11 research outputs found
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
Exploring the Anti-Hypoxaemia Effect of Hydromethylthionine : A Prospective Study of Phase 3 Clinical Trial Participants
Funding Information: This work was funded by TauRx Therapeutics Ltd., Singapore.Peer reviewedPublisher PD
Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method
Abstract Background The reliable and robust estimation of ligand binding affinity continues to be a challenge in drug design. Many current methods rely on molecular mechanics (MM) calculations which do not fully explain complex molecular interactions. Full quantum mechanical (QM) computation of the electronic state of protein-ligand complexes has recently become possible by the latest advances in the development of linear-scaling QM methods such as the ab initio fragment molecular orbital (FMO) method. This approximate molecular orbital method is sufficiently fast that it can be incorporated into the development cycle during structure-based drug design for the reliable estimation of ligand binding affinity. Additionally, the FMO method can be combined with approximations for entropy and solvation to make it applicable for binding affinity prediction for a broad range of target and chemotypes. Results We applied this method to examine the binding affinity for a series of published cyclin-dependent kinase 2 (CDK2) inhibitors. We calculated the binding affinity for 28 CDK2 inhibitors using the ab initio FMO method based on a number of X-ray crystal structures. The sum of the pair interaction energies (PIE) was calculated and used to explain the gas-phase enthalpic contribution to binding. The correlation of the ligand potencies to the protein-ligand interaction energies gained from FMO was examined and was seen to give a good correlation which outperformed three MM force field based scoring functions used to appoximate the free energy of binding. Although the FMO calculation allows for the enthalpic component of binding interactions to be understood at the quantum level, as it is an in vacuo single point calculation, the entropic component and solvation terms are neglected. For this reason a more accurate and predictive estimate for binding free energy was desired. Therefore, additional terms used to describe the protein-ligand interactions were then calculated to improve the correlation of the FMO derived values to experimental free energies of binding. These terms were used to account for the polar and non-polar solvation of the molecule estimated by the Poisson-Boltzmann equation and the solvent accessible surface area (SASA), respectively, as well as a correction term for ligand entropy. A quantitative structure-activity relationship (QSAR) model obtained by Partial Least Squares projection to latent structures (PLS) analysis of the ligand potencies and the calculated terms showed a strong correlation (r2 = 0.939, q2 = 0.896) for the 14 molecule test set which had a Pearson rank order correlation of 0.97. A training set of a further 14 molecules was well predicted (r2 = 0.842), and could be used to obtain meaningful estimations of the binding free energy. Conclusions Our results show that binding energies calculated with the FMO method correlate well with published data. Analysis of the terms used to derive the FMO energies adds greater understanding to the binding interactions than can be gained by MM methods. Combining this information with additional terms and creating a scaled model to describe the data results in more accurate predictions of ligand potencies than the absolute values obtained by FMO alone.</p