Literature DB >> 10545346

A modular treatment of molecular traffic through the active site of cholinesterase.

S A Botti1, C E Felder, S Lifson, J L Sussman, I Silman.   

Abstract

We present a model for the molecular traffic of ligands, substrates, and products through the active site of cholinesterases (ChEs). First, we describe a common treatment of the diffusion to a buried active site of cationic and neutral species. We then explain the specificity of ChEs for cationic ligands and substrates by introducing two additional components to this common treatment. The first module is a surface trap for cationic species at the entrance to the active-site gorge that operates through local, short-range electrostatic interactions and is independent of ionic strength. The second module is an ionic-strength-dependent steering mechanism generated by long-range electrostatic interactions arising from the overall distribution of charges in ChEs. Our calculations show that diffusion of charged ligands relative to neutral isosteric analogs is enhanced approximately 10-fold by the surface trap, while electrostatic steering contributes only a 1.5- to 2-fold rate enhancement at physiological salt concentration. We model clearance of cationic products from the active-site gorge as analogous to the escape of a particle from a one-dimensional well in the presence of a linear electrostatic potential. We evaluate the potential inside the gorge and provide evidence that while contributing to the steering of cationic species toward the active site, it does not appreciably retard their clearance. This optimal fine-tuning of global and local electrostatic interactions endows ChEs with maximum catalytic efficiency and specificity for a positively charged substrate, while at the same time not hindering clearance of the positively charged products.

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Year:  1999        PMID: 10545346      PMCID: PMC1300520          DOI: 10.1016/S0006-3495(99)77080-3

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  80 in total

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3.  External and internal electrostatic potentials of cholinesterase models.

Authors:  C E Felder; S A Botti; S Lifson; I Silman; J L Sussman
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4.  Cationic and uncharged substrates and reversible inhibitors in hydrolysis by acetylcholinesterase (EC 3.1.1.7). The trimethyl subsite.

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5.  Responses of acetylcholinesterase from Torpedo marmorata to salts and curarizing drugs.

Authors:  J P Changeux
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7.  Cholinesterases regulate neurite growth of chick nerve cells in vitro by means of a non-enzymatic mechanism.

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8.  Electrostatic potential of the acetylcholine binding sites in the nicotinic receptor probed by reactions of binding-site cysteines with charged methanethiosulfonates.

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9.  Inhibition of serine proteases by peptidyl fluoromethyl ketones.

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10.  Fractional diffusion-limited component of reactions catalyzed by acetylcholinesterase.

Authors:  M Bazelyansky; E Robey; J F Kirsch
Journal:  Biochemistry       Date:  1986-01-14       Impact factor: 3.162

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  11 in total

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2.  Flexibility of aromatic residues in the active-site gorge of acetylcholinesterase: X-ray versus molecular dynamics.

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3.  Molecular docking study on the "back door" hypothesis for product clearance in acetylcholinesterase.

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4.  Forebrain Cholinergic Signaling: Wired and Phasic, Not Tonic, and Causing Behavior.

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6.  Acetylcholinesterase: from 3D structure to function.

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Journal:  Chem Biol Interact       Date:  2010-02-04       Impact factor: 5.192

7.  Synthesis and pharmacological evaluation of multi-functional homoisoflavonoid derivatives as potent inhibitors of monoamine oxidase B and cholinesterase for the treatment of Alzheimer's disease.

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Journal:  Medchemcomm       Date:  2017-05-24       Impact factor: 3.597

Review 8.  Acetylcholinesterase: a multifaceted target for structure-based drug design of anticholinesterase agents for the treatment of Alzheimer's disease.

Authors:  Harry M Greenblatt; Hay Dvir; Israel Silman; Joel L Sussman
Journal:  J Mol Neurosci       Date:  2003       Impact factor: 2.866

9.  The discovery of potential acetylcholinesterase inhibitors: a combination of pharmacophore modeling, virtual screening, and molecular docking studies.

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10.  qPIPSA: relating enzymatic kinetic parameters and interaction fields.

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