Improvement of RNA Simulations with Torsional Revisions of the AMBER Force Field

Yildirim, Ilyas

doi:10.1007/978-1-4939-9608-7_3

Cited by 2 publications

(2 citation statements)

References 66 publications

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“…In 2016, we proposed a reoptimized set of parameters for Ψ that provided a much improved description for the glycosidic torsion distribution along with a satisfactory description of the pucker distribution . For unmodified RNA, it was reported that incorporation of revised χ and α/γ torsional parameters results in significant improvements in the description of single-stranded RNA tetramers. , Unfortunately, for pseudouridine and its derivatives, the revised glycosidic torsion parameters χ YIL or χ OL3 corresponding to uridine are not applicable. In view of this, the parameter sets for modified RNA residues, developed by Santa Lucia Jr. and co-workers, which are now part of the distribution of the molecular modeling suite AMBER, cannot be used for pseudouridine and its derivatives in combination with the recommended χ OL3 correction.…”

Section: Introductionmentioning

confidence: 99%

Molecular Dynamics Simulation of the Conformational Preferences of Pseudouridine Derivatives: Improving the Distribution in the Glycosidic Torsion Space

Dutta

Sarzyñska

Lahiri

2020

J. Chem. Inf. Model.

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There are only four derivatives of pseudouridine (Ψ) that are known to occur naturally in RNA as post-transcriptional modifications. We have studied the conformational consequences of pseudouridylation and further modifications using replica exchange molecular dynamics simulations at the nucleoside level, and the simulated conformational preferences were compared with the available experimental (NMR) data. We found that the existing AMBER FF99-derived parameters for these nucleosides did not reproduce the observed experimental features and while the recommended bsc0 correction could be combined with these parameters leading to an improvement in the description of sugar pucker distributions, the χOL3 correction could not be applied to these nucleosides as such because of base isomerization. On the other hand, the revised χ torsion parameters (χIDRP) for Ψ developed earlier by us (DebI. Deb, I. J. Comput. Chem.20163715761588) in combination with the AMBER provided parameters and the revised γ torsion parameters generated conformational distributions, which generally were in better agreement with the experimental data. A significant shift of the distribution of base orientation toward the syn conformation was observed with our revised parameter sets compared to the large excess of anti conformation predicted by the FF99 parameters. Overall, our observations indicated that our revised set of parameters (χIDRP) for Ψ were also able to generate conformational distributions for all of the derivatives of Ψ in better agreement with the experimental data.

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Section: Introductionmentioning

confidence: 99%

Molecular Dynamics Simulation of the Conformational Preferences of Pseudouridine Derivatives: Improving the Distribution in the Glycosidic Torsion Space

Dutta

Sarzyñska

Lahiri

2020

J. Chem. Inf. Model.

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“…Over the last few years, AMBER (used also for all the applications shown here) was substantially improved [ 21 ] (i) by refining the backbone and glycosidic torsion parameters [ 65 , 67 , 68 , 69 , 70 , 71 , 72 ]; (ii) by finely tuning the van der Waals parameters of nucleobase atoms [ 73 ]; (iii) by refining electrostatic, torsional, and van der Waals parameters of atoms other than those in (ii) [ 74 , 75 , 76 ]; (iv) by using the advanced water FFs, such as the TIP4P–D water model [ 77 ]; Although this may not be sufficient to significantly improve the performance of the FFs [ 21 ], the choice of water model affects accuracy in the prediction of experimental data such as NMR data [ 78 ]; and (v) by developing accurate nonbonded parameters for hydrogen bonding [ 79 , 80 ], which include induced polarization [ 64 ]. All of these improvements have succeeded in boosting RNA AMBER FF toward a predictive power approaching that of MD proteins [ 64 , 81 ].…”

Section: Targeting Rna Trinucleotide Repeat Expansions: Htt Rna Cagmentioning

confidence: 99%

Role and Perspective of Molecular Simulation-Based Investigation of RNA–Ligand Interaction: From Small Molecules and Peptides to Photoswitchable RNA Binding

et al. 2021

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Aberrant RNA–protein complexes are formed in a variety of diseases. Identifying the ligands that interfere with their formation is a valuable therapeutic strategy. Molecular simulation, validated against experimental data, has recently emerged as a powerful tool to predict both the pose and energetics of such ligands. Thus, the use of molecular simulation may provide insight into aberrant molecular interactions in diseases and, from a drug design perspective, may allow for the employment of less wet lab resources than traditional in vitro compound screening approaches. With regard to basic research questions, molecular simulation can support the understanding of the exact molecular interaction and binding mode. Here, we focus on examples targeting RNA–protein complexes in neurodegenerative diseases and viral infections. These examples illustrate that the strategy is rather general and could be applied to different pharmacologically relevant approaches. We close this study by outlining one of these approaches, namely the light-controllable association of small molecules with RNA, as an emerging approach in RNA-targeting therapy.

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Improvement of RNA Simulations with Torsional Revisions of the AMBER Force Field

Cited by 2 publications

References 66 publications

Molecular Dynamics Simulation of the Conformational Preferences of Pseudouridine Derivatives: Improving the Distribution in the Glycosidic Torsion Space

Molecular Dynamics Simulation of the Conformational Preferences of Pseudouridine Derivatives: Improving the Distribution in the Glycosidic Torsion Space

Role and Perspective of Molecular Simulation-Based Investigation of RNA–Ligand Interaction: From Small Molecules and Peptides to Photoswitchable RNA Binding

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