Rapid estimation of hydration thermodynamics of macromolecular regions

Abstract

This work describes a novel protocol to efficiently calculate the local free energy of hydration of specific regions in macromolecules. The method employs Monte Carlo simulations in the grand canonical ensemble to generate water configurations in a selected spherical region in the macromolecule. Excess energy and entropy of hydration are calculated by analyzing the water configurational distributions following the recently published grid inhomogeneous solvation theory method [C. N. Nguyen, T. K. Young, and M. K. Gilson, J. Chem. Phys. 137, 044101 (2012)]. Our method involves the approximations of treating the macromolecule and distant solvent as rigid and performing calculations on multiple such conformations to account for conformational diversity. These approximations are tested against water configurations obtained from a molecular dynamics simulation. The method is validated by predicting the number and location of water molecules in 5 pockets in the protein Interleukin-1β for which experimental water occupancy data are available. Free energy values are validated against decoupling free energy perturbation calculations. The results indicate that the approximations used in the method enable efficient prediction of free energies of water displacement.

Quantifying the Entropy of Binding for Water Molecules in Protein Cavities by Computing Correlations

“…The fifth step is exnihilation of the water molecule in the cavity (Δ G exnihilation ) using FEP. The final step is to remove the harmonic restraint (Δ G unrestrain ) and this contribution is assumed to be zero, as in previous work, and is justified because the dynamics of the water molecule in the cavity are not affected by a force constant that is small in relation to the atomic fluctuations ( 9,18 ). For cavities containing two water molecules, the exnihilation is performed on both simultaneously and interactions between the exnihilated water molecules are also scaled to decouple them ( 18 ).…”

“…Δ G IFST can be calculated for small subvolumes of the system, allowing the contribution of specific regions to be estimated ( 13,45,46 ). In the context of protein systems, water molecules tend to cluster at distinct locations termed hydration sites, and it is natural to compute the contribution of individual water molecules to the hydration free energy ( 14,18,47,48 ). For the IFST calculations, 100.0 ns of production simulation in an NVT ensemble were performed at 300 K for each system.…”

“…It has proven a very useful tool in modeling networks of water molecules in biological systems. IFST has also been used to study water molecules in cavities of IL-1β ( 18 ), and in this article we extend such a study to five different proteins and nineteen protein cavities. In addition, we combine the k-nearest neighbors (KNN) ( 19,20 ) algorithm with information theory ( 21–24 ) to study doubly occupied cavities and explicitly calculate the contributions of changes in water-water correlations and the associated entropy changes.…”

Spatial Analysis and Quantification of the Thermodynamic Driving Forces in Protein–Ligand Binding: Binding Site Variability

“…Δ ω i is the angular distance of a water molecule i to its nearest neighbor geometry in the same voxel. Unlike our previous study[16], we used of the norm of the distance between quaternions to evaluate Δ ω . This metric was recently shown to posses superior convergence properties than the Eucledian distance between the Euler angles.…”

Hydration thermodynamics of cytosolic phospholipase A2 GIVA predict its membrane-associated parts and its highly hydrated binding site

“…In this work, we assigned hydrophobicity values on the amino acids based on the calculation of the thermodynamic properties of the surrounding water molecules. We implemented this using the GIST (Nguyen, Cruz, Gilson, & Kurtzman, 2014;Nguyen, Gilson, & Young, 2011;Nguyen, Kurtzman, & Gilson, 2012;Raman & MacKerell, 2013) tool in AmberTools, an application of the inhomogeneous fluid solvation theory (IFST) on biomolecules (Green, 1952;Huggins, 2012;Lazaridis, 1998;Li & Lazaridis, 2006). GIST divides a defined solvent area in a 3D grid, which consists of small grid boxes.…”