scholarly journals Accounting for the Central Role of Interfacial Water in Protein-Ligand Binding Free Energy Calculations

Author(s):  
Ido Ben-Shalom ◽  
Zhixiong Lin ◽  
Brian Radak ◽  
Charles Lin ◽  
Woody Sherman ◽  
...  

Rigorous binding free energy methods in drug discovery are growing in popularity due to a combination of methodological advances, improvements in computer hardware, and workflow automation. These calculations typically use molecular dynamics (MD) to sample from the Boltzmann distribution of conformational states. However, when part or all the binding site is inaccessible to bulk solvent, the time needed for water molecules to equilibrate between bulk solvent and the binding site can be well beyond what is practical with standard MD. This sampling limitation is problematic in relative binding free energy calculations, which compute the reversible work of converting Ligand 1 to Ligand 2 within the binding site. Thus, if Ligand 1 is smaller and/or more polar than Ligand 2, the perturbation may allow additional water molecules to occupy a region of the binding site. However, this change in hydration may not be captured by standard MD simulations and may therefore lead to errors in the computed free energy. We recently developed a hybrid Monte Carlo/MD (MC/MD) method, which speeds the equilibration of water between bulk solvent and buried cavities, while sampling from the intended distribution of states. Here, we report on the use of this approach in the context of alchemical binding free energy calculations. We find that using MC/MD markedly improves the accuracy of the calculations and also reduces hysteresis between the forward and reverse perturbations, relative to matched calculations using only MD with or without the crystallographic water molecules. The present method is available for use in the AMBER simulation software.<br>

Author(s):  
Ido Ben-Shalom ◽  
Zhixiong Lin ◽  
Brian Radak ◽  
Charles Lin ◽  
Woody Sherman ◽  
...  

Rigorous binding free energy methods in drug discovery are growing in popularity due to a combination of methodological advances, improvements in computer hardware, and workflow automation. These calculations typically use molecular dynamics (MD) to sample from the Boltzmann distribution of conformational states. However, when part or all the binding site is inaccessible to bulk solvent, the time needed for water molecules to equilibrate between bulk solvent and the binding site can be well beyond what is practical with standard MD. This sampling limitation is problematic in relative binding free energy calculations, which compute the reversible work of converting Ligand 1 to Ligand 2 within the binding site. Thus, if Ligand 1 is smaller and/or more polar than Ligand 2, the perturbation may allow additional water molecules to occupy a region of the binding site. However, this change in hydration may not be captured by standard MD simulations and may therefore lead to errors in the computed free energy. We recently developed a hybrid Monte Carlo/MD (MC/MD) method, which speeds the equilibration of water between bulk solvent and buried cavities, while sampling from the intended distribution of states. Here, we report on the use of this approach in the context of alchemical binding free energy calculations. We find that using MC/MD markedly improves the accuracy of the calculations and also reduces hysteresis between the forward and reverse perturbations, relative to matched calculations using only MD with or without the crystallographic water molecules. The present method is available for use in the AMBER simulation software.<br>


2019 ◽  
Author(s):  
Panagiotis Lagarias ◽  
Kerry Barkan ◽  
Eva Tzortzini ◽  
Eleni Vrontaki ◽  
Margarita Stampelou ◽  
...  

<p>Adenosine A<sub>3 </sub>receptor (A<sub>3</sub>R), is a promising drug target against cancer cell proliferation. Currently there is no experimentally determined structure of A<sub>3</sub>R. Here, we have investigate a computational model, previously applied successfully for agonists binding to A<sub>3</sub>R, using molecular dynamic (MD) simulations, Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) binding free energy calculations. Extensive computations were performed to explore the binding profile of O4-{[3-(2,6-dichlorophenyl)-5-methylisoxazol-4-yl]carbonyl}-2-methyl-1,3-thiazole-4-carbohydroximamide (K18) to A<sub>3</sub>R. K18 is a new specific and competitive antagonist at the orthosteric binding site of A<sub>3</sub>R, discovered using virtual screening and characterized pharmacologically in our previous studies. The most plausible binding conformation for the dichlorophenyl group of K18 inside the A<sub>3</sub>R is oriented towards trans-membrane helices (TM) 5 and 6, according to the MM-PBSA and MM-GBSA binding free energy calculations, and by the previous results obtained by mutating residues of TM5, TM6 to alanine which reduce antagonist potency. The results from 14 site-directed mutagenesis experiments were interpreted using MD simulations and MM-GBSA calculations which show that the relative binding free energies of the mutant A<sub>3</sub>R - K18 complexes compare to the WT A<sub>3</sub>R are in agreement with the effect of the mutations, i.e. the reduction, maintenance or increase of antagonist potency. We show that when the residues V169<sup>5.30</sup>, M177<sup>5.38</sup>, I249<sup>6.54</sup> involved in direct interactions with K18 are mutated to alanine, the mutant A<sub>3</sub>R - K18 complexes reduce potency, increase the RMSD value of K18 inside the binding area and the MM-GBSA binding free energy compared to the WT A<sub>3</sub>R complex. Our computational model shows that other mutant A<sub>3</sub>R complexes with K18, including directly interacting residues, i.e. F168<sup>5.29</sup>A, L246<sup>6.51</sup>A, N250<sup>6.55</sup>A complexes with K18 are not stable. In these complexes of A<sub>3</sub>R mutated in directly interacting residues one or more of the interactions between K18 and these residues are lost. In agreement with the experiments, the computations show that, M174<sup>5.35</sup> a residue which does not make direct interactions with K18 is critical for K18 binding. A striking results is that the mutation of residue V169<sup>5.30</sup> to glutamic acid maintained antagonistic potency. This effect is in agreement with the binding free energy calculations and it is suggested that is due to K18 re-orientation but also to the plasticity of A<sub>3</sub>R binding area. The mutation of direct interacting L90<sup>3.32</sup> in the low region and the non-directly interacting L264<sup>7.35</sup> to alanine in the middle region increases the antagonistic potency, suggesting that chemical modifications of K18 can be applied to augment antagonistic potency. The calculated binding energies Δ<i>G</i><sub>eff</sub> values of K18 against mutant A<sub>3</sub>Rs displayed very good correlation with experimental potencies (pA<sub>2</sub> values). These results further approve the computational model for the description of K18 binding with critical residues of the orthosteric binding area which can have implications for the design of more effective antagonists based on the structure of K18.</p>


2019 ◽  
Author(s):  
Panagiotis Lagarias ◽  
Kerry Barkan ◽  
Eva Tzortzini ◽  
Eleni Vrontaki ◽  
Margarita Stampelou ◽  
...  

<p>Adenosine A<sub>3 </sub>receptor (A<sub>3</sub>R), is a promising drug target against cancer cell proliferation. Currently there is no experimentally determined structure of A<sub>3</sub>R. Here, we have investigate a computational model, previously applied successfully for agonists binding to A<sub>3</sub>R, using molecular dynamic (MD) simulations, Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) binding free energy calculations. Extensive computations were performed to explore the binding profile of O4-{[3-(2,6-dichlorophenyl)-5-methylisoxazol-4-yl]carbonyl}-2-methyl-1,3-thiazole-4-carbohydroximamide (K18) to A<sub>3</sub>R. K18 is a new specific and competitive antagonist at the orthosteric binding site of A<sub>3</sub>R, discovered using virtual screening and characterized pharmacologically in our previous studies. The most plausible binding conformation for the dichlorophenyl group of K18 inside the A<sub>3</sub>R is oriented towards trans-membrane helices (TM) 5 and 6, according to the MM-PBSA and MM-GBSA binding free energy calculations, and by the previous results obtained by mutating residues of TM5, TM6 to alanine which reduce antagonist potency. The results from 14 site-directed mutagenesis experiments were interpreted using MD simulations and MM-GBSA calculations which show that the relative binding free energies of the mutant A<sub>3</sub>R - K18 complexes compare to the WT A<sub>3</sub>R are in agreement with the effect of the mutations, i.e. the reduction, maintenance or increase of antagonist potency. We show that when the residues V169<sup>5.30</sup>, M177<sup>5.38</sup>, I249<sup>6.54</sup> involved in direct interactions with K18 are mutated to alanine, the mutant A<sub>3</sub>R - K18 complexes reduce potency, increase the RMSD value of K18 inside the binding area and the MM-GBSA binding free energy compared to the WT A<sub>3</sub>R complex. Our computational model shows that other mutant A<sub>3</sub>R complexes with K18, including directly interacting residues, i.e. F168<sup>5.29</sup>A, L246<sup>6.51</sup>A, N250<sup>6.55</sup>A complexes with K18 are not stable. In these complexes of A<sub>3</sub>R mutated in directly interacting residues one or more of the interactions between K18 and these residues are lost. In agreement with the experiments, the computations show that, M174<sup>5.35</sup> a residue which does not make direct interactions with K18 is critical for K18 binding. A striking results is that the mutation of residue V169<sup>5.30</sup> to glutamic acid maintained antagonistic potency. This effect is in agreement with the binding free energy calculations and it is suggested that is due to K18 re-orientation but also to the plasticity of A<sub>3</sub>R binding area. The mutation of direct interacting L90<sup>3.32</sup> in the low region and the non-directly interacting L264<sup>7.35</sup> to alanine in the middle region increases the antagonistic potency, suggesting that chemical modifications of K18 can be applied to augment antagonistic potency. The calculated binding energies Δ<i>G</i><sub>eff</sub> values of K18 against mutant A<sub>3</sub>Rs displayed very good correlation with experimental potencies (pA<sub>2</sub> values). These results further approve the computational model for the description of K18 binding with critical residues of the orthosteric binding area which can have implications for the design of more effective antagonists based on the structure of K18.</p>


2020 ◽  
Vol 118 (3) ◽  
pp. 144a
Author(s):  
Ido Y. Ben-Shalom ◽  
Charles Lin ◽  
Tom Kurtzman ◽  
Ross Walker ◽  
Michael K. Gilson

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.


2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresdern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains...


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