Biomolecular recognition refers to the interaction between a macromolecule (usually a protein or a nucleic acid) and a target molecule. Most often obtaining 3D experimental data is not trivial at atomistic scale. Computational methods offer the possibility of precisely describing all types of ligand–macromolecule interactions and are therefore a promising avenue to obtain that information, to test or discard a large variety of hypotheses regarding molecular recognition, folding of proteins/peptides and/or to select, among the vast chemical space of potential drug scaffolds, those which are most likely to meet success before committing expensive experimental resources to their synthesis and evaluation.
This project will use computational methods to unravel the details of the three-dimensional structure and interactions of proteins and their targets for medical and biotechnological applications.
- work with the atomistic 3D models of biological molecules of interest in out group
- concentrate on structure-based approaches and apply a range of computational modelling and drug design techniques such as molecular docking, protein folding, high performance computing and visualisation tools
- work in a highly interdisciplinary environment and have the opportunity to collaborate with experimental researchers for experimentally validating the established models and generated hypothesis.
- have access to high performance computing systems (supercomputers). You will be using open source and commercial modelling software.
Intrinsically disordered proteins (IDPs) lack stable tertiary and/or secondary structure yet fulfills key biological functions. These proteins are often associated with human diseases like cancer, cardiovascular, and Alzheimers.
Often IDPs contain multiple binding motifs and are frequently the sites for post-translational modification, an important mediator of the control of signalling pathways. One of the grand challenges of modern biophysical science is to understand how IDPs and the post-translational modifications can fold into a unique, biologically functioning protein structure from the myriad conformations of the unfolded state.
To combine the inherent power of high performance computing and advanced physics based algorithms (molecular dynamics simulations) to capture the conformational changes in IDPs that typically occur on the millisecond time scale.
Skills and experience
Ideally you will be a highly motivated individual with a strong interest in applying computational tools to address complex chemical and biological questions. A solid background in chemistry and biophysics, such as an undergraduate or dual degrees in pharmacy, chemistry, biology, computing or a related discipline, is required. Previous experience with computational chemistry, cheminformatics, or computational drug design tools and software packages is a plus.
Contact the supervisor for more information.