With current advancements in RNA based therapeutics, it is becoming crucial to utilize theoretical and computational methods to describe properly the physical properties of RNA molecules. NMR and X-ray crystallography are two powerful techniques for investigating structural properties. However, if the RNA molecules are complex or dynamic, these methods might not be adequate. For computational approaches, the quality of the force field will determine accuracy of our predictions. In this contribution, we revise the α/γ torsional parameters of RNA for amber force field using a model system representing an RNA dimer backbone. Combined with revised χ torsional parameters, previously shown to improve computational predictions, we benchmarked the revised force field on five single-stranded RNA (ssRNA) tetramers, three RNA dodecamer duplexes, and an RNA hairpin. A total of 60 μs of molecular dynamics (MD) simulations were run. We also employ the discrete path sampling (DPS) approach to compare the predictions for the revised amber force field with those for amber10. Our results indicate that the unphysical states observed with amber10 in ssRNA MD simulations are suppressed for the revised amber force field. In line with NMR experimental observations, incorporation of the revised α/γ and χ torsional parameters leads to A-form-like conformational states as the most favorable ssRNA tetramer conformations. Furthermore, the revised force field maintains the A-form geometry in regular RNA duplexes. Our revised amber force field for RNA should therefore improve structural and thermodynamic predictions for challenging RNA systems.
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Langmuir
January 2025
John A. Reif, Jr. Department of Civil and Environmental Engineering, New Jersey Institute of Technology, 323 Martin Luther King Blvd., Newark, New Jersey 07102, United States.
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View Article and Find Full Text PDFAcc Chem Res
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School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
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View Article and Find Full Text PDFJ Chem Phys
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School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, United Kingdom.
Membrane properties are determined in part by lipid composition, and cholesterol plays a large role in determining these properties. Cellular membranes show a diverse range of cholesterol compositions, the effects of which include alterations to cellular biomechanics, lipid raft formation, membrane fusion, signaling pathways, metabolism, pharmaceutical therapeutic efficacy, and disease onset. In addition, cholesterol plays an important role in non-cellular membranes, with its concentration in the skin lipid matrix being implicated in several skin diseases.
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View Article and Find Full Text PDFInnovation (Camb)
January 2025
AIM Center, College of Life Sciences and Technology, Beijing University of Chemical Technology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Predicting free energy changes (ΔΔG) is essential for enhancing our understanding of protein evolution and plays a pivotal role in protein engineering and pharmaceutical development. While traditional methods offer valuable insights, they are often constrained by computational speed and reliance on biased training datasets. These constraints become particularly evident when aiming for accurate ΔΔG predictions across a diverse array of protein sequences.
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