Gallic acid improves color quality and stability of red wine via physico-chemical interaction and chemical transformation as revealed by thermodynamics, real wine dynamics and benchmark quantum mechanical calculations.

The aim of this study was to explore the copigmentation effect of gallic acid on red wine color and to dissect its mechanism at the molecular level. Three-dimensional studies, e.g., in model wine, in real wine and in silico, and multiple indicators, e.g., color, spectrum, thermodynamics and phenolic dynamics, were employed. The results showed that gallic acid significantly enhanced the color quality and stability of red wine. Physico-chemical interactions and chemical transformations should be the most likely mechanism, and physico-chemical interactions are also a prerequisite for chemical transformations. QM calculations of the physico-chemical interactions proved that the binding between gallic acid and malvidin-3-O-glucoside is a spontaneous exothermic reaction driven by hydrogen bonding and dispersion forces. The sugar moiety of malvidin-3-O-glucoside and the phenolic hydroxyl groups of gallic acid affect the formation of hydrogen bonds, while the dispersion interaction was related to the stacking of the molecular skeleton.

[Development of Membrane Permeability Coefficient by Means of Novel Molecular Dynamics Methods].

The membrane permeability, and its evaluation, is crucial factor in the process of uptake of compounds from outside to inside the cell and in the inhibition of the activity of disease-causing target proteins. Although molecular dynamics (MD) simulations have been shown to be able to reproduce the conformational changes of compounds occurring during membrane permeation, it is still challenging to extract the membrane permeability at an affordable computational workload solely by conventional MD. Indeed, the time scale accessible by MD is far below the one characterizing the actual permeation process. Phenomena occurring in living organisms escaping the reach of standard MD are generally referred to as biological rare events, and the membrane permeation process is one of them. To overcome this time-scale problem, several enhanced sampling methods have been proposed over the years to improve conformational sampling. In this review, a hybrid sampling method that combines the parallel cascade selection MD (PaCS-MD) and the outlier flooding method (OFLOOD), introduced and developed by our group, is proposed as a tool to study the membrane permeation from structural sampling (rare-event sampling). The obtained trajectories are used to estimate the free energy profiles for the membrane permeation and to compute the membrane permeation coefficients. Moreover, we present an example of application of the free energy reaction network method as a versatile way for incorporating explicitly into reaction coordinates the degrees of freedom related to internal motion.

New methods for resolution of hydroxychloroquine by forming diastereomeric salt and adding chiral mobile phase agent on RP-HPLC.

Hydroxychloroquine (HCQ), 2-([4-([7-Chloro-4-quinolyl]amino)pentyl]ethylamino)ethanol, exhibited significant biological activity, while its side effects cannot be overlooked. The RP-HPLC enantio-separation was investigated for cost-effective and convenient optical purity analysis of HCQ. The thermodynamic resolution of Rac-HCQ, driven by enthalpy and entropy, was achieved on the C18 column using Carboxymethyl-ß-cyclodextrin (CM-ß-CD) as the chiral mobile phase agent (CMPA). The effects of CCM-ß-CD, pH, and triethylamine (TEA) V% on the enantio-separation process were explored. Under the optimum conditions at 24°C, the retention times for the two enantiomers were t R 1 = 29.39 min $$ {t}_{R1}=29.39\ \min $$ and t R 2 = 32.42 min $$ {t}_{R2}=32.42\ \min $$ , resulting in R s = 1.87 $$ {R}_s=1.87 $$ . The resolution via diastereomeric salt formation of Rac-HCQ was developed to obtain the active pharmaceutical ingredient of single enantiomer S-HCQ. Di-p-Anisoyl-L-Tartaric Acid (L-DATA) was proved effective as the resolution agent for Rac-HCQ. Surprisingly, it was found that refluxing time was a key fact affecting the resolution efficiency, which meant the kinetic dominate during the process of the resolution. Four factors-solvent volume, refluxing time, filtration temperature, and molar ratio-were optimized using the single-factor method and the response surface method. Two cubic models were established, and the reliability was subsequently verified. Under the optimal conditions, the less soluble salt of 2L-DATA:S-HCQ was obtained with a yield of 96.9% and optical purity of 63.0%. The optical purity of this less soluble salt increases to 99.0% with a yield of 74.2% after three rounds recrystallization.

Biosorption of arsenic (III) from aqueous solution using calcium alginate immobilized dead biomass of Acinetobacter sp. strain Sp2b.

This study presents a novel biosorbent developed by immobilizing dead Sp2b bacterial biomass into calcium alginate (CASp2b) to efficiently remove arsenic (AsIII) from contaminated water. The bacterium Sp2b was isolated from arsenic-contaminated industrial soil of Punjab, a state in India. The strain was designated Acinetobacter sp. strain Sp2b as per the 16S rDNA sequencing, GenBank accession number -OP010048.The CASp2b was used for the biosorption studies after an initial screening for the biosorption capacity of Sp2b biomass with immobilized biomass in both live and dead states. The optimum biosorption conditions were examined in batch experimentations with contact time, pH, biomass, temperature, and AsIII concentration variables. The maximum biosorption capacity (qmax = 20.1 ± 0.76 mg/g of CA Sp2b) was obtained at pH9, 35 ̊ C, 20 min contact time, and 120 rpm agitation speed. The isotherm, kinetic and thermodynamic modeling of the experimental data favored Freundlich isotherm (R2 = 0.941) and pseudo-2nd-order kinetics (R2 = 0.968) with endothermic nature (ΔH° = 27.42) and high randomness (ΔS° = 58.1).The scanning electron microscopy with energy dispersive X-ray (SEM-EDX) analysis indicated the As surface binding. The reusability study revealed the reasonable usage of beads up to 5 cycles. In conclusion, CASp2b is a promising, efficient, eco-friendly biosorbent for AsIII removal from contaminated water.

HSPiP, Computational, and Thermodynamic Model-Based Optimized Solvents for Subcutaneous Delivery of Tolterodine Tartrate and GastroPlus-Based In Vivo Prediction in Humans: Part I.

Tolterodine tartrate (TOTA) is associated with adverse effect, high hepatic access, varied bioavailability, slight aqueous solubility, and short half-life after oral delivery. Hansen solubility parameters (HSP, HSPiP program), experimental solubility (T = 298.2 to 318.2 K and p = 0.1 MPa), computational (van't Hoff and Apelblat models), and thermodynamic models were used to the select solvent(s). HSPiP predicted PEG400 as the most suitable co-solvent based on HSP values (δd = 17.88, δp = 4.0, and δh = 8.8 of PEG400) and comparable to the drug (δd = 17.6, δp = 2.4, and δh = 4.6 of TOTA). The experimental mole fraction solubility of TOTA was maximum (xe = 0.0852) in PEG400 confirming the best fit of the prediction. The observed highest solubility was attributed to the δp and δh interacting forces. The activity coefficient (ϒi) was found to be increased with temperature. The higher values of r2 (linear regression coefficient) and low RMSD (root mean square deviation) indicated a good correlation between the generated "xe" data for crystalline TOTA and the explored models (modified Apelblat and van't Hoff models). TOTA solubility in "PEG400 + water mixture" was endothermic and entropy-driven. IR (immediate release product) formulation can be tailored using 60% PEG400 in buffer solution for 2 mg of TOTA in 0.25 mL (dosing volume). The isotonic binary solution was associated with a pH of 7.2 suitable for sub-Q delivery. The approach would be a promising alternative with ease of delivery to children and aged patients.

Studying protein stability in crowded environments by NMR.

Most proteins perform their functions in crowded and complex cellular environments where weak interactions are ubiquitous between biomolecules. These complex environments can modulate the protein folding energy landscape and hence affect protein stability. NMR is a nondestructive and effective method to quantify the kinetics and equilibrium thermodynamic stability of proteins at an atomic level within crowded environments and living cells. Here, we review NMR methods that can be used to measure protein stability, as well as findings of studies on protein stability in crowded environments mimicked by polymer and protein crowders and in living cells. The important effects of chemical interactions on protein stability are highlighted and compared to spatial excluded volume effects.

Protein Interface Regulating the Inserting Process of Imidazole Ionic Liquids into the Cell Membrane.

Ionic liquids (ILs) have shown promising potential in membrane protein extraction; however, the underlying mechanism remains unclear. Herein, we employed GPU-accelerated molecular dynamics (MD) simulations to investigate the dynamic insertion process of ILs into cell membranes containing membrane proteins. Our findings reveal that ILs spontaneously insert into the membrane, and the presence of membrane proteins significantly decelerates the rate of IL insertion into the membrane. Specifically, the relationship between the insertion rate and inserting free energy exhibits non-monotonic changes, which can be attributed to interfacial effects. The protein-water interface acts as trap for free ions and ionic clusters, while free ions preferentially insert into the membrane from the protein-lipid interface, which limits the insertion rate due to its narrowness. Thus, the insertion rate is governed by a combination of the free energy and interfacial effects. These findings provide valuable insights into the interfacial effects of protein-lipid bilayers and have implications for various biochemical-related applications.

Prediction of 3D RNA Structures from Sequence Using Energy Landscapes of RNA Dimers: Application to RNA Tetraloops.

Access to the three-dimensional structure of RNA enables an ability to gain a more profound understanding of its biological mechanisms, as well as the ability to design RNA-targeting drugs, which can take advantage of the unique chemical environment imposed by a folded RNA structure. Due to the dynamic and structurally complex properties of RNA, both experimental and traditional computational methods have difficulty in determining RNA's 3D structure. Herein, we introduce TAPERSS (Theoretical Analyses, Prediction, and Evaluation of RNA Structures from Sequence), a physics-based fragment assembly method for predicting 3D RNA structures from sequence. Using a fragment library created using discrete path sampling calculations of RNA dinucleoside monophosphates, TAPERSS can sample the physics-based energy landscapes of any RNA sequence with relatively low computational complexity. We have benchmarked TAPERSS on 21 RNA tetraloops, using a combinatorial algorithm as a proof-of-concept. We show that TAPERSS was successfully able to predict the apo-state structures of all 21 RNA hairpins, with 16 of those structures also having low predicted energies as well. We demonstrate that TAPERSS performs most accurately on GNRA-like tetraloops with mostly stacked loop-nucleotides, while having limited success with more dynamic UNCG and CUYG tetraloops, most likely due to the influence of the RNA force field used to create the fragment library. Moreover, we show that TAPERSS can successfully predict the majority of the experimental non-apo states, highlighting its potential in anticipating biologically significant yet unobserved states. This holds great promise for future applications in drug design and related studies. With discussed improvements and implementation of more efficient sampling algorithms, we believe TAPERSS may serve as a useful tool for a physics-based conformational sampling of large RNA structures.

Exploring Biomolecular Conformational Dynamics with Polarizable Force Field AMOEBA and Enhanced Sampling Method Milestoning.

Conformational dynamics play a crucial role in determining the behavior of the biomolecules. Polarizable force fields, such as AMOEBA, can accurately capture electrostatic interactions underlying the conformational space. However, applying a polarizable force field in molecular dynamics (MD) simulations can be computationally expensive, especially in studying long-time-scale dynamics. To overcome this challenge, we incorporated the AMOEBA potential with Milestoning, an enhanced sampling method in this work. This integration allows us to efficiently sample the rare and important conformational states of a biomolecule by using many short and independent molecular dynamics trajectories with the AMOEBA force field. We applied this method to investigate the conformational dynamics of alanine dipeptide, DNA, and RNA A-B form conversion. Well-converged thermodynamic and kinetic properties were obtained, including the free energy difference, mean first passage time, and critical transitions between states. Our results demonstrate the power of integrating polarizable force fields with enhanced sampling methods in quantifying the thermodynamic and kinetic properties of biomolecules at the atomic level.

Carbonic Anhydrases: Different Active Sites, Same Metal Selectivity Rules.

Carbonic anhydrases are mononuclear metalloenzymes catalyzing the reversible hydration of carbon dioxide in organisms belonging to all three domains of life. Although the mechanism of the catalytic reaction is similar, different families of carbonic anhydrases do not have a common ancestor nor do they exhibit significant resemblance in the amino acid sequence or the structure and composition of the metal-binding sites. Little is known about the physical principles determining the metal affinity and selectivity of the catalytic centers, and how well the native metal is protected from being dislodged by other metal species from the local environment. Here, we endeavor to shed light on these issues by studying (via a combination of density functional theory calculations and polarizable continuum model computations) the thermodynamic outcome of the competition between the native metal cation and its noncognate competitor in various metal-binding sites. Typical representatives of the competing cations from the cellular environments of the respective classes of carbonic anhydrases are considered. The calculations reveal how the Gibbs energy of the metal competition changes when varying the metal type, structure, composition, and solvent exposure of the active center. Physical principles governing metal competition in different carbonic anhydrase metal-binding sites are delineated.

Theoretical Study of Cyanidin-Resveratrol Copigmentation by the Functional Density Theory.

Anthocyanins are colored water-soluble plant pigments. Upon consumption, anthocyanins are quickly absorbed and can penetrate the blood-brain barrier (BBB). Research based on population studies suggests that including anthocyanin-rich sources in the diet lowers the risk of neurodegenerative diseases. The copigmentation caused by copigments is considered an effective way to stabilize anthocyanins against adverse environmental conditions. This is attributed to the covalent and noncovalent interactions between colored forms of anthocyanins (flavylium ions and quinoidal bases) and colorless or pale-yellow organic molecules (copigments). The present work carried out a theoretical study of the copigmentation process between cyanidin and resveratrol (CINRES). We used three levels of density functional theory: M06-2x/6-31g+(d,p) (d3bj); ωB97X-D/6-31+(d,p); APFD/6-31+(d,p), implemented in the Gaussian16W package. In a vacuum, the CINRES was found at a copigmentation distance of 3.54 Å between cyanidin and resveratrol. In water, a binding free energy ∆G was calculated, rendering -3.31, -1.68, and -6.91 kcal/mol, at M06-2x/6-31g+(d,p) (d3bj), ωB97X-D/6-31+(d,p), and APFD/6-31+(d,p) levels of theory, respectively. A time-dependent density functional theory (TD-DFT) was used to calculate the UV spectra of the complexes and then compared to its parent molecules, resulting in a lower energy gap at forming complexes. Excited states' properties were analyzed with the ωB97X-D functional. Finally, Shannon aromaticity indices were calculated and isosurfaces of non-covalent interactions were evaluated.

Exploring the Potential of Biochar Derived from Chinese Herbal Medicine Residue for Efficient Removal of Norfloxacin.

One-step carbonization was explored to prepare biochar using the residue of a traditional Chinese herbal medicine, Atropa belladonna L. (ABL), as the raw material. The resulting biochar, known as ABLB4, was evaluated for its potential as a sustainable material for norfloxacin (NOR) adsorption in water. Subsequently, a comprehensive analysis of adsorption isotherms, kinetics, and thermodynamics was conducted through batch adsorption experiments. The maximum calculated NOR adsorption capacity was 252.0 mg/g at 298 K, and the spontaneous and exothermic adsorption of NOR on ABLB4 could be better suited to a pseudo-first-order kinetic model and Langmuir model. The adsorption process observed is influenced by pore diffusion, π-π interaction, electrostatic interaction, and hydrogen bonding between ABLB4 and NOR molecules. Moreover, the utilization of response surface modeling (RSM) facilitated the optimization of the removal efficiency of NOR, yielding a maximum removal rate of 97.4% at a temperature of 304.8 K, an initial concentration of 67.1 mg/L, and a pH of 7.4. Furthermore, the biochar demonstrated favorable economic advantages, with a payback of 852.5 USD/t. More importantly, even after undergoing five cycles, ABLB4 exhibited a consistently high NOR removal rate, indicating its significant potential for application in NOR adsorption.

Energy condensation and dipole alignment in protein dynamics.

The possibility that distant biomolecules in a cell interact via electromagnetic (e.m.) radiation was proposed many years ago to explain the high rate of encounters of partners in some enzymatic reactions. The results of two recent experiments designed to test the propensity of protein bovine serum albumin (BSA) to interact via e.m. radiation with other proteins were interpreted in a theoretical framework based on three main assumptions: (i) in order to experience this kind of interaction the protein must be in an out-of-equilibrium state; (ii) in this state there is a condensation of energy in low-frequency vibrational modes; and (iii) the hydration layers of water around the protein sustain the energy condensation. In the present paper we present the results of molecular dynamics simulations of BSA in four states: at equilibrium and out-of-equilibrium in water, and at room and high temperature in vacuum. By comparing physical properties of the system in the four states, our simulations provide a qualitative and quantitative assessment of the three assumptions on which the theoretical framework is based. Our results confirm the assumptions of the theoretical model showing energy condensation at low frequency and electretlike alignment between the protein's and the water's dipoles; they also allow a quantitative estimate of the contribution of the out-of-equilibrium state and of the water to the observed behavior of the protein. In particular, it has been found that in the out-of-equilibrium state the amplitude of the oscillation of the protein's dipole moment greatly increases, thereby enhancing a possible absorption or emission of e.m. radiation. The analysis of BSA's dynamics outlined in the present paper provides a procedure for checking the propensity of a biomolecule to interact via e.m. radiation with its biochemical partners.

Probing the energy barriers and stages of membrane protein unfolding using solid-state NMR spectroscopy.

Understanding how the amino acid sequence dictates protein structure and defines its stability is a fundamental problem in molecular biology. It is especially challenging for membrane proteins that reside in the complex environment of a lipid bilayer. Here, we obtain an atomic-level picture of the thermally induced unfolding of a membrane-embedded α-helical protein, human aquaporin 1, using solid-state nuclear magnetic resonance spectroscopy. Our data reveal the hierarchical two-step pathway that begins with unfolding of a structured extracellular loop and proceeds to an intermediate state with a native-like helical packing. In the second step, the transmembrane domain unravels as a single unit, resulting in a heterogeneous misfolded state with high helical content but with nonnative helical packing. Our results show the importance of loops for the kinetic stabilization of the whole membrane protein structure and support the three-stage membrane protein folding model.

Deep learning path-like collective variable for enhanced sampling molecular dynamics.

Several enhanced sampling techniques rely on the definition of collective variables to effectively explore free energy landscapes. The existing variables that describe the progression along a reactive pathway offer an elegant solution but face a number of limitations. In this paper, we address these challenges by introducing a new path-like collective variable called the "deep-locally non-linear-embedding," which is inspired by principles of the locally linear embedding technique and is trained on a reactive trajectory. The variable mimics the ideal reaction coordinate by automatically generating a non-linear combination of features through a differentiable generalized autoencoder that combines a neural network with a continuous k-nearest neighbor selection. Among the key advantages of this method is its capability to automatically choose the metric for searching neighbors and to learn the path from state A to state B without the need to handpick landmarks a priori. We demonstrate the effectiveness of DeepLNE by showing that the progression along the path variable closely approximates the ideal reaction coordinate in toy models, such as the Müller-Brown potential and alanine dipeptide. Then, we use it in the molecular dynamics simulations of an RNA tetraloop, where we highlight its capability to accelerate transitions and estimate the free energy of folding.

Photobiomodulation on isolated mitochondria at 810 nm: first results on the efficiency of the energy conversion process.

In this paper the photobiomodulation on isolated mitochondria of bovine liver is studied as a thermodynamic process of conversion of energy. This analysis is conducted by considering a particular set-up for the photobiomodulation experiments of interest. It allows, in particular, the computation of the electromagnetic field and the related energetic quantities in the stimulated organelles. The measurements of the excess of biochemical power density produced by the illuminated mitochondria are performed at regular time intervals after the experiments. The calculations and the measurements finally allow us to obtain the first results on the efficiency of the process of conversion of electromagnetic energy into excess of biochemical energy released by the isolated organelles.

Electrostatics introduce a trade-off between mesophilic stability and adaptation in halophilic proteins.

Extremophile organisms have adapted to extreme physicochemical conditions. Halophilic organisms, in particular, survive at very high salt concentrations. To achieve this, they have engineered the surface of their proteins to increase the number of short, polar and acidic amino acids, while decreasing large, hydrophobic and basic residues. While these adaptations initially decrease protein stability in the absence of salt, they grant halophilic proteins remarkable stability in environments with extremely high salt concentrations, where non-adapted proteins unfold and aggregate. The molecular mechanisms by which halophilic proteins achieve this, however, are not yet clear. Here, we test the hypothesis that the halophilic amino acid composition destabilizes the surface of the protein, but in exchange improves the stability in the presence of salts. To do that, we have measured the folding thermodynamics of various protein variants with different degrees of halophilicity in the absence and presence of different salts, and at different pH values to tune the ionization state of the acidic amino acids. Our results show that halophilic amino acids decrease the stability of halophilic proteins under mesophilic conditions, but in exchange improve salt-induced stabilization and solubility. We also find that, in contrast to traditional assumptions, contributions arising from hydrophobic effect and preferential ion exclusion are more relevant for haloadaptation than electrostatics. Overall, our findings suggest a trade-off between folding thermodynamics and halophilic adaptation to optimize proteins for hypersaline environments.

Thermodynamic and structural investigation of oily wastewater treatment using peach kernel and walnut shell based activated carbon.

Despite the many articles about activated carbon with different precursors in adsorption process, no in-depth research has been carried out to understand the causes of the difference in surface adsorption characteristics of activated carbon with different precursors and different activation processes. In this work, the ability of two active carbon adsorbents made of walnut shell and peach kernel by two chemical and physical methods (totally 4 different types of activated carbon) in treatment of oily wastewater including diesel, gasoline, used oil or engine lubricant has been compared. The results show that the chemical activated peach carbon active with 97% hardness has provided the highest hardness and physical activated walnut carbon active has obtained the lowest hardness value (87%). It is also found that peach activated carbon has a higher iodine number than walnut activated carbon, and this amount can be increased using chemical methods; Therefore, the highest amount of Iodine Number is related to Peach activated carbon that is made by chemical method (1230 mg/g), and the lowest amount of iodine number is seen in walnut activated carbon that is made by physical method (1020 mg/g). moreover, the pore diameter of physical activated carbon is lower than chemical activated carbon in all cases. So that the pore diameter of chemical activated peach carbon active is equal to 22.08 µm and the measured pore diameter of physical activated peach carbon active is equal to 20.42 µm. These values for walnut are obtained as 22.74 µm and 21.86 µm, respectively. Furthermore, the temperature and pH effects on the adsorption of different synthesized oily wastewater was studied and it was found that a decrease in adsorption can be seen with an increase in temperature or decreasing the pH value, which can be referred to this fact that the process of adsorption is an exothermic process. Finally, to analyze the compatibility of adsorption isotherms with experimental data and to predict the adsorption process, three different isotherms named Langmuir, Temkin, and Freundlich isotherms were applied and their parameters were correlated. The correlation results show that the Langmuir isotherm had the best correlation in all cases compared to the Freundlich and Temkin isotherms, based on the correlation coefficient, and the calculated R2 values which was greater than 0.99 in all the studied cases.

The molecular interaction of six single-stranded DNA aptamers to cardiac troponin I revealed by docking and molecular dynamics simulation.

Cardiac troponin I (cTnI) is a cardiac biomarker for diagnosing ischemic heart disease and acute myocardial infarction. Current biochemical assays use antibodies (Abs) due to their high specificity and sensitivity. However, there are some limitations, such as the high-cost production of Abs due to complex instruments, reagents, and steps; the variability of Abs quality from batch to batch; the low stability at high temperatures; and the difficulty of chemical modification. Aptamer overcomes the limitations of antibodies, such as relatively lower cost, high reproducibility, high stability, and ease of being chemically modified. Aptamers are three-dimensional architectures of single-stranded RNA or DNA that bind to targets such as proteins. Six aptamers (Tro1-Tro6) with higher binding affinity than an antibody have been identified, but the molecular interaction has not been studied. In this study, six DNA aptamers were modeled and docked to cTnI protein. Molecular docking revealed that the interaction between all aptamer and cTnI happened in the similar cTnI region. The interaction between aptamer and cTnI involved hydrophobic interaction, hydrogen bonds, π-cation interactions, π-stack interactions, and salt-bridge formation. The calculated binding energy of all complexes was negative, which means that the complex formation was thermodynamically favorable. The electrostatic energy term was the main driving force of the interaction between all aptamer and cTnI. This study could be used to predict the behavior of further modified aptamer to improve aptamer performance.

RNA Secondary Structure Thermodynamics.

Several different ways to predict RNA secondary structures have been suggested in the literature. Statistical methods, such as those that utilize stochastic context-free grammars (SCFGs), or approaches based on machine learning aim to predict the best representative structure for the underlying ensemble of possible conformations. Their parameters have therefore been trained on larger subsets of well-curated, known secondary structures. Physics-based methods, on the other hand, usually refrain from using optimized parameters. They model secondary structures from loops as individual building blocks which have been assigned a physical property instead: the free energy of the respective loop. Such free energies are either derived from experiments or from mathematical modeling. This rigorous use of physical properties then allows for the application of statistical mechanics to describe the entire state space of RNA secondary structures in terms of equilibrium probabilities. On that basis, and by using efficient algorithms, many more descriptors of the conformational state space of RNA molecules can be derived to investigate and explain the many functions of RNA molecules. Moreover, compared to other methods, physics-based models allow for a much easier extension with other properties that can be measured experimentally. For instance, small molecules or proteins can bind to an RNA and their binding affinity can be assessed experimentally. Under certain conditions, existing RNA secondary structure prediction tools can be used to model this RNA-ligand binding and to eventually shed light on its impact on structure formation and function.