Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites

Ross, Gregory A.; Morris, Garrett M.; Biggin, Philip C.

doi:10.1371/journal.pone.0032036

Cited by 168 publications

(207 citation statements)

References 75 publications

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“…45 To calculate the binding free energies of strongly bound water molecules, we have modified the JAWS biasing term. These modifications are now discussed.…”

Section: Results and Discussion Jaws Placementmentioning

confidence: 99%

Strategies to Calculate Water Binding Free Energies in Protein–Ligand Complexes

Bodnarchuk

Viner

Michel

et al. 2014

J. Chem. Inf. Model.

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Water molecules are commonplace in protein binding pockets, where they can typically form a complex between the protein and a ligand or become displaced upon ligand binding.As a result, it is often of great interest to establish both the binding free energy and location of such molecules. Several approaches to predicting the location and affinity of water molecules to proteins have been proposed and utilized in the literature, although it is often unclear which method should be used under what circumstances. We report here a comparison between three such methodologies; Just Add Water Molecules (JAWS), Grand Canonical Monte Carlo (GCMC) and double-decoupling, in the hope of understanding the advantages and limitations of each method when applied to enclosed binding sites. As a result, we have adapted the JAWS scoring procedure, allowing the binding free energies of strongly bound water molecules to be * To whom correspondence should be addressed † University of Southampton ‡ Syngenta ¶ University of Edinburgh 1 calculated to a high degree of accuracy, requiring significantly less computational effort than more rigorous approaches. The combination of JAWS and GCMC offers a route to a rapid scheme capable of both locating and scoring water molecules for rational drug design.

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“…45 To calculate the binding free energies of strongly bound water molecules, we have modified the JAWS biasing term. These modifications are now discussed.…”

Section: Results and Discussion Jaws Placementmentioning

confidence: 99%

Strategies to Calculate Water Binding Free Energies in Protein–Ligand Complexes

Bodnarchuk

Viner

Michel

et al. 2014

J. Chem. Inf. Model.

View full text Add to dashboard Cite

show abstract

“…In these cases, the additional computational expense required by GCMC was required to improve on the accuracy of the much faster WaterDock. 4 A particularly stringent test of water placement with GCI was its application to MUP-I, as the binding cavity was expected to be have a low occupancy despite its size. 71 In agreement with a previous study, 72 we predicted the occupancy of the MUP-I cavity to be between zero and six molecules.…”

Section: Discussionmentioning

confidence: 99%

“…7,8 Inhomogeneous solvation theory, which has been used by numerous groups, [15][16][17][18] can also calculate the binding free energy of individual water molecules, with the added benefit of decomposing the binding free energies into enthalpies and entropies. Simple models and scoring-based methods have also been utilised to inform which waters should be targeted for displacement 4,19,20 .…”

Section: Introductionmentioning

confidence: 99%

Water Sites, Networks, And Free Energies with Grand Canonical Monte Carlo

2015

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Water molecules play integral roles in the formation of many protein-ligand complexes, and recent computational efforts have been focused on predicting the thermodynamic properties of individual waters and how they may be exploited in rational drug design. However, when water molecules form highly coupled hydrogen bonding networks, there is, as yet, no method that can rigorously calculate the free energy to bind the entire network, or assess the degree of cooperativity between waters. In this work, we report theoretical and methodological developments to the grand canonical Monte Carlo simulation technique. Central to our results is a rigorous equation that can be used to calculate efficiently the binding free energies of water networks of arbitrary size and complexity. Using a single set of simulations, our methods can locate waters, estimate their binding affinities, capture the cooperativity of the water network, and evaluate the hydration free energy of entire protein binding sites. Our techniques have been applied to multiple test systems and compare favourably to thermodynamic integra- *

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“…During all these steps the following parameters were used: a 10 Å cutoff with switching starting at 8.5 Å was applied to the electrostatics and van der Waals interactions; Particle Mesh Ewald method 19 was used for dealing with electrostatics interactions, grid spacing 1Å. Equilibrated protein structure was extracted; internal waters were added into protein cavities using WaterDock program 20 .…”

Section: Methodsmentioning

confidence: 99%

A voltage-dependent fluorescent indicator for optogenetic applications, archaerhodopsin-3: Structure and optical properties from in silico modeling

et al. 2017

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It was demonstrated in recent studies that some rhodopsins can be used in optogenetics as fluorescent indicators of membrane voltage. One of the promising candidates for these applications is archaerhodopsin-3. However, the fluorescent signal for wild-type achaerhodopsin-3 is not strong enough for real applications. Rational design of mutants with an improved signal is an important task, which requires both experimental and theoretical studies. Herein, we used a homology-based computational approach to predict the three-dimensional structure of archaerhodopsin-3, and a Quantum Mechanics/Molecular Mechanics (QM/MM) hybrid approach with high-level multireference ab initio methodology (SORCI+Q/AMBER) to model optical properties of this protein. We demonstrated that this methodology allows for reliable prediction of structure and spectral properties of archaerhodopsin-3. The results of this study can be utilized for computational molecular design of efficient fluorescent indicators of membrane voltage for modern optogenetics on the basis of archaerhodopsin-3.

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Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites

Cited by 168 publications

References 75 publications

Strategies to Calculate Water Binding Free Energies in Protein–Ligand Complexes

Strategies to Calculate Water Binding Free Energies in Protein–Ligand Complexes

Water Sites, Networks, And Free Energies with Grand Canonical Monte Carlo

A voltage-dependent fluorescent indicator for optogenetic applications, archaerhodopsin-3: Structure and optical properties from in silico modeling

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