Next Generation Drug Design by Advanced Computation

It would be fantastic if a new drug could be designed successfully by computation only. The problem is that predicting binding affinity is still seen as a holy grail. One of the reasons is that protein-ligand interaction energies are still computed by methods of limited accuracy. There is an urgent need for more reliable modelling tools.

We have a method that has the potential to move beyond the current status-quo. The work proposed here will impact on the prediction of small-molecule binding modes to macromolecules, which is a problem of paramount importance in rational drug design. This is known as the docking problem. A provocative perspective1 asks why docking remains so primitive that it is unable to even rank-order a hit list, and literally stated that docking seems to have reached a plateau, waiting for an important breakthrough. We strive to help in this breakthrough. We aim at making (molecular mechanics) force fields more accurate and realistic.

You will contribute to an exciting project, which develops a reliable computational tool, now called FFLUX2. FFLUX is a sophisticated force field (or energy-force predictor), based on Quantum Chemical Topology3,4, which treats atoms as “bubbles” (see Figures) that are quantum mechanically well-defined. A machine learning method captures5 the way the energy of a given atom changes in response to a change in this atom’s environment. This change can be geometrical or caused by a variation in substituents. Trends can be systematically established based on rigorous intra- and interatomic energies. An in-house package program ANANKE is able to find out, from thousands of energies, which part of the system behaves as the total system upon an induced perturbation (geometry or substituent). This new method is how chemical insight is rigorously drawn from highly quantitative data. You will work on case studies found in the Protein Data Bank (PDB).

Computational chemistry is the research area with the highest impact on the whole of chemistry as can be concluded from the Web of Knowledge. This project follows novel ideas to release the power of computational chemistry as a valuable source of information, independent of experiment.

Qualifications
Applicants should have or expect a good II(i) honours degree (or an equivalent degree) in Masters Chemistry or Physics. The project is purely computational without tapping into mathematical skills or programming. If you have those skills then that is a bonus but it is not necessary. If you wish to develop these skills then this can be taken care of. However, the project requires the efficient and correct running of existing computer programs and a systematic analysis of the data generated.

Contact for further Information
For general admission information, please email: [Email Address Removed].

Informal inquiries about the project should be sent to Prof. Paul Popelier by email ([Email Address Removed]). Please note that to apply for this studentship you must submit the relevant information via the University’s online application form.