Predicting the location and binding affinity of small molecules in protein binding sites

Abstract

In this thesis, various methods for locating and scoring the binding affinity of water molecules and molecular fragments in protein binding sites are described. The primary aim of this work is to understand how different methodologies compare to one another and how, by carefully choosing the correct method, they can be used to extract information on how small molecules interact with proteins. Three different methods are used to predict the location and affinity of water molecules; Just Add Water Molecules (JAWS), Grand Canonical Monte Carlo (GCMC) and double-decoupling. By applying the methods to the N9-Neuraminidase system, it can be shown that all of the methods predict the same binding free energy of the water molecules to within error. The JAWS method was shown to be advantageous for the rapid prediction of the binding free energy of water molecules, whilst GCMC was preferred for the prediction of hydration sites. The combination of the methods were used on a variety of novel test cases, including hydrophobic cavities and protein kinases. These test cases highlight how the methods can be used to accurately predict hydration patterns as a function of the binding free energy in GCMC simulations, and how these patterns can be used to dictate ligand design in a drug discovery context. The approaches described are likely to be of interest to the pharmaceutical industry. A JAWS based fragment based drug discovery methodology is also described, which takes into account key features commonly neglected by existing computational approaches such as fragment-solvent competition and fragment desolvation. This method is used upon the Kinesin Spindle Protein and factor Xa, and demonstrates that the method is able to accurately locate the position of molecular fragments and water molecules compared to crystallographic ligands.

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ORCID for Jonathan W. Essex: orcid.org/0000-0003-2639-2746

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