Electrostatic models for computing protonation and redox equilibria in proteins

Ullmann, G. Matthias; Ew, Knapp

doi:10.1007/s002490050236

Cited by 249 publications

(369 citation statements)

References 118 publications

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“…The intrinsic pK a , pK intr , and the interaction energy matrix W µν can be calculated from the linearized Poisson-Boltzmann equation as described in detail elsewhere. 13,22,32 In analogy to eq. (2), d µ is identified as dead-end if:…”

Section: Application Of X-dee To the Determination Of Protonation Statesmentioning

confidence: 99%

“…Consequently, algorithms that are able to produce gap-free lists of low energy states, i.e., lists of states that are complete up to a given energy distance from the global energy minimum, are of general interest in structural biology. While Monte Carlo techniques allow to sample low energy states and generally provide an accurate description of thermal properties, 13 they do not allow to obtain gap-free lists of low-energy states for a given energy range. This is a major drawback if one investigates the kinetics of a working enzyme.…”

Section: Introductionmentioning

confidence: 99%

“…The protonation state energy is routinely calculated from intrinsic energies of the sites and pairwise interaction between the protonatable residues. 13,22,23 The energy contribution of each protonatable residue depends on its protonation form. In proteins, not only the state of lowest energy but also the next higher protonation states are commonly significantly populated and often play a functional role.…”

Section: Introductionmentioning

confidence: 99%

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An extended dead‐end elimination algorithm to determine gap‐free lists of low energy states

2007

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Abstract:Proteins are flexible systems and commonly populate several functionally important states. To understand protein function, these states and their energies have to be identified. We introduce an algorithm that allows the determination of a gap-free list of the low energy states. This algorithm is based on the dead-end elimination (DEE) theorem and is termed X-DEE (extended DEE). X-DEE is applicable to discrete systems whose state energy can be formulated as pairwise interaction between sites and their intrinsic energies. In this article, the computational performance of X-DEE is analyzed and discussed. X-DEE is implemented to determine the lowest energy protonation states of proteins, a problem to which DEE has not been applied so far. We use X-DEE to calculate a list of low energy protonation states for two bacteriorhodopsin structures that represent the first proton transfer step of the bacteriorhodopsin photocycle.

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Section: Application Of X-dee To the Determination Of Protonation Statesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An extended dead‐end elimination algorithm to determine gap‐free lists of low energy states

2007

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“…The dielectric constant for the cells inside the protein was assigned a value of 2 [6], inside the solution it is 80, at the boundary protein-solution it is 40, and the value of the ionic strength inside the protein was assigned zero. The potential in every such cell is calculated by the iterative formula using the values obtained at the preceding step in six neighboring cells [31]:…”

Section: Simulation Of Electrostatic Interactionsmentioning

confidence: 99%

“…To calculate this force, the electrostatic potential was determined using the Poisson-Boltzmann equation [7,31] that describes an electric field around the immobile charges with account of free ions:…”

Section: Simulation Of Electrostatic Interactionsmentioning

confidence: 99%

Computer Simulation of Protein-Protein Association in Photosynthesis

Kovalenko

Abaturova

Diakonova

et al. 2011

Math. Model. Nat. Phenom.

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Abstract. The paper is devoted to the method of computer simulation of protein interactions taking part in photosynthetic electron transport reactions. Using this method we have studied kinetic characteristics of protein-protein complex formation for four pairs of proteins involved in photosynthesis at a variety of ionic strength values. Computer simulations describe non-monotonic dependences of complex formation rates on the ionic strength as the result of long-range electrostatic interactions. Calculations confirm that the decrease in the association second order rate constant at low values of the ionic strength is caused by the protein pairs spending more time in "wrong" orientations which do not satisfy the docking conditions and so do not form the final complex capable of the electron transfer.

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Calculation of Reduction Potential and p K _a

Jensen

2005

Encyclopedia of Inorganic Chemistry

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Three methods, quantum mechanical and molecular mechanical polarizable continuum model (QM/MM/PCM), QM/PCM, and empirical, were developed and applied to calculate protein reduction potential ( E 0 ) and p K a values. In the QM/MM/PCM calculation of Lys55 p K a of turkey ovomucoid third domain (OMTKY3), the MP2/6‐31 + G(2d,p) method was used to describe the QM region consisting of ∼45 atoms; the rest of the protein was modeled either with ab initio‐derived electric multipole points or atomic charges from standard force field methods; and the aqueous solvation effect was described with the polarizable continuum model (PCM). The calculated Lys55 p K a values are in good agreement with experiments. QM/PCM methods were used to calculate p K a values of various proteins and the E 0 of type‐1 Cu centers. For solvent‐exposed p K a sites, QM/PCM (MP2/6‐31 + G(2d,p) for ∼100 atoms, PCM with dielectric = 78.39 for aqueous solution) methods can often reproduce experimental p K a values. For type‐1 Cu E 0 , because of protein burial, the desolvation effect becomes significant: it was found that Cu‐ligand interactions and desolvation can potentially change the E 0 by ∼300 and ∼400 mV, respectively, using the CPCM/B3LYP/6‐311++G(2df,p) method and model molecules of ∼100 atoms. An empirical method, PROPKA, was developed for protein p K a calculation and analysis, which is able to calculate the p K a values of a protein within ∼1 s.

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Electrostatic models for computing protonation and redox equilibria in proteins

Cited by 249 publications

References 118 publications

An extended dead‐end elimination algorithm to determine gap‐free lists of low energy states

An extended dead‐end elimination algorithm to determine gap‐free lists of low energy states

Computer Simulation of Protein-Protein Association in Photosynthesis

Calculation of Reduction Potential and p K _a

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Electrostatic models for computing protonation and redox equilibria in proteins

Cited by 249 publications

References 118 publications

An extended dead‐end elimination algorithm to determine gap‐free lists of low energy states

An extended dead‐end elimination algorithm to determine gap‐free lists of low energy states

Computer Simulation of Protein-Protein Association in Photosynthesis

Calculation of Reduction Potential and p K a

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Calculation of Reduction Potential and p K _a