Solvation Free Energy as a Measure of Hydrophobicity: Application to Serine Protease Binding Interfaces

Abstract

Solvation and hydrophobicity play a key role in a variety of biological mechanisms. In substrate binding, but also in structure-based drug design, the thermodynamic properties of water molecules surrounding a given protein are of high interest. One of the main algorithms devised in recent years to quantify thermodynamic properties of water is the grid inhomogeneous solvation theory (GIST), which calculates these features on a grid surrounding the protein. Despite the inherent advantages of GIST, the computational demand is a major drawback, as calculations for larger systems can take days or even weeks. Here, we present a GPU accelerated version of the GIST algorithm, which facilitates efficient estimates of solvation free energy even of large biomolecular interfaces. Furthermore, we show that GIST can be used as a reliable tool to evaluate protein surface hydrophobicity. We apply the approach on a set of nine different proteases calculating localized solvation free energies on the surface of the binding interfaces as a measure of their hydrophobicity. We find a compelling agreement with the hydrophobicity of their substrates, i.e., peptides, binding into the binding cleft, and thus our approach provides a reliable description of hydrophobicity characteristics of these biological interfaces.

An Online Repository of Solvation Thermodynamic and Structural Maps of SARS-CoV-2 Targets

“…GIST maps were created using the GPU port 16 of AmberTools cpptraj-GIST 17 . Analyses were performed on the complete 50 ns production trajectory for each system (25000 configurational snapshots).…”

Thermodynamic Decomposition of Solvation Free Energies with Particle Mesh Ewald and Long-Range Lennard-Jones Interactions in Grid Inhomogeneous Solvation Theory

“…Although serval studies have applied IST and GIST for solvation free energy calculations, long-range interactions have not been included in these works, and high order entropies have been either approximated or neglected completely. 15,16,40 Here, in order to investigate how the inclusion of long-range interactions affect GIST's accuracy in calculating solvation energy (DEsolv), we computed solvation energies using GIST-2016 and PME-GIST and then compared them to the solvation energies obtained by TI.…”

“…Indeed, several studies have used IST to estimate free energies of solvation for small molecules and amino acids. 15,16 However, discrepancies between how GIST tools estimate energies and how molecular dynamics (MD) engines calculate, particularly differences in the treatment of longrange interactions, have prevented precise comparison between GIST-calculated energies and the energies produced from MD free energy methods such as TI and FEP. Here, we address this by presenting a formalism by which PMEbased electrostatic energies 17,18 and long-range LJ energies 19 are decomposed and assigned to individual atoms and the corresponding voxels they occupy in a manner consistent with the GIST formulation.…”

Ground-State Destabilization by Active-Site Hydrophobicity Controls the Selectivity of a Cofactor- Free Decarboxylase

“…For this, an additional MD simulation was run for each enzyme for 100 ns, with all protein heavy atoms restrained (as is standard with this approach, see the Supplementary Methodology). 60 GIST analysis was then performed on the active site using CPPTRAJ 58 (see the Supplementary Methodology), with the output of the GIST analysis used to determine and project the "surface mapped hydrophobicity" onto each substrate atom, using the approach described by Kraml et al 61 We note that as our the GIST analysis was performed on the unliganded states of each enzyme (to identify how each enzyme modulates the active site enviroment), and the optimal positions of both carboxyl groups are essentially identical across the different substrates for the same binding pose, we focused our GIST analysis on only compound 1b (as this compound was studied by EVB and metadynamics simulations for all four enzymes).…”

“…Here, we used GIST to calculate the solvation free energy of the active site and used this as a measure of the hydrophobicity. 61 This approach explicity considers both non-additive and cooperative effects on the local hydrophobicity, 41,60,61 both of which are known to play significant roles in modulating the hydrophobicity/solvation free energy. 61,73 We projected the local hydrophobicity onto both possible reactive binding Poses (A and B) of compound 1b for each enzyme (Figures 8A and B for the wild-type enzyme and the CLG-IPL variant, and Figure S19 for the G74C/C188G and G74C/C188A variants).…”