scholarly journals Rationalizing generation of broad spectrum antibiotics with the addition of a primary amine

2021 ◽  
Author(s):  
Nandan Haloi ◽  
Archit Kumar Vasan ◽  
Emily Jane Geddes ◽  
Arjun Prasanna ◽  
Po-Chao Wen ◽  
...  
Keyword(s):  
Free Energy ◽  
Primary Amine ◽  
Electrostatic Interactions ◽  
Degrees Of Freedom ◽  
Md Simulations ◽  
Free Energy Calculations ◽  
Gram Negative ◽  
Molecular Conformations ◽  
Energy Calculations ◽  
Cell Accumulation

Antibiotic resistance of Gram-negative bacteria is largely attributed to the low permeability of their outer membrane (OM). Recently, we disclosed the eNTRy rules, a key lesson of which is that the introduction of a primary amine enhances OM permeation in certain contexts. To understand the molecular basis for this finding, we perform an extensive set of molecular dynamics (MD) simulations and free energy calculations comparing the permeation of aminated and amine-free antibiotic derivatives through the most abundant OM porin of E. coli, OmpF. To improve sampling of conformationally flexible drugs in MD simulations, we developed a novel, Monte Carlo and graph theory based algorithm to probe more efficiently the rotational and translational degrees of freedom visited during the permeation of the antibiotic molecule through OmpF. The resulting pathways were then used for free-energy calculations, revealing a lower barrier against the permeation of the aminated compound, substantiating its greater OM permeability. Further analysis revealed that the amine facilitates permeation by enabling the antibiotic to align its dipole to the luminal electric field of the porin and while forming favorable electrostatic interactions with specific, highly-conserved charged residues. The importance of these interactions in permeation was further validated with experimental mutagenesis and whole cell accumulation assays. Overall, this study provides insights on the importance of the primary amine for antibiotic permeation into Gram-negative pathogens that could help the design of future antibiotics. We also offer a new computational approach for calculating free-energy of processes where relevant molecular conformations cannot be efficiently captured.

Small-to-Large Length Scale Transition of TMAO Interaction with Hydrophobic Solutes

2021 ◽  
Author(s):  
Angelina Folberth ◽  
Swaminath Bharadwaj ◽  
Nico van der Vegt
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Md Simulations ◽  
Free Energy Calculations ◽  
Length Scale ◽  
Simulation Data ◽  
Energy Calculations ◽  
Large Length ◽  
Hydrophobic Solutes ◽  
Large Length Scale

We report the effect of trimethylamine N-oxide (TMAO) on the solvation of nonpolar solutes in water studied with molecular dynamics (MD) simulations and free-energy calculations. The simulation data indicate the...

Insights to the Binding of a Selective Adenosine A3 Receptor Antagonist using Molecular Dynamics Simulations, Binding Free Energy Calculations and Mutagenesis

2019 ◽  
Author(s):  
Panagiotis Lagarias ◽  
Kerry Barkan ◽  
Eva Tzortzini ◽  
Eleni Vrontaki ◽  
Margarita Stampelou ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Model ◽  
Molecular Mechanics ◽  
Surface Area ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Free Energy Calculations ◽  
Binding Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations

<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>

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

2020 ◽  
Author(s):  
Ido Ben-Shalom ◽  
Zhixiong Lin ◽  
Brian Radak ◽  
Charles Lin ◽  
Woody Sherman ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Site ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Computer Hardware ◽  
Water Molecules ◽  
Energy Calculations ◽  
Binding Free Energy Calculations

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>

scholarly journals Insights to the Binding of a Selective Adenosine A3 Receptor Antagonist using Molecular Dynamics Simulations, Binding Free Energy Calculations and Mutagenesis

2019 ◽  
Author(s):  
Panagiotis Lagarias ◽  
Kerry Barkan ◽  
Eva Tzortzini ◽  
Eleni Vrontaki ◽  
Margarita Stampelou ◽  
...  
Keyword(s):  
Free Energy ◽  
Computational Model ◽  
Molecular Mechanics ◽  
Surface Area ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Free Energy Calculations ◽  
Binding Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations

<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>

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

2020 ◽  
Author(s):  
Ido Ben-Shalom ◽  
Zhixiong Lin ◽  
Brian Radak ◽  
Charles Lin ◽  
Woody Sherman ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Site ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Computer Hardware ◽  
Water Molecules ◽  
Energy Calculations ◽  
Binding Free Energy Calculations

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>

scholarly journals The Energetics of Cholesterol Transport through Patched1: MD Simulations and Free Energy Calculations

2021 ◽  
Vol 120 (3) ◽  
pp. 72a
Author(s):  
T. Bertie Ansell ◽  
Robin A. Corey ◽  
Christian Siebold ◽  
Mark S. Sansom
Keyword(s):  
Free Energy ◽  
Md Simulations ◽  
Free Energy Calculations ◽  
Cholesterol Transport ◽  
Energy Calculations
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