Dataset Information

Markov-State Transition Path Analysis of Electrostatic Channeling.

ABSTRACT: Electrostatic channeling is a naturally occurring approach to control the flux of charged intermediates in catalytic cascades. Computational techniques have enabled quantitative understanding of such mechanisms, augmenting experimental approaches by modeling molecular interactions in atomic detail. In this work, we report the first utilization of a Markov-state model (MSM) to describe the surface diffusion of a reaction intermediate, glucose 6-phosphate, on an artificially modified cascade where hexokinase and glucose-6-phosphate dehydrogenase are covalently conjugated by a cationic oligopeptide bridge. Conformation space networks are used to represent intermediate transport on enzyme surfaces, along with committor probabilities that assess the desorption probability of the intermediate on each segment of the channeling pathway. For the region between the peptide bridge and downstream active site, the ionic strength dependence of desorption probability by MSM agreed well with that by transition state theory. A kinetic Monte Carlo model integrates parameters from different computational methods to evaluate the contribution of desorption during each step. The approach is validated by calculation of kinetic lag time, which agrees well with experimental results. These results further demonstrate the applicability of molecular simulations and advanced sampling techniques to the design of chemical networks.

SUBMITTER: Liu Y

PROVIDER: S-EPMC6602406 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Markov-State Transition Path Analysis of Electrostatic Channeling.

Liu Yuanchao Y Hickey David P DP Minteer Shelley D SD Dickson Alex A Calabrese Barton Scott S

The journal of physical chemistry. C, Nanomaterials and interfaces 20190522 24

Electrostatic channeling is a naturally occurring approach to control the flux of charged intermediates in catalytic cascades. Computational techniques have enabled quantitative understanding of such mechanisms, augmenting experimental approaches by modeling molecular interactions in atomic detail. In this work, we report the first utilization of a Markov-state model (MSM) to describe the surface diffusion of a reaction intermediate, glucose 6-phosphate, on an artificially modified cascade where ...[more]

PMID: 31275507

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Project description:Glycinamide ribonucleotide transformylase (GART) undergoes a pH-dependent coil-helix transition with pK(a) approximately 7. An alpha-helix is formed at high pH spanning 8 residues of a 21-residue-long loop, comprising the segment Thr120-His121-Arg122-Gln123-Ala124-Leu125-Glu126-Asn127. To understand the electrostatic nature of this loop-helix, called the activation loop-helix, which leads to the formation and stability of the alpha-helix, pK(a) values of all ionizable residues of GART have been calculated, using Poisson-Boltzmann electrostatic calculations and crystallographic data. Crystallographic structures of high and low pH E70A GART have been used in our analysis. Low pK(a) values of 5.3, 5.3, 3.9, 1.7, and 4.7 have been calculated for five functionally important histidines, His108, His119, His121, His132, and His137, respectively, using the high pH E70A GART structure. Ten theoretical single and double mutants of the high pH E70A structure have been constructed to identify pairwise interactions of ionizable residues, which have aided in elucidating the multiplicity of electrostatic interactions of the activation loop-helix, and the impact of the activation helix on the catalytic site. Based on our pK(a) calculations and structural data, we propose that: (1) His121 forms a molecular switch for the coil-helix transition of the activation helix, depending on its protonation state; (2) a strong electrostatic interaction between His132 and His121 is observed, which can be of stabilizing or destabilizing nature for the activation helix, depending on the relative orientation and protonation states of the rings of His121 and His132; (3) electrostatic interactions involving His119 and Arg122 play a role in the stability of the activation helix; and (4) the activation helix contains the helix-promoting sequence Arg122-Gln123-Ala124-Leu125-Glu126, but its alignment relative to the N and C termini of the helix is not optimal, and is possibly of a destabilizing nature. Finally, we provide electrostatic evidence that the formation and closure of the activation helix create a hydrophobic environment for catalytic-site residue His108, to facilitate catalysis.

Dataset Information

Markov-State Transition Path Analysis of Electrostatic Channeling.

Publications

Markov-State Transition Path Analysis of Electrostatic Channeling.

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