Quantitative models of biomolecular hydration thermodynamics

This thesis explores the use of cell theory calculations to characterise hydration thermodynamics in small molecules (cations, ions, hydrophobic molecules), proteins and protein-ligand complexes. Cell theory uses the average energies, forces and torques of a water molecule measured in its molecular frame of reference to parameterise a harmonic potential. From this harmonic potential analytical expressions for entropies and enthalpies are derived. In order to spatially resolve these thermodynamic quantities grid points are used to store the forces, torques, and energies of nearby waters which giving rise to the new grid cell theory (GCT) model. GCT allows one to monitor hydration thermodynamics at heterogeneous environments such as that of a protein surface. Through an understanding of the hydration thermodynamics around the protein and particularly around binding sites, robust protein-ligand scoring functions are created to estimate and rank protein-ligand binding affinities. GCT was then able to retrospectively rationalise the structure activity relationships made during lead optimisation of various ligand-protein systems including Hsp90, FXa, scytalone dehydratase among others. As well as this it was also used to analyse water behaviour in various protein environments with a dataset of 17 proteins. The grid cell theory implementation provides a theoretical framework which can aid the iterative design of ligands during the drug discovery and lead optimisation processes, and can provide insight into the effect of protein environment to hydration thermodynamics in general

Metabolism and hydrophilicity of the polarised 'Janus face' all-cis tetrafluorocyclohexyl ring, a candidate motif for drug discovery

This work was supported by the Initial Training Network, FLUOR21, funded by the FP7 Marie Curie Actions of the European Commission (FP7-PEOPLE-2013-ITN-607787). JM is supported by a University Research Fellowship from the Royal Society. The research leading to these results has received funding from the European Research Council under the EU 7th Framework Programme (FP7/2007-2013)/ERC No 336289.The metabolism and polarity of the all-cis tetra-fluorocyclohexane motif is explored in the context of its potential as a motif for inclusion in drug discovery programmes. Biotransformations of phenyl all-cis tetra-, tri- and di- fluoro cyclohexanes with the human metabolism model organism Cunninghamella elegans illustrates various hydroxylated products, but limited to benzylic hydroxylation for the phenyl all-cis tetrafluorocyclohexyl ring system. Evaluation of the lipophilicities (Log P) indicate a significant and progressive increase in polarity with increasing fluorination on the cyclohexane ring system. Molecular dynamics simulations indicate that water associates much more closely with the hydrogen face of these Janus face cyclohexyl rings than the fluorine face owing to enhanced hydrogen bonding interactions with the polarised hydrogens and water.Publisher PDFPeer reviewe

Assessment of Hydration Thermodynamics at Protein Interfaces with Grid Cell Theory

Molecular dynamics simulations have been analyzed with the Grid Cell Theory (GCT) method to spatially resolve the binding enthalpies and entropies of water molecules at the interface of 17 structurally diverse proteins. Correlations between computed energetics and structural descriptors have been sought to facilitate the development of simple models of protein hydration. Little correlation was found between GCT-computed binding enthalpies and continuum electrostatics calculations. A simple count of contacts with functional groups in charged amino acids correlates well with enhanced water stabilization, but the stability of water near hydrophobic and polar residues depends markedly on its coordination environment. The positions of X-ray-resolved water molecules correlate with computed high-density hydration sites, but many unresolved waters are significantly stabilized at the protein surfaces. A defining characteristic of ligand-binding pockets compared to nonbinding pockets was a greater solvent-accessible volume, but average water thermodynamic properties were not distinctive from other interfacial regions. Interfacial water molecules are frequently stabilized by enthalpy and destabilized entropy with respect to bulk, but counter-examples occasionally occur. Overall detailed inspection of the local coordinating environment appears necessary to gauge the thermodynamic stability of water in protein structures

Biomolecular simulations: From dynamics and mechanisms to computational assays of biological activity

Biomolecular simulation is increasingly central to understanding and designing biological molecules and their interactions. Detailed, physics‐based simulation methods are demonstrating rapidly growing impact in areas as diverse as biocatalysis, drug delivery, biomaterials, biotechnology, and drug design. Simulations offer the potential of uniquely detailed, atomic‐level insight into mechanisms, dynamics, and processes, as well as increasingly accurate predictions of molecular properties. Simulations can now be used as computational assays of biological activity, for example, in predictions of drug resistance. Methodological and algorithmic developments, combined with advances in computational hardware, are transforming the scope and range of calculations. Different types of methods are required for different types of problem. Accurate methods and extensive simulations promise quantitative comparison with experiments across biochemistry. Atomistic simulations can now access experimentally relevant timescales for large systems, leading to a fertile interplay of experiment and theory and offering unprecedented opportunities for validating and developing models. Coarse‐grained methods allow studies on larger length‐ and timescales, and theoretical developments are bringing electronic structure calculations into new regimes. Multiscale methods are another key focus for development, combining different levels of theory to increase accuracy, aiming to connect chemical and molecular changes to macroscopic observables. In this review, we outline biomolecular simulation methods and highlight examples of its application to investigate questions in biology. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Free Energy Method

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects

Current and emerging opportunities for molecular simulations in structure-based drug design

An overview of the current capabilities and limitations of molecular simulation of biomolecular complexes in the context of computer-aided drug design is provided. Steady improvements in computer hardware coupled with more refined representations of energetics are leading to a new appreciation of the driving forces of molecular recognition. Molecular simulations are poised to more frequently guide the interpretation of biophysical measurements of biomolecular complexes. Ligand design strategies emerge from detailed analyses of computed structural ensembles. The feasibility of routine applications to ligand optimization problems hinges upon successful extensive large scale validation studies and the development of protocols to intelligently automate computations