Description of Potential Energy Surfaces of Molecules using FFLUX Machine Learning Models

yesA new type of model, FFLUX, to describe the interaction between atoms has been developed as an alternative to traditional force fields. FFLUX models are constructed from applying the kriging machine learning method to the topological energy partitioning method, Interacting Quantum Atoms (IQA). The effect of varying parameters in the construction of the FFLUX models is analyzed, with the most dominant effects found to be the structure of the molecule and the number of conformations used to build the model. Using these models the optimization of a variety of small organic molecules is performed, with sub kJ mol-1 accuracy in the energy of the optimized molecules. The FFLUX models are also evaluated in terms of their performance in describing the potential energy surfaces (PESs) associated with specific degrees of freedoms within molecules. While the accurate description of PESs presents greater challenges than individual minima, FFLUX models are able to achieve errors of <2.5 kJ mol-1 across the full C-C-C-C dihedral PES of n-butane, indicating the future possibilities of the technique

Bonding Interactions in Congested Molecules: A Study of the Interatomic Forces and the Molecular Electrostatic Potential

Chemistry and Polymer Scienc

Analysis and Prediction of Protein-Protein Recognition

The aims of the work presented in this thesis were two-fold. Firstly, an existing protein-protein docking algorithm was re-implemented on a type of computer more available than that used originally, and its behaviour was analysed in detail. This analysis led to changes in the scoring function, a treatment of electrostatic complementarity, and side-chain truncation. The algorithm had problems with its representation of surface, but more generally it pointed to difficulties in dealing with conformational change on association. Thus such changes were the second problem studied. They were measured in thirty-nine pairs of structures of complexed and unbound proteins, averaged over interface and non-interface regions and for individual residues. The significance of the changes was evaluated by comparison with the differences seen in twelve pairs of independently solved structures of identical proteins. Just over half had some substantial overall movement. Movements involved main-chains as well as side-chains, and large changes in the interface were closely involved with complex formation, while those of exposed non-interface residues were caused by flexibility and disorder. Interface movements in enzymes were similar in extent to those of inhibitors. All eight of the complexes that had structures of both components in an unbound form available showed some significant interface movement. An algorithm that was tested on five of these complexes was seen to be successful even when some of the largest changes occurred. The situation may be different in systems other than the enzyme-inhibitors which dominate this study. Thus the general model of protein-protein recognition was found to be induced fit. However, because there is only limited conformational change in many systems, recognition can be treated as lock and key to a first approximation

The Design and Application of Enzyme Inter-residue Interaction Networks Towards Quantum Mechanical Modeling

The Design and Application of Enzyme Inter-residue Interaction Networks Towards Quantum Mechanical Modelin