scholarly journals A single molecular distance predicts agonist binding energy in nicotinic receptors

2019 ◽  
Vol 151 (4) ◽  
pp. 452-464 ◽  
Author(s):  
Sushree Tripathy ◽  
Wenjun Zheng ◽  
Anthony Auerbach
Keyword(s):  
Binding Energy ◽  
Acetylcholine Receptors ◽  
Structural Parameters ◽  
Aromatic Amino Acids ◽  
Binding Pocket ◽  
Binding Energies ◽  
Agonist Binding ◽  
Response Curves ◽  
Dynamics Simulations ◽  
Experimental Binding Energy

Agonists turn on receptors because they bind more strongly to active (R*) versus resting (R) conformations of their target sites. Here, to explore how agonists activate neuromuscular acetylcholine receptors, we built homology models of R and R* neurotransmitter binding sites, docked ligands to those sites, ran molecular dynamics simulations to relax (“equilibrate”) the structures, measured binding site structural parameters, and correlated them with experimental agonist binding energies. Each binding pocket is a pyramid formed by five aromatic amino acids and covered partially by loop C. We found that in R* versus R, loop C is displaced outward, the pocket is smaller and skewed, the agonist orientation is reversed, and a key nitrogen atom in the agonist is closer to the pocket center (distance dx) and a tryptophan pair but farther from αY190. Of these differences, the change in dx shows the largest correlation with experimental binding energy and provides a good estimate of agonist affinity, efficacy, and efficiency. Indeed, concentration–response curves can be calculated from just dx values. The contraction and twist of the binding pocket upon activation resemble gating rearrangements of the extracellular domain of related receptors at a smaller scale.

scholarly journals Agonists to ions: Efficiency suggests a 'zipper' mechanism for nicotinic receptor activation

2021 ◽  
Author(s):  
Anthony Auerbach
Keyword(s):  
Binding Energy ◽  
Nicotinic Receptor ◽  
Receptor Activation ◽  
Agonist Binding ◽  
Response Curves ◽  
Nicotinic Acetylcholine ◽  
Turn On ◽  
Activation Gating ◽  
Target Sites ◽  
Agonist Property

Agonists are classified by the strength at which they bind to their target sites (affinity) and their ability to activate receptors once bound to those sites (efficacy). Efficiency is a third fundamental agonist property that is a measure of the correlation between affinity and efficacy. Efficiency is the percent of agonist binding energy that is converted into energy for receptor activation ('gating'). In the muscle nicotinic acetylcholine receptor, agonists belong to families having discrete efficiencies of 54%, 51%, 42% or 35%. Efficiency depends on the size and composition of both the agonist and binding site, and can be estimated from, and used to interpret, concentration-response curves. A correlation between affinity and efficacy indicates that the agonist's energy changes that take place within binding and gating processes are linked. Efficiency suggests that receptors turn on and off by progressing through a sequence of energy-linked domain rearrangements, as in a zipper.

scholarly journals Efficiency measures the conversion of agonist binding energy into receptor conformational change

2019 ◽  
Vol 151 (4) ◽  
pp. 465-477 ◽  
Author(s):  
Tapan K. Nayak ◽  
Ridhima Vij ◽  
Iva Bruhova ◽  
Jayasha Shandilya ◽  
Anthony Auerbach
Keyword(s):  
Activation Energy ◽  
Binding Energy ◽  
Conformational Change ◽  
Acetylcholine Receptors ◽  
Single Channel ◽  
Equilibrium Constants ◽  
Bk Channels ◽  
Agonist Binding ◽  
Aryl Hydrocarbon ◽  
Efficiency Measures

Receptors alternate between resting↔active conformations that bind agonists with low↔high affinity. Here, we define a new agonist attribute, energy efficiency (η), as the fraction of ligand-binding energy converted into the mechanical work of the activation conformational change. η depends only on the resting/active agonist-binding energy ratio. In a plot of activation energy versus binding energy (an “efficiency” plot), the slope gives η and the y intercept gives the receptor’s intrinsic activation energy (without agonists; ΔG0). We used single-channel electrophysiology to estimate η for eight different agonists and ΔG0 in human endplate acetylcholine receptors (AChRs). From published equilibrium constants, we also estimated η for agonists of KCa1.1 (BK channels) and muscarinic, γ-aminobutyric acid, glutamate, glycine, and aryl-hydrocarbon receptors, and ΔG0 for all of these except KCa1.1. Regarding AChRs, η is 48–56% for agonists related structurally to acetylcholine but is only ∼39% for agonists related to epibatidine; ΔG0 is 8.4 kcal/mol in adult and 9.6 kcal/mol in fetal receptors. Efficiency plots for all of the above receptors are approximately linear, with η values between 12% and 57% and ΔG0 values between 2 and 12 kcal/mol. Efficiency appears to be a general attribute of agonist action at receptor binding sites that is useful for understanding binding mechanisms, categorizing agonists, and estimating concentration–response relationships.

scholarly journals Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19

Antibiotics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 856
Author(s):  
Faizul Azam
Keyword(s):  
Binding Energy ◽  
Nucleocapsid Protein ◽  
Drug Targets ◽  
Bacterial Infections ◽  
Interaction Mechanism ◽  
Binding Energies ◽  
Ligand Complex ◽  
Average Binding Energy ◽  
Dynamics Simulations

Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro, and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were employed to decrypt the mechanistic insight of teicoplanin interaction with several COVID-19 drug targets. Initially, molecular docking was employed to study the teicoplanin interaction with twenty-five SARS-CoV-2 structural and non-structural proteins which was followed by molecular mechanics/generalized Born surface area (MM/GBSA) computation for binding energy predictions of top ten models from each target. Amongst all macromolecular targets, the N-terminal domain of the nucleocapsid protein displayed the strongest affinity with teicoplanin showing binding energies of −7.4 and −102.13 kcal/mol, in docking and Prime MM/GBSA, respectively. Thermodynamic stability of the teicoplanin-nucleocapsid protein was further probed by molecular dynamics simulations of protein–ligand complex as well as unbounded protein in 100 ns trajectories. Post-simulation MM-GBSA computation of 50 frames extracted from simulated trajectories estimated an average binding energy of −62.52 ± 12.22 kcal/mol. In addition, conformational state of protein in complex with docked teicoplanin displayed stable root-mean-square deviation/fluctuation. In conclusion, computational investigation of the potential targets of COVID-19 and their interaction mechanism with teicoplanin can guide the design of novel therapeutic armamentarium for the treatment of SARS-CoV-2 infection. However, additional studies are warranted to establish the clinical use or relapses, if any, of teicoplanin in the therapeutic management of COVID-19 patients.

scholarly journals Agonist efficiency estimated from concentration-response curves

2020 ◽  
Author(s):  
Dinesh C. Indurthi ◽  
Anthony Auerbach
Keyword(s):  
Binding Energy ◽  
Binding Site ◽  
Nicotinic Acetylcholine Receptors ◽  
Acetylcholine Receptors ◽  
Head Group ◽  
Constitutive Activity ◽  
High Concentration ◽  
Response Curves ◽  
Nicotinic Acetylcholine ◽  
Low Efficiency

AbstractConcentration-response curves (CRCs) are characterized by a midpoint (EC50) and a high-concentration asymptote (Pomax) that relate to agonist affinity and efficacy. A third agonist attribute, efficiency, is the fraction of binding energy that is applied to the conformational change that activates the receptor. Here we show that agonist efficiency can be calculated from EC50 and Pomax, and estimate the efficiencies of 17 agonists of adult muscle nicotinic acetylcholine receptors (AChRs). The distribution of efficiency values was bi-modal with means+s.d of 52±2% (n=11) and 41±3% (n=6). Efficiency is correlated inversely with the volume of the agonists’ head-group. For 22 binding site mutations only αY190A affects significantly ACh efficiency, switching it from the high-to the low-efficiency population. If agonist efficiency is known, EC50 can be estimated from Pomax and the receptor’s level of constitutive activity can be calculated from a CRC.

scholarly journals Simulations support the interaction of the SARS-CoV-2 spike protein with nicotinic acetylcholine receptors

2020 ◽  
Author(s):  
A. Sofia F. Oliveira ◽  
Amaurys Avila Ibarra ◽  
Isabel Bermudez ◽  
Lorenzo Casalino ◽  
Zied Gaieb ◽  
...  
Keyword(s):  
Binding Energy ◽  
Nicotinic Acetylcholine Receptors ◽  
Acetylcholine Receptors ◽  
Binding Pocket ◽  
Spike Protein ◽  
Receptor Subtype ◽  
Nicotinic Acetylcholine ◽  
S Protein ◽  
Open Conformation ◽  
Potential Binding

AbstractChangeux et al. recently suggested that the SARS-CoV-2 spike (S) protein may interact with nicotinic acetylcholine receptors (nAChRs). Such interactions may be involved in pathology and infectivity. Here, we use molecular simulations of validated atomically detailed structures of nAChRs, and of the S protein, to investigate this ‘nicotinic hypothesis’. We examine the binding of the Y674-R685 loop of the S protein to three nAChRs, namely the human α4β2 and α7 subtypes and the muscle-like αβγd receptor from Tetronarce californica. Our results indicate that Y674-R685 has affinity for nAChRs and the region responsible for binding contains the PRRA motif, a four-residue insertion not found in other SARS-like coronaviruses. In particular, R682 has a key role in the stabilisation of the complexes as it forms interactions with loops A, B and C in the receptor’s binding pocket. The conformational behaviour of the bound Y674-R685 region is highly dependent on the receptor subtype, adopting extended conformations in the α4β2 and α7 complexes and more compact ones when bound to the muscle-like receptor. In the α4β2 and αβγd complexes, the interaction of Y674-R685 with the receptors forces the loop C region to adopt an open conformation similar to other known nAChR antagonists. In contrast, in the α7 complex, Y674-R685 penetrates deeply into the binding pocket where it forms interactions with the residues lining the aromatic box, namely with TrpB, TyrC1 and TyrC2. Estimates of binding energy suggest that Y674-R685 forms stable complexes with all three nAChR subtypes. Analyses of the simulations of the full-length S protein show that the Y674-R685 region is accessible for binding, and suggest a potential binding orientation of the S protein with nAChRs.

Combined Virtual Screening, DFT Calculations and Molecular Dynamics Simulations to Discovery of Potent MMP-9 Inhibitors

2019 ◽  
Vol 16 (8) ◽  
pp. 892-903
Author(s):  
Hamed Bahrami ◽  
Hafezeh Salehabadi ◽  
Zahra Nazari ◽  
Massoud Amanlou
Keyword(s):  
Molecular Dynamics ◽  
Binding Energy ◽  
Virtual Screening ◽  
Dft Calculations ◽  
Molecular Dynamics Simulations ◽  
Density Functional ◽  
Docking Studies ◽  
Binding Energies ◽  
Energy Calculations ◽  
Dynamics Simulations

Background: Matrix metalloproteinase-9 (MMP-9) plays a crucial role in the development and progression of cancer. Therefore, identifying its inhibitors has enjoyed numerous attentions. In this report, a hybrid approach, including pharmacophore-based virtual screening, docking studies, and density functional theory (DFT) binding energy calculations followed by molecular dynamics simulations, was used to identify potential MMP-9 inhibitors. Methods: Pharmacophore modeling based on ARP101, as a known MMP-9 inhibitor, was performed and followed by virtual screening of ZINC database and docking studies to introduce a set of new ligands as candidates for potent inhibitors of MMP-9. The binding energies of MMP-9 and the selected ligands as well as ARP101, were estimated via the DFT energy calculations. Subsequently, molecular dynamics simulations were applied to evaluate and compare the behavior of ARP101 and the selected ligand in a dynamic environment. Results: (S,Z)-6-(((2,3-dihydro-1H-benzo[d]imidazol-2-yl)thio)methylene)-2-((4,6,7- trimethylquinazolin- 2-yl)amino)-1,4,5,6-tetrahydropyrimidin-4-ol, ZINC63611396, with the largest DFT binding energy, was selected as a proper potent MMP-9 inhibitor. Molecular dynamics simulations indicated that the new ligand was stable in the active site. Conclusion: The results of this study revealed that compared to the binding energies achieved from the docking studies, the binding energies obtained from the DFT calculations were more consistent with the intermolecular interactions. Also, the interaction between the Zinc ion and ligand, in particular the Zn2+-ligand distance, played a profound role in the quantity of DFT binding energies.

scholarly journals Benchmarking binding energy calculations for organic structure-directing agents in pure-silica zeolites

2021 ◽  
Author(s):  
Daniel Schwalbe-Koda ◽  
Rafael Gomez-Bombarelli
Keyword(s):  
Binding Energy ◽  
Density Functional ◽  
Single Point ◽  
Cost Effective ◽  
Binding Energies ◽  
Computationally Efficient ◽  
Organic Structure ◽  
Pure Silica ◽  
Structure Directing Agents ◽  
Dynamics Simulations

Molecular modeling plays an important role in the discovery of organic structure-directing agents (OSDAs) for zeolites. By quantifying the intensity of host-guest interactions, it is possible to select cost-effective molecules that maximize binding towards a given zeolite framework. Over the last decades, a variety of methods and levels of theory have been used to calculate these binding energies. Nevertheless, there is no consensus on the best calculation strategy for high-throughput virtual screening undertakings. In this work, we compare binding affinities from density functional theory (DFT) and force field calculations for 272 zeolite-OSDA pairs obtained from static and time-averaged simulations. Enabled by automation software, we show that binding energies from the frozen pose method correlate best with DFT time-averaged energies. They are also less sensitive to the choice of initial lattice parameters and optimization algorithms, as well as less computationally expensive. Furthermore, we demonstrate that a broader exploration of the conformation space from molecular dynamics simulations does not provide significant improvements in binding energy trends over single-point calculations. The code and benchmark data are open-sourced and provide robust and computationally-efficient guidelines to calculating binding energies in zeolite-OSDA pairs.

On the Adsorption of Aspartate Derivatives to Calcite Surfaces in Aqueous Environment

2020 ◽  
Author(s):  
Robert Stepic ◽  
Lara Jurković ◽  
Ksenia Klementyeva ◽  
Marko Ukrainczyk ◽  
Matija Gredičak ◽  
...  
Keyword(s):  
Active Sites ◽  
Realistic Model ◽  
Binding Energies ◽  
Inhibition Mechanism ◽  
Aqueous Environment ◽  
Binding Modes ◽  
Carboxylate Groups ◽  
Dissolved Ions ◽  
Living Organisms ◽  
Dynamics Simulations

In many living organisms, biomolecules interact favorably with various surfaces of calcium carbonate. In this work, we have considered the interactions of aspartate (Asp) derivatives, as models of complex biomolecules, with calcite. Using kinetic growth experiments, we have investigated the inhibition of calcite growth by Asp, Asp2 and Asp3.This entailed the determination of a step-pinning growth regime as well as the evaluation of the adsorption constants and binding free energies for the three species to calcite crystals. These latter values are compared to free energy profiles obtained from fully atomistic molecular dynamics simulations. When using a flat (104) calcite surface in the models, the measured trend of binding energies is poorly reproduced. However, a more realistic model comprised of a surface with an island containing edges and corners, yields binding energies that compare very well with experiments. Surprisingly, we find that most binding modes involve the positively charged, ammonium group. Moreover, while attachment of the negatively charged carboxylate groups is also frequently observed, it is always balanced by the aqueous solvation of an equal or greater number of carboxylates. These effects are observed on all calcite features including edges and corners, the latter being associated with dominant affinities to Asp derivatives. As these features are also precisely the active sites for crystal growth, the experimental and theoretical results point strongly to a growth inhibition mechanism whereby these sites become blocked, preventing further attachment of dissolved ions and halting further growth.

Schistosomal Sulfotransferase Interaction with Oxamniquine Involves Hybrid Mechanism of Induced-fit and Conformational Selection

2020 ◽  
Vol 16 (4) ◽  
pp. 451-459 ◽  
Author(s):  
Fortunatus C. Ezebuo ◽  
Ikemefuna C. Uzochukwu
Keyword(s):  
Molecular Dynamics ◽  
Amino Acid ◽  
Binding Energy ◽  
Binding Site ◽  
Conformational Dynamics ◽  
Side Chain ◽  
Amino Acid Residues ◽  
Conformational Selection ◽  
Hybrid Mechanism ◽  
Dynamics Simulations

Background: Sulfotransferase family comprises key enzymes involved in drug metabolism. Oxamniquine is a pro-drug converted into its active form by schistosomal sulfotransferase. The conformational dynamics of side-chain amino acid residues at the binding site of schistosomal sulfotransferase towards activation of oxamniquine has not received attention. Objective: The study investigated the conformational dynamics of binding site residues in free and oxamniquine bound schistosomal sulfotransferase systems and their contribution to the mechanism of oxamniquine activation by schistosomal sulfotransferase using molecular dynamics simulations and binding energy calculations. Methods: Schistosomal sulfotransferase was obtained from Protein Data Bank and both the free and oxamniquine bound forms were subjected to molecular dynamics simulations using GROMACS-4.5.5 after modeling it’s missing amino acid residues with SWISS-MODEL. Amino acid residues at its binding site for oxamniquine was determined and used for Principal Component Analysis and calculations of side-chain dihedrals. In addition, binding energy of the oxamniquine bound system was calculated using g_MMPBSA. Results: The results showed that binding site amino acid residues in free and oxamniquine bound sulfotransferase sampled different conformational space involving several rotameric states. Importantly, Phe45, Ile145 and Leu241 generated newly induced conformations, whereas Phe41 exhibited shift in equilibrium of its conformational distribution. In addition, the result showed binding energy of -130.091 ± 8.800 KJ/mol and Phe45 contributed -9.8576 KJ/mol. Conclusion: The results showed that schistosomal sulfotransferase binds oxamniquine by relying on hybrid mechanism of induced fit and conformational selection models. The findings offer new insight into sulfotransferase engineering and design of new drugs that target sulfotransferase.

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