Grand Canonical Monte Carlo Simulation of Ligand−Protein Binding

Guarnieri, Frank; Shkurko, Igor; Wiseman, Jeffrey S.

doi:10.1021/ci050268f

Cited by 96 publications

(83 citation statements)

References 42 publications

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“…Binding of ethanol to the model NR2A subunit was evaluated by adapting the general Monte Carlo simulation method of Clark et al (37). For the MD simulation, the NR2A subunit was solvated with a 3.5-Å layer of ethanol, which included 122 solvent molecules.…”

Section: Molecular Modeling and Molecular Dynamics (Md)mentioning

confidence: 99%

Functional Interactions of Alcohol-sensitive Sites in the N-Methyl-d-aspartate Receptor M3 and M4 Domains

Ren

Salous

Paul

et al. 2008

Journal of Biological Chemistry

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The N-methyl-D-aspartate receptor is an important mediator of the behavioral effects of ethanol in the central nervous system. Previous studies have demonstrated sites in the third and fourth membrane-associated (M) domains of the N-methyl-Daspartate receptor NR2A subunit that influence alcohol sensitivity and ion channel gating. We investigated whether two of these sites, Phe-637 in M3 and Met-823 in M4, interactively regulate the ethanol sensitivity of the receptor by testing dual substitution mutants at these positions. Ethanol is unusual among the major drugs of abuse in that it acts only at high concentrations (in the millimolar range) and that it acts on multiple targets in the central nervous system. For the greater part of the last century, ethanol was generally believed to produce its effects on central nervous system function via nonspecific actions on neuronal lipids, but it is now well accepted that the biologically important actions of ethanol are due to its interactions with proteins (1, 2). Of these proteins, the N-methyl-D-aspartate (NMDA) 2 receptor is among the most important target sites of ethanol in the central nervous system. At relevant concentrations, ethanol inhibits ionic current (3), synaptic potentials (4), Ca 2ϩ influx (5, 6), and neurotransmitter release (7) mediated by NMDA receptors. Studies of the mechanism of this inhibition have shown that it does not involve competitive inhibition at the glutamate or glycine binding sites (7-12) or interaction with sites for other allosteric modulators (8,12) or open channel block (13,14) but that it involves changes in NMDA receptor gating, notably mean open time and opening frequency (13,14). Thus, ethanol appears to inhibit NMDA receptors via low affinity interactions with sites that regulate ion channel gating. Although sites in the intracellular C-terminal domain may modulate both ethanol sensitivity of the NMDA receptor (15) and ion channel gating (16 -19), this domain does not contain the site of ethanol action, since removal of this region of the protein does not decrease ethanol inhibition of the receptor (20).In a previous study, Ronald et al. (21) demonstrated that a phenylalanine residue (Phe-639) in the third membrane-associated (M) domain of the NMDA receptor NR1 subunit influences alcohol sensitivity and shows some characteristics of a site of alcohol action. A previous study from this laboratory (22) identified a methionine residue in the M4 domain of the NMDA receptor NR2A subunit that also influences alcohol sensitivity and that fulfills some of the criteria for a site of alcohol action. The methionine in M4, however, also profoundly affects the gating behavior of the ion channel (23). We have recently shown (24) that the cognate position of NR1(Phe-639) in the NR2A subunit, Phe-637, also regulates alcohol sensitivity as well as desensitization and agonist potency. Studies in ␥-aminobutyric acid A and glycine receptors have demonstrated residues in transmembrane domains 2 and 3 that form sites of alcohol and anesthetic act...

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Section: Molecular Modeling and Molecular Dynamics (Md)mentioning

confidence: 99%

Functional Interactions of Alcohol-sensitive Sites in the N-Methyl-d-aspartate Receptor M3 and M4 Domains

Ren

Salous

Paul

et al. 2008

Journal of Biological Chemistry

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“…Which approach to dealing with protein flexibility will ultimately yield the best combination of computational speed and accuracy for free energy calculations remains to be determined. Using a single protein structure has proven satisfactory in the limited number of cases reported to date [Clark et al, 2006;Moore, 2005]. The data in the next section further support this approach.…”

Section: Protein Structurementioning

confidence: 70%

“…The calculation is based on the Grand Canonical Ensemble formalism from statistical thermodynamics [Guarnieri, 2004;Clark et al, 2006]. This method is fragment-based, meaning that binding affinities are computed for molecular fragments in the 100-200-dalton size range and the fragments are then computationally assembled into a virtual molecule library.…”

Section: Computation Of Binding Free Energymentioning

confidence: 99%

“…The first application of the Grand Canonical method to compute ligand-macromolecule binding affinities was used to compute the differential binding affinities of water for the major vs. minor groove of DNA, for example [Guarnieri and Mezei, 1996]. This method has been used successfully to identify water molecules that bind tightly to proteins and cannot be displaced by small organic ligands [Clark et al, 2006]. These water molecules can be considered to be just an element of the protein structure when designing ligands.…”

Section: Solvationmentioning

confidence: 99%

“…Since this method will simulate the complete water network at the binding site, both with and without bound ligand, it is straightforward to determine that many ligands will displace all of the water molecules in the binding pocket. In this case, therefore, the correction for desolvation of the protein will be constant across a chemical series, and accurate rank ordering of ligand potency is a more than adequate outcome in most cases [Clark et al, 2006].…”

Section: Solvationmentioning

confidence: 99%

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Developing technologies in biodefense research: computational drug design

Meshkat¹,

Talbot²,

Konteatis³

et al. 2009

Drug Development Research

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The development of small-molecule drugs to counter the threat of bioterrorism will differ from classical drug discovery because it will be impossible to evaluate efficacy in clinical trials for many agents. This difference focuses biodefense on the identification of multiple drug candidates for each threat organism so that multiple treatments can be mounted simultaneously when needed to maximize the probability of success. Accordingly, drug discovery will become the rate-and cost-limiting phase of the overall drug development process. We address the potential of computational chemistry to optimize efficiency and efficacy in the discovery phase. The major elements required for a successful computational approach are the calculation of binding free energy, accounting for changes in solvation on ligand binding, and compensating for protein flexibility. Drug Dev Res 70 : 279-287, 2009. r

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Location of Binding Sites on Proteins by the Multiple Solvent Crystal Structure Method

Ringe

Mattos

2006

Fragment‐based Approaches in Drug Discovery

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IntroductionOne of the greater challenges of structural biology is to characterize proteins in enough detail so that the structures can be used for computational prediction of function, and for the design of compounds that can be used to modulate or to interfere with that function. In general, the function of a protein is associated with its interaction with other molecules, either small molecules or other large biological molecules, such as nucleic acids or proteins. Invariably, the function can be disrupted when that interaction is prevented. A complete industry exists solely for the purpose of finding such disruptors -they are called drugs. The discovery of drugs had been a serendipitous process, in an age when very little was known about the structures of the small molecules or their targets. The process of discovery has become more sophisticated as such structures became available.The success of this process relies on knowing where an interaction site is located on a protein and characterizing the properties of that site. The first step is therefore the location of such a site. The properties of the site can then be used to design a molecule that fits it perfectly in terms of size, shape and chemical properties. One method to obtain such properties is to map a site with chemical probe molecules. Ideally these probe molecules can be connected to form a larger molecule that takes advantage of as many of the potential interaction partners in the site as possible. Finally, when the process of finding and characterizing becomes robust enough, the process can be accomplished computationally.At this moment in time, locating a binding site on a protein without any extraneous information, such as a fortuitously bound ligand in the crystal structure, is only marginally successful. The characterization of a binding site is still very laborious when done experimentally and is not robust when done computationally. Thus, mapping such a site with chemical probes could help characterize the site, the map then being used to design a specific ligand unique for the site. In addition, such a map can provide the data from which computational approaches can be calibrated. One way in which mapping can be achieved is to use a variety of small probe molecules and observe where they bind to the surface of the protein. 67 Fragment-based Approaches in Drug Discovery. Edited

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Grand Canonical Monte Carlo Simulation of Ligand−Protein Binding

Cited by 96 publications

References 42 publications

Functional Interactions of Alcohol-sensitive Sites in the N-Methyl-d-aspartate Receptor M3 and M4 Domains

Functional Interactions of Alcohol-sensitive Sites in the N-Methyl-d-aspartate Receptor M3 and M4 Domains

Developing technologies in biodefense research: computational drug design

Location of Binding Sites on Proteins by the Multiple Solvent Crystal Structure Method

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