Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.

• Keywords
• ionizable lipid, lipid nanocarrier, lipid nanoparticle, liposome, molecular simulation, vesicle,
• MeSH
• Pharmaceutical Preparations chemistry   administration & dosage   MeSH
• Drug Delivery Systems * methods   MeSH
• Humans MeSH
• Lipids * chemistry   MeSH
• Nanoparticles chemistry   MeSH
• Drug Carriers * chemistry   MeSH
• Computer Simulation MeSH
• Molecular Dynamics Simulation MeSH
• Machine Learning MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Pharmaceutical Preparations MeSH
• Lipids * MeSH
• Drug Carriers * MeSH

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

• MeSH
• DNA chemistry   MeSH
• Catalysis MeSH
• Nucleic Acid Conformation * MeSH
• Computer Simulation MeSH
• RNA chemistry   MeSH
• Molecular Dynamics Simulation * MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• DNA MeSH
• RNA MeSH

We have carried out a series of extended unbiased molecular dynamics (MD) simulations (up to 10 μs long, ∼162 μs in total) complemented by replica-exchange with the collective variable tempering (RECT) approach for several human telomeric DNA G-quadruplex (GQ) topologies with TTA propeller loops. We used different AMBER DNA force-field variants and also processed simulations by Markov State Model (MSM) analysis. The slow conformational transitions in the propeller loops took place on a scale of a few μs, emphasizing the need for long simulations in studies of GQ dynamics. The propeller loops sampled similar ensembles for all GQ topologies and for all force-field dihedral-potential variants. The outcomes of standard and RECT simulations were consistent and captured similar spectrum of loop conformations. However, the most common crystallographic loop conformation was very unstable with all force-field versions. Although the loss of canonical γ-trans state of the first propeller loop nucleotide could be related to the indispensable bsc0 α/γ dihedral potential, even supporting this particular dihedral by a bias was insufficient to populate the experimentally dominant loop conformation. In conclusion, while our simulations were capable of providing a reasonable albeit not converged sampling of the TTA propeller loop conformational space, the force-field description still remained far from satisfactory.

• MeSH
• DNA chemistry   genetics   metabolism   MeSH
• G-Quadruplexes * MeSH
• Humans MeSH
• Base Sequence MeSH
• Cluster Analysis MeSH
• Molecular Dynamics Simulation * MeSH
• Telomere genetics   MeSH
• Water chemistry   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• DNA MeSH
• Water MeSH

The computer-aided folding of biomolecules, particularly RNAs, is one of the most difficult challenges in computational structural biology. RNA tetraloops are fundamental RNA motifs playing key roles in RNA folding and RNA-RNA and RNA-protein interactions. Although state-of-the-art Molecular Dynamics (MD) force fields correctly describe the native state of these tetraloops as a stable free-energy basin on the microsecond time scale, enhanced sampling techniques reveal that the native state is not the global free energy minimum, suggesting yet unidentified significant imbalances in the force fields. Here, we tested our ability to fold the RNA tetraloops in various force fields and simulation settings. We employed three different enhanced sampling techniques, namely, temperature replica exchange MD (T-REMD), replica exchange with solute tempering (REST2), and well-tempered metadynamics (WT-MetaD). We aimed to separate problems caused by limited sampling from those due to force-field inaccuracies. We found that none of the contemporary force fields is able to correctly describe folding of the 5'-GAGA-3' tetraloop over a range of simulation conditions. We thus aimed to identify which terms of the force field are responsible for this poor description of TL folding. We showed that at least two different imbalances contribute to this behavior, namely, overstabilization of base-phosphate and/or sugar-phosphate interactions and underestimated stability of the hydrogen bonding interaction in base pairing. The first artifact stabilizes the unfolded ensemble, while the second one destabilizes the folded state. The former problem might be partially alleviated by reparametrization of the van der Waals parameters of the phosphate oxygens suggested by Case et al., while in order to overcome the latter effect we suggest local potentials to better capture hydrogen bonding interactions.

• MeSH
• Nucleic Acid Conformation MeSH
• RNA chemistry   metabolism   MeSH
• RNA Folding MeSH
• Molecular Dynamics Simulation * MeSH
• RNA Stability MeSH
• Static Electricity MeSH
• Temperature MeSH
• Hydrogen Bonding MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• RNA MeSH

The utility of molecular dynamics (MD) simulations to model biomolecular structure, dynamics, and interactions has witnessed enormous advances in recent years due to the availability of optimized MD software and access to significant computational power, including GPU multicore computing engines and other specialized hardware. This has led researchers to routinely extend conformational sampling times to the microsecond level and beyond. The extended sampling time has allowed the community not only to converge conformational ensembles through complete sampling but also to discover deficiencies and overcome problems with the force fields. Accuracy of the force fields is a key component, along with sampling, toward being able to generate accurate and stable structures of biopolymers. The Amber force field for nucleic acids has been used extensively since the 1990s, and multiple artifacts have been discovered, corrected, and reassessed by different research groups. We present a direct comparison of two of the most recent and state-of-the-art Amber force field modifications, bsc1 and OL15, that focus on accurate modeling of double-stranded DNA. After extensive MD simulations with five test cases and two different water models, we conclude that both modifications are a remarkable improvement over the previous bsc0 force field. Both force field modifications show better agreement when compared to experimental structures. To ensure convergence, the Drew-Dickerson dodecamer (DDD) system was simulated using 100 independent MD simulations, each extended to at least 10 μs, and the independent MD simulations were concatenated into a single 1 ms long trajectory for each combination of force field and water model. This is significantly beyond the time scale needed to converge the conformational ensemble of the internal portions of a DNA helix absent internal base pair opening. Considering all of the simulations discussed in the current work, the MD simulations performed to assess and validate the current force fields and water models aggregate over 14 ms of simulation time. The results suggest that both the bsc1 and OL15 force fields render average structures that deviate significantly less than 1 Å from the average experimental structures. This can be compared to similar but less exhaustive simulations with the CHARMM 36 force field that aggregate to the ∼90 μs time scale and also perform well but do not produce structures as close to the DDD NMR average structures (with root-mean-square deviations of 1.3 Å) as the newer Amber force fields. On the basis of these analyses, any future research involving double-stranded DNA simulations using the Amber force fields should employ the bsc1 or OL15 modification.

• MeSH
• DNA, B-Form chemistry   MeSH
• DNA chemistry   MeSH
• Nucleic Acid Conformation MeSH
• Magnetic Resonance Spectroscopy MeSH
• Base Pairing MeSH
• Molecular Dynamics Simulation MeSH
• Water chemistry   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• DNA, B-Form MeSH
• DNA MeSH
• Water MeSH

RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM-RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein-RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein-RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for 'MD-adapted structure ensemble' as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein-RNA complexes.

• MeSH
• Protein Conformation MeSH
• Humans MeSH
• Magnetic Resonance Spectroscopy MeSH
• Models, Molecular MeSH
• RNA Recognition Motif genetics   MeSH
• Multiprotein Complexes chemistry   genetics   MeSH
• RNA chemistry   genetics   MeSH
• Amino Acid Sequence genetics   MeSH
• Serine-Arginine Splicing Factors chemistry   genetics   MeSH
• RNA Splicing Factors chemistry   genetics   MeSH
• Molecular Dynamics Simulation MeSH
• Binding Sites MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Multiprotein Complexes MeSH
• RBFOX1 protein, human MeSH Browser
• RNA MeSH
• Serine-Arginine Splicing Factors MeSH
• RNA Splicing Factors MeSH
• SRSF1 protein, human MeSH Browser

We provide theoretical predictions of the intrinsic stability of different arrangements of guanine quadruplex (G-DNA) stems. Most computational studies of nucleic acids have applied Molecular Mechanics (MM) approaches using simple pairwise-additive force fields. The principle limitation of such calculations is the highly approximate nature of the force fields. In this study, we for the first time apply accurate QM computations (DFT-D3 with large atomic orbital basis sets) to essentially complete DNA building blocks, seven different folds of the cation-stabilized two-quartet G-DNA stem, each having more than 250 atoms. The solvent effects are approximated by COSMO continuum solvent. We reveal sizable differences between MM and QM descriptions of relative energies of different G-DNA stems, which apparently reflect approximations of the DNA force field. Using the QM energy data, we propose correction to earlier free energy estimates of relative stabilities of different parallel, hybrid, and antiparallel G-stem folds based on classical simulations. The new energy ranking visibly improves the agreement between theory and experiment. We predict the 5'-anti-anti-3' GpG dinucleotide step to be the most stable one, closely followed by the 5'-syn-anti-3' step. The results are in good agreement with known experimental structures of 2-, 3-, and 4-quartet G-DNA stems. Besides providing specific results for G-DNA, our study highlights basic limitations of force field modeling of nucleic acids. Although QM computations have their own limitations, mainly the lack of conformational sampling and the approximate description of the solvent, they can substantially improve the quality of calculations currently relying exclusively on force fields.

• MeSH
• DNA chemistry   MeSH
• G-Quadruplexes * MeSH
• Guanine chemistry   MeSH
• Quantum Theory * MeSH
• Models, Molecular MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH
• Names of Substances
• DNA MeSH
• Guanine MeSH

We present a refinement of the backbone torsion parameters ε and ζ of the Cornell et al. AMBER force field for DNA simulations. The new parameters, denoted as εζOL1, were derived from quantum-mechanical calculations with inclusion of conformation-dependent solvation effects according to the recently reported methodology (J. Chem. Theory Comput. 2012, 7(9), 2886-2902). The performance of the refined parameters was analyzed by means of extended molecular dynamics (MD) simulations for several representative systems. The results showed that the εζOL1 refinement improves the backbone description of B-DNA double helices and G-DNA stem. In B-DNA simulations, we observed an average increase of the helical twist and narrowing of the major groove, thus achieving better agreement with X-ray and solution NMR data. The balance between populations of BI and BII backbone substates was shifted towards the BII state, in better agreement with ensemble-refined solution experimental results. Furthermore, the refined parameters decreased the backbone RMS deviations in B-DNA MD simulations. In the antiparallel guanine quadruplex (G-DNA) the εζOL1 modification improved the description of non-canonical α/γ backbone substates, which were shown to be coupled to the ε/ζ torsion potential. Thus, the refinement is suggested as a possible alternative to the current ε/ζ torsion potential, which may enable more accurate modeling of nucleic acids. However, long-term testing is recommended before its routine application in DNA simulations.

• Publication type
• Journal Article MeSH