as free energy techniques.
These make use of the theory of thermodynamics and statistical mechanics to
allow detailed treatments of such systems and can be highly effective under appropriate 
conditions.  Application of these requires the ability to accurately calculate the energies 
of proteins in complex with potential drug molecules. Two contrasting ways of making 
energy calculations are through classical and quantum approaches. 
Classical approaches are highly paramaterised, however comparatively cheap, and 
effectively attempt to approximate the chemical bonds within a system with idealised
potentials. Quantum approaches on the other hand provide a theoretically exact representation
of the chemistry of the system, allowing them to capture effects that are lost in classical 
representations, although at a far greater computational expense.

My project focuses on so called hybrid classical and quantum methods, in
partnership with Professor Jon Essex and Chris Skylaris from the department of
chemistry. These approches attempt to gain the best of both worlds in terms of
accuracy and computational tractability of both models. This effectively
involves switching between the two different levels of description of the
system and the presents novel practical and theoretical difficulties.

The current focus of my work is the validation of a technique known as a free energy
perturbation (FEP) that can be used to transition between different descriptions of a
molecular system. Examining the implicit assumptions of an FEP and determing its
limitations are key to its successful application.