Novel US-CpHMD Protocol to Study the Protonation-Dependent Mechanism of the ATP/ADP Carrier

Oliveira, Nuno F. B.; Machuqueiro, Miguel

doi:10.1021/acs.jcim.2c00233

Cited by 13 publications

(11 citation statements)

References 99 publications

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“…Typically, there is a particular pH at which biological activity, macromolecular stability, and binding are best optimized, termed pH-optimum [ 18 ]. The pH-dependence originates from the pKa values of the ionizable groups, both ionizable amino acids and nucleic acids, and thus indicates the importance of assigning correct protonation states before any modeling or introducing of pH in molecular dynamics simulations (constant-pH MD [ 19 , 20 , 21 , 22 , 23 ]). Below, we outline recent contributions to modeling pH-dependent phenomena.…”

Section: Electrostatics Of Wild-type Biological Macromoleculesmentioning

confidence: 99%

“…The pH-optimum is the particular pH at which biological activity, macromolecular stability, and binding are best optimized [ 18 ]. It originates from the pKa values of the ionizable groups, indicating the importance of assigning correct protonation states in molecular dynamics simulations [ 19 , 20 , 21 , 22 , 23 ]. Recent contributions to modeling pH-dependent phenomena are shown in Section 2.3 .…”

Section: Introductionmentioning

confidence: 99%

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Electrostatics in Computational Biophysics and Its Implications for Disease Effects

Sun

Poudel

Alexov

et al. 2022

IJMS

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This review outlines the role of electrostatics in computational molecular biophysics and its implication in altering wild-type characteristics of biological macromolecules, and thus the contribution of electrostatics to disease mechanisms. The work is not intended to review existing computational approaches or to propose further developments. Instead, it summarizes the outcomes of relevant studies and provides a generalized classification of major mechanisms that involve electrostatic effects in both wild-type and mutant biological macromolecules. It emphasizes the complex role of electrostatics in molecular biophysics, such that the long range of electrostatic interactions causes them to dominate all other forces at distances larger than several Angstroms, while at the same time, the alteration of short-range wild-type electrostatic pairwise interactions can have pronounced effects as well. Because of this dual nature of electrostatic interactions, being dominant at long-range and being very specific at short-range, their implications for wild-type structure and function are quite pronounced. Therefore, any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could be the dominant factor contributing to pathogenicity. However, we also outline that due to the plasticity of biological macromolecules, the effect of amino acid mutation may be reduced, and thus a charge deletion or insertion may not necessarily be deleterious.

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Section: Electrostatics Of Wild-type Biological Macromoleculesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Electrostatics in Computational Biophysics and Its Implications for Disease Effects

Sun

Poudel

Alexov

et al. 2022

IJMS

View full text Add to dashboard Cite

show abstract

“…and its level of detail (all-atom, united-atom, and coarse grain); and (iii) the approximations used to deal with charge fluctuations in the simulation box, often related with the use of counterions and the long-range electrostatics treatment (reaction-field vs Ewald summation methods). In discrete CpHMD methods, ,,,− ,,,,− ,− , continuum electrostatics calculations are used to estimate the energies for the Monte Carlo (MC) move while the MD simulations are run in either implicit or fully explicit solvent. The most recent continuous CpHMD methods are based on the λ-dynamics approach for free-energy calculations, where an individual λ variable is assigned to each titratable site of the protein. ,− ,− ,,,− , All protonation states coordinates vary continuously between 0 and 1, representing the protonated and deprotonated states, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…However, these pH effects are often ignored in molecular dynamics (MD) simulations due to the difficulty of sampling correct protonation states. Over the last 28 years, many constant-pH MD (CpHMD) methods have been developed to address these limitations. − The different strategies employed can be distinguished mainly by (i) the type of protonation (continuous vs discrete); (ii) the force field (AMBER, CHARMM, GROMOS, OPLS, MARTINI, etc.) and its level of detail (all-atom, united-atom, and coarse grain); and (iii) the approximations used to deal with charge fluctuations in the simulation box, often related with the use of counterions and the long-range electrostatics treatment (reaction-field vs Ewald summation methods).…”

Section: Introductionmentioning

confidence: 99%

Extending the Stochastic Titration CpHMD to CHARMM36m

et al. 2022

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The impact of pH on proteins is significant but often neglected in molecular dynamics simulations. Constant-pH Molecular Dynamics (CpHMD) is the state-of-the-art methodology to deal with these effects. However, it still lacks widespread adoption by the scientific community. The stochastic titration CpHMD is one of such methods that, until now, only supported the GROMOS force field family. Here, we extend this method's implementation to include the CHARMM36m force field available in the GROMACS software package. We test this new implementation with a diverse group of proteins, namely, lysozyme, Staphylococcal nuclease, and human and E. coli thioredoxins. All proteins were conformationally stable in the simulations, even at extreme pH values. The RMSE values (pK a prediction vs experimental) obtained were very encouraging, in particular for lysozyme and human thioredoxin. We have also identified a few residues that challenged the CpHMD simulations, highlighting scenarios where the method still needs improvement independently of the force field. The CHARMM36m all-atom implementation was more computationally efficient when compared with the GROMOS 54A7, taking advantage of a shorter nonbonded interaction cutoff and a less frequent neighboring list update. The new extension will allow the study of pH effects in many systems for which this force field is particularly suited, i.e., proteins, membrane proteins, lipid bilayers, and nucleic acids.

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“…Several studies focused on the structural stability, , (de-)insertion kinetics, possible metastable states, and electrostatic interactions modulating the pH dependency. ,,, Most of them used 2-oleoyl-1-palmitoyl- sn -glycero-3-phosphocholine (POPC) membrane bilayers to mimic liposomal conditions, such as ionic strength, pH, and peptide state. ,, Particularly, constant-pH molecular dynamics (CpHMD) simulations are helpful, as the residues are titrating at specific pH values, allowing the conformational and protonation sampling to be coupled. These methods may treat the protonation either as discrete ,,− or continuous. − Consequently, they promote the study of complex peptide–membrane configurations and the impact of the key titrating residues positioning along the membrane normal on helical (un)folding and side-chain interactions. The electrostatic environment around the key aspartate residues changes with the peptide movement, favoring either insertion or exiting processes through protonation or deprotonation events, respectively.…”

Section: Introductionmentioning

confidence: 99%

Increasing the Realism of in Silico pHLIP Peptide Models with a Novel pH Gradient CpHMD Method

Silva

Vila-Viçosa

Machuqueiro

2022

J. Chem. Theory Comput.

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The pH-low insertion peptides (pHLIP) are pH-dependent membrane inserting peptides, whose function depends on the cell microenvironment acidity. Several peptide variants have been designed to improve upon the wt-sequence, particularly the state transition kinetics and the selectivity for tumor pH. The variant 3 (Var3) peptide is a 27 residue long peptide, with a key titrating residue (Asp-13) that, despite showing a modest performance in liposomes (pK ins ∼ 5.0), excelled in tumor cell experiments. To help rationalize these results, we focused on the pH gradient in the cell membrane, which is one of the crucial properties that are not present in liposomes. We extended our CpHMD-L method and its pH replica-exchange (pHRE) implementation to include a pH gradient and mimic the pHLIP-membrane microenvironment in a cell where the internal pH is fixed (pH 7.2) and the external pH is allowed to change. We showed that, by properly modeling the pH-gradient, we can correctly predict the experimentally observed loss and gain of performance in tumor cells experiments by the wt and Var3 sequences, respectively. In sum, the pH gradient implementation allowed for more accurate and realistic pK a estimations and was a pivotal step in bridging the in silico data and the in vivo cell experiments.

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Novel US-CpHMD Protocol to Study the Protonation-Dependent Mechanism of the ATP/ADP Carrier

Cited by 13 publications

References 99 publications

Electrostatics in Computational Biophysics and Its Implications for Disease Effects

Electrostatics in Computational Biophysics and Its Implications for Disease Effects

Extending the Stochastic Titration CpHMD to CHARMM36m

Increasing the Realism of in Silico pHLIP Peptide Models with a Novel pH Gradient CpHMD Method

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