Heat Capacity Change Research Articles

Determination of Protein-Ligand Binding Affinities by Thermal Shift Assay.

Quantification of protein-ligand interactions is crucial for understanding the protein's biological function and for drug discovery. In this study, we employed three distinct approaches for determination of protein-ligand binding affinities by a thermal shift assay using a single ligand concentration. We present the results of the comparison of the performance of the conventional curve fitting (CF) method and two newly introduced methods - assuming zero heat capacity change across small temperature ranges (ZHC) and utilizing the unfolding equilibrium constant (UEC); the latter has the advantage of reducing calculations by obtaining the unfolding equilibrium constant directly from the experimental data. Our results highlight superior performance of the ZHC and UEC methods over the conventional CF method in estimating the binding affinity, irrespective of the ligand concentration. In addition, we evaluated how the new methods can be applied to high-throughput screening for potential binders, when the enthalpy (ΔH L) and molar heat capacity change (ΔC PL) of ligand binding are unknown. Our results suggest that, in this scenario, using the -300 cal K-1 mol-1 assumption for ΔC pL and either -5 kcal mol-1 or the average enthalpy efficiency-based estimation for ΔH L(T) can still provide reasonable estimates of the binding affinity. Incorporating the new methods into the workflow for screening of small drug-like molecules, typically conducted using single-concentration libraries, could greatly simplify and streamline the drug discovery process.

Energy-efficient solar heat supply system based on hybrid photovoltaic collector

Following the commitments made under the Paris Climate Agreement, the scientific community has initiated a strategic increase in the share of renewable energy sources while gradually reducing dependence on traditional carbon fuels. Priority is given to the acceleration of the development of the photovoltaic industry, which has shown a constant increase in capacity over the past decades. According to the energy and climate strategies of the European Union, a significant increase in the amount of energy generation due to solar sources is planned. Therefore, the article is devoted to the development of a solar heat supply system based on a hybrid thermal photovoltaic solar collector with an improved design and analysis of the main characteristics of its operation using computer modeling. The authors have developed a 3D computer model of the proposed hybrid system with a solar collector by using SolidWorks software. The change in the temperature of the heat carrier in the hybrid thermal photovoltaic solar collector under constant solar radiation was analyzed. The temperature change of the coolant in the thermal accumulator of the system was also investigated. The results of the simulation of thermal processes revealed the key regularities of the temperature increase during the computer experiment, both in the hybrid thermal photovoltaic solar collector and in the thermal accumulator. The change in the instantaneous specific heat capacity of the developed solar collector was analyzed, and its average efficiency was estimated. The trends of changes in the thermal efficiency of the developed heat supply system during the computer experiment were determined. The novelty of the study is that the design of the hybrid thermophotoelectric solar collector has been improved, its 3D computer model has been developed, and the main thermal characteristics of the developed heat supply system with constant solar radiation have been obtained, which will contribute to the development of calculation methods for such heat supply systems with hybrid solar collectors in the future.

Theoretical description of the thermodynamic properties and the magnetocaloric effect in R2Cu2Cd (R = Dy,Ho)

In this paper, we present a theoretical discussion of the magnetocaloric effect in the compounds Dy2Cu2Cd and Ho2Cu2Cd whose curves of the heat capacity and isothermal entropy change exhibit two peaks. For this purpose, we use a model Hamiltonian of local magnetic moments with two anisotropic magnetic sublattices. In the model, it is considered that exchange interactions between magnetic moments depend on their xyz components. Besides, it is also included in the model a single ion uniaxial anisotropy and the Dzyaloshinskii-Moriya interaction to account for the canted magnetic moments. Our theoretical calculations show that the existence of these two peaks is associated with a spin reorientation transition at a lower temperature and a ferromagnetic-paramagnetic one at a higher temperature. The results of our theoretical calculations are in reasonable agreement with the existing experimental data of heat capacity and the isothermal entropy change.

Differential Scanning Calorimetry: A Powerful and Versatile Tool for Analyzing Proteins and Peptides

Differential Scanning Calorimetry (DSC) is an efficient and versatile analytical technique widely used to study the thermal properties and stability of proteins. This review article provides a comprehensive overview of the principles and applications of DSC in protein research. DSC measures the heat flow associated with temperature-induced conformational changes in proteins, allowing for the direct determination of key thermodynamic parameters such as melting temperature (Tm), enthalpy change (ΔH), and heat capacity change (ΔCp). These parameters provide valuable insights into protein and peptide stability, folding mechanisms, and interactions with ligands. The review discusses the methodological aspects of DSC, including sample preparation, experimental setup, and data analysis techniques. It also highlights the application of DSC in various aspects, such as drug discovery, biopharmaceutical development, and the study of protein-ligand interactions. By elucidating the thermal behavior of proteins, DSC contributes significantly to our understanding of protein and peptide structure, function, and stability, making it an indispensable tool in biochemical and biophysical research.

Computational Analysis of Heat Capacity Effects in Protein-Ligand Binding.

Heat capacity effects in protein-ligand binding as measured by calorimetric experiments have recently attracted considerable attention, particularly in the field of enzyme inhibitor design. A significant negative heat capacity change upon ligand binding implies a marked temperature dependence of the binding enthalpy, which is of high relevance for attempts to optimize protein-ligand interactions. In this work, we address the question of how well such heat capacity changes can be predicted by computer simulations. We examine a series of human thrombin inhibitors that all bind with ΔCp values of about -0.4 kcal/mol/K and calculate heat capacity changes from plain molecular dynamics simulations of the bound and free states of the enzyme and ligand. The results show that accurate ΔCp estimates within a few tenths of a kcal/mol/K of the experimental values can be obtained with this approach. This allows us to address the structural and energetic origin of the negative heat capacity changes for the thrombin inhibitors, and it is found that conformational equilibria of the free ligands in solution make a major contribution to the observed effect.

STUDYING THE STRUCTURAL, ELECTRICAL, AND MAGNETIC CHARACTERISTICS OF ASiNRS-DOPED NEODYMIUM USING THE FIRST PRINCIPLE

There have been many applied studies on Nd in medicine, cooling techniques due to large amplitude changes in specific heat capacity, making glass pigments, making laser materials, and many other fields. However, there have been no specific studies on the structural and electronic properties related to the band gap. In this study, we investigated the optimization of Nd adsorption on Armchair nanoribbon silicene substrate. The research was carried out in three steps. The first step is to change the Nd atom through the four positions (top, valley, hollow, and bridge) to determine the optimal position. As a result, the bridge site has a magnetic moment of 4.68 µB and a locking degree of 0.69 Ǻ, has the lowest absorbed energy value of -2.6 eV, and has the most stable structure. Second step, we varied the Si-Si bond length of silicene for the same target, resulting in choosing the optimal bond length of 2.27 Ǻ. Finally, we consider the distance between the Nd atom and the silicene surface and determine that with the same bond length 2.27 Ǻ, the result obtained at a height of 2.11 Ǻ occurs most optimally. This result proves that silicene-doped Nd is very promising as a material for making visible sensors and spin motors in the future.

Enhanced cryogenic magnetocaloric performance and the existence of short-range magnetic correlations in frustrated diamond geometries

The magnetocaloric effect in the cryogenic temperature regime has gained enormous attention due to its application in the field of cryogenic refrigeration technology, which is required for quantum computing, space sciences and basic research activities. In this context, Gd- and Dy-based frustrated systems are considered as promising cryogenic magnetocaloric materials. Hence, in this paper the magnetic and magnetocaloric properties of GdTaO4, GdNbO4 and DyNbO4 are comprehensively investigated. Structural analysis suggests that these compounds crystallize in a monoclinic structure, wherein magnetic ions form an elongated diamond geometry. Analysis of magnetization, heat capacity and field-dependent magnetic entropy changes confirms the presence of short-range magnetic correlations in these compounds. Additionally, a remarkably large magnetic entropy change and relative cooling power are noted. The mechanical efficiency is found to be comparable to (or even better than) those reported for good magnetic refrigerants. Our study suggests that GdTaO4, GdNbO4 and DyNbO4 can be regarded as promising cryogenic magnetic refrigerant materials.

Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations

Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, as it directly correlated with the protein function. Thus, this study delves into the intricacies of protein stability, highlighting its dependence on various factors, including thermodynamics, thermal conditions, and structural properties. Moreover, a notable focus is placed on the free energy change of unfolding (ΔGunfolding), change in heat capacity (ΔCp) with protein structural transition, melting temperature (Tm) and number of disulfide bonds, which are critical parameters in understanding protein stability. In this study, a machine learning (ML) predictive model was developed to estimate these four parameters using the primary sequence of the protein. The shortfall of available tools for protein stability prediction based on multiple parameters propelled the completion of this study. Convolutional Neural Network (CNN) with multiple layers was adopted to develop a more reliable ML model. Individual predictive models were prepared for each property, and all the prepared models showed results with high accuracy. The R2 (coefficient of determination) of these models were 0.79, 0.78, 0.92 and 0.92, respectively, for ΔG, ΔCp, Tm and disulfide bonds. A case study on stability analysis of two homologous proteins was presented to validate the results predicted through the developed model. The case study included in silico analysis of protein stability using molecular docking and molecular dynamic simulations. This validation study assured the accuracy of each model in predicting the stability associated properties. The alignment of physics-based principles with ML models has provided an opportunity to develop a fast machine learning solution to replace the computationally demanding physics-based calculations used to determine protein stability. Furthermore, this work provided valuable insights into the impact of mutation on protein stability, which has implications for the field of protein engineering. The source codes are available at https://github.com/Growdeatechnology.

Analysis of the energy efficiency of a system with a hybrid solar collector and thermal energy storage

The object of research is heat transfer in a hybrid thermal photovoltaic solar collector. International agreements and strategies aimed at combating climate change and reducing greenhouse gas emissions strongly call for the active implementation of renewable energy sources on a global scale. A special emphasis is placed on the development of solar energy, which has significant growth potential due to the constant improvement of technologies and cost reduction of production. With this in mind, the authors focused on the development and analysis of a computer model of an innovative hybrid system that effectively combines a solar collector for the simultaneous production of both thermal and electrical energy. The research included a detailed study of the temperature changes of the heat carrier in the hybrid photovoltaic solar collector and thermal accumulator during the period of solar irradiation. Thanks to careful monitoring, the main patterns of gradual temperature increase in both key components of the hybrid system were established. In addition, an assessment of the dynamics of changes in the instantaneous thermal power of the solar collector under the influence of various factors, such as the intensity of solar radiation, the angle of inclination of the collector, wind speed, etc., was carried out. The results of computer modeling showed the average indicator of the efficiency of the entire hybrid system, as well as its variations during a certain time of operation. In addition, the change in the instantaneous specific heat capacity and the overall efficiency of heat energy generation by the hybrid photovoltaic solar collector were analyzed. Special attention was paid to the study of the dynamics of changes in the thermal efficiency of the entire system, as well as its ability to efficiently store thermal energy in a specialized battery. The comprehensive analysis made it possible to obtain the key thermophysical parameters of the developed hybrid system with a photovoltaic solar collector. This data is extremely important, as it will allow engineers and scientists to accurately calculate the potential performance and efficiency of such a system when it is put into practical use in the future. In general, the results of the study emphasize the promising development of hybrid solar collectors as one of the leading technologies in the field of renewable energy in the context of global challenges of climate change.

Study on the effect of low-temperature cycling on the thermal and gas production behaviors of Ni0.8Co0.1Al0.1/graphite lithium-ion batteries

With their high energy density and long cycle life, lithium-ion batteries (LIBs) are currently the most promising electrochemical energy storage system for electric vehicles. However, their safety and cycling performance can be significantly compromised in low-temperature environments due to lithium plating and other factors. Therefore, it is essential to study the safety of aging batteries. In this study, we focused on a commercially available high-specific-energy Ni0.8Co0.1Al0.1 cathode system battery and simulated the aging of the battery by long-term cycling at 0 ℃. This study compares and analyzes the samples on the basis of the previous ones in terms of heat production power, thermal runaway (TR) characteristics and gas production characteristics. It reveals the influence of low-temperature aging on the comprehensive performance of lithium batteries in a more comprehensive way. The results show that the charging pattern of all three characteristics is related to the aging degree of the battery. In terms of the thermal characteristics, the relative change in specific heat capacity of the aged battery is only between 0.32 % and 1.08 % compared to that of a fresh battery, so the effect of ageing on the specific heat capacity of the battery is negligible. The average heat generation power of batteries with different state of health (SOH) is not monotonically increasing with the decrease of SOH, the threshold of dramatic increase is SOH = 80 %. In terms of TR characteristics, the onset temperature of exothermic reactions (TOER) of aged batteries is significantly lower than that of fresh batteries. With the decrease of SOH, TOER also decreases gradually. Compared with batteries with different SOHs, the more seriously aged the battery safety valve opens earlier, and the TR occurs earlier. In terms of the TR gas production characteristics, the more severely aged the battery, the earlier the safety valve opens compared to a fresh battery. The most gas is produced when SOH = 70 %, which increases the risk of catastrophic damage.

Isothermal titration calorimetry and surface plasmon resonance methods to probe protein–protein interactions

Isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR) are two commonly used methods to probe biomolecular interactions. ITC can provide information about the binding affinity, stoichiometry, changes in Gibbs free energy, enthalpy, entropy, and heat capacity upon binding. SPR can provide information about the association and dissociation kinetics, binding affinity, and stoichiometry. Both methods can determine the nature of protein–protein interactions and help understand the physicochemical principles underlying complex biochemical pathways and communication networks. This methods article discusses the practical knowledge of how to set up and troubleshoot these two experiments with some examples.

Estimation of Peptide Helicity from Circular Dichroism Using the Ensemble Model.

An established method for the quantitation of the helix content in peptides using circular dichroism (CD) relies on the linear spectroscopic model. This model assumes an average value of the helix-length correction for all peptide conformers, irrespective of the length of the helical segment. Here we assess the validity of this approximation and introduce a more physically realistic ensemble-based analysis of the CD signal in which the length correction is assigned specifically to each ensemble conformer. We demonstrate that the linear model underestimates peptide helicity, with the difference depending on the ensemble composition. We developed a computer program that implements the ensemble model to estimate the peptide helicity. Using this model and the CD data set covering a broad range of helicities, we recalibrate CD baseline parameters and redetermine helix-coil parameters for the alanine-rich peptide. We show that the ensemble model leverages small differences in signal between conformers to extract more information from the experimental data, enabling the determination of several poorly defined quantities, such as the nucleation constant and heat capacity change associated with helix folding. Overall, the presented ensemble-based treatment of the CD signal, together with the recalibrated values of the spectroscopic baseline parameters, provides a coherent framework for the analysis of the peptide helix content.

Cooperative Conformational Transitions Underpin the Activation Heat Capacity in the Temperature Dependence of Enzyme Catalysis.

Many enzymes display non-Arrhenius behavior with curved Arrhenius plots in the absence of denaturation. There has been significant debate about the origin of this behavior and recently the role of the activation heat capacity (ΔCP⧧) has been widely discussed. If enzyme-catalyzed reactions occur with appreciable negative values of ΔCP⧧ (arising from narrowing of the conformational space along the reaction coordinate), then curved Arrhenius plots are a consequence. To investigate these phenomena in detail, we have collected high precision temperature-rate data over a wide temperature interval for a model glycosidase enzyme MalL, and a series of mutants that change the temperature-dependence of the enzyme-catalyzed rate. We use these data to test a range of models including macromolecular rate theory (MMRT) and an equilibrium model. In addition, we have performed extensive molecular dynamics (MD) simulations to characterize the conformational landscape traversed by MalL in the enzyme-substrate complex and an enzyme-transition state complex. We have crystallized the enzyme in a transition state-like conformation in the absence of a ligand and determined an X-ray crystal structure at very high resolution (1.10 Å). We show (using simulation) that this enzyme-transition state conformation has a more restricted conformational landscape than the wildtype enzyme. We coin the term "transition state-like conformation (TLC)" to apply to this state of the enzyme. Together, these results imply a cooperative conformational transition between an enzyme-substrate conformation (ES) and a transition-state-like conformation (TLC) that precedes the chemical step. We present a two-state model as an extension of MMRT (MMRT-2S) that describes the data along with a convenient approximation with linear temperature dependence of the activation heat capacity (MMRT-1L) that can be used where fewer data points are available. Our model rationalizes disparate behavior seen for MalL and previous results for a thermophilic alcohol dehydrogenase and is consistent with a raft of data for other enzymes. Our model can be used to characterize the conformational changes required for enzyme catalysis and provides insights into the role of cooperative conformational changes in transition state stabilization that are accompanied by changes in heat capacity for the system along the reaction coordinate. TLCs are likely to be of wide importance in understanding the temperature dependence of enzyme activity and other aspects of enzyme catalysis.

The effect of graphene nanoparticleson the thermal conductivity enhancementof organic phase change material and its energystorage properties

Organic phase change materials (PCMs), which are typically used as the accumulating material in latent heat thermal energy storage, provide chemical and thermal stability, but have low thermal conductivity. This limits heat transfer rates and prolongs storage charging/discharging time. A method to improve the thermal conductivity of organic PCMs is to add nanomaterials with high thermal conductivity. The paper presents the research on the effect of the addition of graphene nanoparticles (GNPs) on the thermal conductivity of organic PCM (RT28 HC), and its energy storage properties. The transient hot wire and the pipe Poensgen apparatus methods were used to measure thermal conductivity, and the differential scanning calorimetry method was used to determine the heat capacity and phase change temperature. The achieved characteristics of thermal conductivity depending on the amount of added graphene nanoparticles (and stabilizer) indicate that GNPs allow to increase the thermal conductivity on average by 26–87% in the solid state and by 7–28% in the liquid, but this reduces the PCM heat capacity. Therefore, the paper indicates what mass fraction of dopants is optimal to achieve the greatest improvement in thermal conductivity of RT28 HC and its smallest reduction in heat capacity, to use this nano-enhanced PCM in practice.

Influence of lithium on the temperature dependence of heat capacity and thermodynamic functions changes in AK1 alloy based on high-purity aluminum

The heat capacity of the AK1 alloy based on high-purity aluminum with lithium was determined in the cooling mode using the known heat capacity of the reference aluminum sample. By means of mathematical processing of cooling rate curves of samples from AK1 alloy with lithium and the reference sample, polynomials describing their cooling rates were obtained. Further, the polynomials of the temperature dependence of the heat capacity of alloys, described by a four-member equation, were established using the experimentally found values of the cooling rates of samples from alloys and the standard, taking into account their mass. Using integrals from specific heat capacity, models of temperature dependence of enthalpy, entropy and Gibbs energy changes were established. It was found that the heat capacity of the alloys increases with rising temperature. The addition of lithium when the temperature is up to 600 K significantly increases the heat capacity, and at temperatures above 600 K lithium in amounts of 0.5 wt. % reduces the heat capacity of the initial alloy AK1. It is shown that lithium addition increases the enthalpy and entropy of the initial AK1 alloy and decreases the Gibbs energy value.

Heat capacity changes associated with G-quadruplex unfolding

Heat capacity changes associated with G-quadruplex unfolding

Energy, water, and protein folding: A molecular dynamics-based quantitative inventory of molecular interactions and forces that make proteins stable.

Protein folding energetics can be determined experimentally on a case-by-case basis but it is not understood in sufficient detail to provide deep control in protein design. The fundamentals of protein stability have been outlined by calorimetry, protein engineering, and biophysical modeling, but these approaches still face great difficulty in elucidating the specific contributions of the intervening molecules and physical interactions. Recently, we have shown that the enthalpy and heat capacity changes associated to the protein folding reaction can be calculated within experimental error using molecular dynamics simulations of native protein structures and their corresponding unfolded ensembles. Analyzing in depth molecular dynamics simulations of four model proteins (CI2, barnase, SNase, and apoflavodoxin), we dissect here the energy contributions to ΔH (a key component of protein stability) made by the molecular players (polypeptide and solvent molecules) and physical interactions (electrostatic, van der Waals, and bonded) involved. Although the proteins analyzed differ in length, isoelectric point and fold class, their folding energetics is governed by the same quantitative pattern. Relative to the unfolded ensemble, the native conformations are enthalpically stabilized by comparable contributions from protein-protein and solvent-solvent interactions, and almost equally destabilized by interactions between protein and solvent molecules. The native protein surface seems to interact better with water than the unfolded one, but this is outweighed by the unfolded surface being larger. From the perspective of physical interactions, the native conformations are stabilized by van de Waals and Coulomb interactions and destabilized by conformational strain arising from bonded interactions. Also common to the four proteins, the sign of the heat capacity change is set by interactions between protein and solvent molecules or, from the alternative perspective, by Coulomb interactions.

Exploring the Heat of Water Intrusion into a Metal-Organic Framework by Experiment and Simulation.

Wetting of a solid by a liquid is relevant for a broad range of natural and technological processes. This process is complex and involves the generation of heat, which is still poorly understood especially in nanoconfined systems. In this article, scanning transitiometry was used to measure and evaluate the pressure-driven heat of intrusion of water into solid ZIF-8 powder within the temperature range of 278.15-343.15 K. The conditions examined included the presence and absence of atmospheric gases, basic pH conditions, solid sample origins, and temperature. Simultaneously with these experiments, molecular dynamics simulations were conducted to elucidate the changing behavior of water as it enters into ZIF-8. The results are rationalized within a temperature-dependent thermodynamic cycle. This cycle describes the temperature-dependent process of ZIF-8 filling, heating, emptying, and cooling with respect to the change of internal energy of the cycle from the calculated change in the specific heat capacity of the system. At 298 K the experimental heat of intrusion per gram of ZIF-8 was found to be -10.8 ± 0.8 J·g-1. It increased by 19.2 J·g-1 with rising temperature to 343 K which is in a reasonable match with molecular dynamic simulations that predicted 16.1 J·g-1 rise. From these combined experiments, the role of confined water in heat of intrusion of ZIF-8 is further clarified.

Evaluation of chemical composition and physical properties of bituminous binders and fractions

Bituminous binders are foreseen as colloidal dispersed systems characterised by high chemical complexity containing a plethora of molecules classified into maltenes and asphaltenes. The effect of these fractions on the overall response of bituminous binders remains elusive. This research selected two binders from the same refinery but with different paving grades. First, Dynamic Shear and Bending Beam Rheometers were employed to assess their rheological properties, and results were consistent with the physical measurements conducted on binders to address low to high temperature rheological response. Then, the binders and their fractions were individually analysed in a Fourier transform infrared spectroscopy and differential scanning calorimetry to elucidate their chemistry associated with the structural changes. No significant difference could be noticed in the infrared spectra of binders, even if they displayed diverse physical properties. Differences may be identified in asphaltenes, an observation which is also supported by calorimetric measurements where steric hindrance occurred upon heating. Maltenes contributed significantly to the glass transition of both binders, while the impact of asphaltenes on the heat capacity changes in glass transition was limited. The findings from this research could be used to establish a new analytical approach for bituminous binders to understand the differences in the physical properties of binders based on their chemistry.

Cold denaturation of DNA origami nanostructures.

The coupling of structural transitions to heat capacity changes leads to destabilization of macromolecules at both elevated and lowered temperatures. DNA origami not only exhibit this property but also provide a nanoscopic observable of cold denaturation processes by directing intramolecular strain to the most sensitive elements within their hierarchical architecture.