A universal approach for continuum solvent pK a calculations: are we there yet?

Ho, Junming; Coote, Michelle L.

doi:10.1007/s00214-009-0667-0

Cited by 428 publications

(621 citation statements)

References 121 publications

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“…Thus, the reacting system can be described by a high-level ab initio are gas-phase acidity, Gibbs free energy of deprotonation in solution, Gibbs free energy of solvation for AH, A − and proton species, respectively method and the environment is represented by sites interacting following molecular mechanics force fields, (Kamerlin et al 2009) or even simplified as a dielectric medium (Li et al 2002;Freitas et al 2007;Ho and Coote 2009b;Casasnovas et al 2014). Such calculations are all performed on thermodynamic cycles and, although the free-energy difference between initial and final states is not path dependent, the chosen cycle can determine the predicted pK a accuracy (the physical meaning of this quantity and other thermodynamical ones are described in detail in the next section).…”

Section: A Quantum Mechanical Treatmentmentioning

confidence: 99%

“…Such calculations are all performed on thermodynamic cycles and, although the free-energy difference between initial and final states is not path dependent, the chosen cycle can determine the predicted pK a accuracy (the physical meaning of this quantity and other thermodynamical ones are described in detail in the next section). As discussed by Ho and Coote (2009b), two methods are suitable for pK a predictions: (i) the direct method, and (ii) the proton exchange method.…”

Section: A Quantum Mechanical Treatmentmentioning

confidence: 99%

“…Different thermodynamic cycles can also be derived by inclusion of solvent molecules, (Ho and Coote 2009b;Casasnovas et al 2014) but they do not eliminate the sources of uncertainties. These uncertainties on the solvation-free energies are higher for ionic species when compared with neutral molecules (Ho and Ertem 2016).…”

Section: A Quantum Mechanical Treatmentmentioning

confidence: 99%

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Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems

daSilva

Dias

2017

Biophys Rev

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pH is a critical parameter for biological and technological systems directly related with electrical charges. It can give rise to peculiar electrostatic phenomena, which also makes them more challenging. Due to the quantum nature of the process, involving the forming and breaking of chemical bonds, quantum methods should ideally by employed. Nevertheless, due to the very large number of ionizable sites, different macromolecular conformations, salt conditions, and all other charged species, the CPU time cost simply becomes prohibitive for computer simulations, making this a quite complex problem. Simplified methods based on Monte Carlo sampling have been devised and will be reviewed here, highlighting the updated state-ofthe-art of this field, advantages, and limitations of different theoretical protocols for biomolecular systems (proteins and nucleic acids). Following a historical perspective, the discussion will be associated with the applications to protein interactions with other proteins, polyelectrolytes, and nanoparticles.

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Section: A Quantum Mechanical Treatmentmentioning

confidence: 99%

Section: A Quantum Mechanical Treatmentmentioning

confidence: 99%

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Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems

daSilva

Dias

2017

Biophys Rev

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“…This understanding can be essential for interpretation of experimental values in various systems (Topol et al, 2000;Ho, Coote, 2010).…”

Section: Introductionmentioning

confidence: 98%

“…There are several experimental methods for determining the acidity constants in aqueous solutions for example, conductometry, spectrophotometric, capillary electrophoresis, calorimetric adsorption, potentiometric titration, HPLC, solubility, partition and distribution (Reijenga et al, 2013;Heinze, 1984;Thurlkill et al, 2005;Santos et al, 2010). In addition to experimental methods, theoretical prediction of the pKa values has received considerable attention and many studies have been carried out on this topic in recent years (Kelly, Cramer, Truhlar, 2006;Ho, Coote, 2010).…”

Section: Introductionmentioning

confidence: 99%

Theoretically nanoscale study on ionization of muscimol nano drug in aqueous solution

Kiani

Abbaszadeh

Pousti

et al. 2015

Braz. J. Pharm. Sci.

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In the present work, acid dissociation constant (pK a ) values of muscimol derivatives were calculated using the Density Functional Theory (DFT) method. In this regard, free energy values of neutral, protonated and deprotonated species of muscimol were calculated in water at the B3LYP/6-31G(d) basis sets. The hydrogen bond formation of all species had been analyzed using the Tomasi's method. It was revealed that the theoretically calculated pK a values were in a good agreement with the existing experimental pK a values, which were determined from capillary electrophoresis, potentiometric titration and UV-visible spectrophotometric measurements.Uniterms: Nanodrug. Muscimol. Acid/dissociation constants. Computational chemistry. Density Functional Theory.No presente trabalho, calculou-se a constante de dissociação do ácido (pK a ) dos derivados de muscimol, utilizando-se o método da teoria do funcional de densidade (DFT). Com esse objetivo, calcularam-se os valores das espécies neutra, protonada e desprotonada do muscimol em água em base B3LYP/6-31G(d). A formação da ligação de hidrogênio de todas as espécies foi analisada utilizando o método de Tomasi. Demonstrou-se que os valores de pKa calculados teoricamente estavam em boa concordância com os valores experimentais disponíveis, determinados por eletroforese capilar, titulação potenciométrica e medidas por espectrofotometria UV-visível.Unitermos: Nanofármaco. Muscimol. Ácido/constantes de dissociação. Química computacional. Teoria do funcional de densidade.

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Predictive Modeling of Molecular Properties: Can We Go beyond Interpretation?

Clark

2011

Modeling of Molecular Properties

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Truly predictive modeling is a rarity in chemistry and biology. This is true for both explicit calculational techniques (quantum chemistry, force fields) and for implicit methods such as quantitative structure-property relationship (QSPR) models and other interpolation techniques. It is true that, for sufficiently small molecules for which a single-determinant Hartree-Fock wavefunction provides a good description, CCSD(T) [1, 2] calculations using an adequate basis set produce gas-phase results that usually rival or better experimental accuracy. This is very positive but of limited use in the impure, finite-temperature condensed-phase world in which many important processes take place. The automobile industry is used to a situation in which the results of crash simulations agree very closely with experimental crash testsso much so that the latter no longer form part of the design process. The fields of chemistry and biology, however, are a very long way from this idyllic situation. This is perhaps surprising, because the physics behind the processes and the systems considered is believed to be well known, such that their accurate modeling should be possible. This aim of this chapter is to analyze the current situation, to identify weaknesses and opportunities in chemical and life-science modeling, and maybe even to suggest some improvements in what can be done. The first stage, however, is to consider the nature of both models and modeling. Models and ModelingModels are exactly that. Unlike CCSDT, they are not an accurate and defined truncation of a physically exact theory, but are rather a simplified representation of a complex object that is intended to behave like the object itself. Behave is a key concept here. It is well known to the multiscale community [3] that a coarse-grain version of a more complex force field can only reproduce a limited set of the Modeling of Molecular Properties, First Edition. Edited by Peter Comba.

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A universal approach for continuum solvent pK a calculations: are we there yet?

Cited by 428 publications

References 121 publications

Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems

Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems

Theoretically nanoscale study on ionization of muscimol nano drug in aqueous solution

Predictive Modeling of Molecular Properties: Can We Go beyond Interpretation?

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