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Journal of Chemical Theory and... Jun 2022The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value...
The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat a myriad of diseases. In this work, we examine the computation of alchemical relative binding free energies with an eye for assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2, and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2, and NAMD3 alpha. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between them of 0.50 kcal/mol. The correlation between packages is very good, with the lowest Spearman's, Pearson's and Kendall's tau correlation coefficients being 0.92, 0.91, and 0.76, respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.
Topics: Entropy; Ligands; Molecular Dynamics Simulation; Protein Binding; Reproducibility of Results; Thermodynamics
PubMed: 35609233
DOI: 10.1021/acs.jctc.2c00114 -
Biophysical Journal Sep 2020We report the free-energy landscape and thermodynamics of the protein-protein association responsible for the drug-induced multimerization of HIV-1 integrase (IN)....
We report the free-energy landscape and thermodynamics of the protein-protein association responsible for the drug-induced multimerization of HIV-1 integrase (IN). Allosteric HIV-1 integrase inhibitors promote aberrant IN multimerization by bridging IN-IN intermolecular interactions. However, the thermodynamic driving forces and kinetics of the multimerization remain largely unknown. Here, we explore the early steps in the IN multimerization by using umbrella sampling and unbiased molecular dynamics simulations in explicit solvent. In direct simulations, the two initially separated dimers spontaneously associate to form near-native complexes that resemble the crystal structure of the aberrant tetramer. Most strikingly, the effective interaction of the protein-protein association is very short-ranged: the two dimers associate rapidly within tens of nanoseconds when their binding surfaces are separated by d ≤ 4.3 Å (less than two water diameters). Beyond this distance, the oligomerization kinetics appears to be diffusion controlled with a much longer association time. The free-energy profile also captured the crucial role of allosteric IN inhibitors in promoting multimerization and explained why several C-terminal domain mutations are remarkably resistant to the drug-induced multimerization. The results also show that at small separation, the protein-protein binding process contains two consecutive phases with distinct thermodynamic signatures. First, interprotein water molecules are expelled to the bulk, resulting in a small increase in entropy, as the solvent entropy gain from the water release is nearly cancelled by the loss of side-chain entropies as the two proteins approach each other. At shorter distances, the two dry binding surfaces adapt to each other to optimize their interaction energy at the expense of further protein configurational entropy loss. Although the binding interfaces feature clusters of hydrophobic residues, overall, the protein-protein association in this system is driven by enthalpy and opposed by entropy.
Topics: Entropy; Molecular Dynamics Simulation; Protein Binding; Proteins; Thermodynamics
PubMed: 32877664
DOI: 10.1016/j.bpj.2020.08.005 -
Molecules and Cells Jan 2022Phase separation is a thermodynamic process leading to the formation of compositionally distinct phases. For the past few years, numerous works have shown that... (Review)
Review
Phase separation is a thermodynamic process leading to the formation of compositionally distinct phases. For the past few years, numerous works have shown that biomolecular phase separation serves as biogenesis mechanisms of diverse intracellular condensates, and aberrant phase transitions are associated with disease states such as neurodegenerative diseases and cancers. Condensates exhibit rich phase behaviors including multiphase internal structuring, noise buffering, and compositional tunability. Recent studies have begun to uncover how a network of intermolecular interactions can give rise to various biophysical features of condensates. Here, we review phase behaviors of biomolecules, particularly with regard to regular solution models of binary and ternary mixtures. We discuss how these theoretical frameworks explain many aspects of the assembly, composition, and miscibility of diverse biomolecular phases, and highlight how a model-based approach can help elucidate the detailed thermodynamic principle for multicomponent intracellular phase separation.
Topics: Humans; Neurodegenerative Diseases; Thermodynamics
PubMed: 34966005
DOI: 10.14348/molcells.2021.0204 -
International Journal of Molecular... Mar 2023We review the key steps leading to an improved analysis of thermal protein unfolding. Thermal unfolding is a dynamic cooperative process with many short-lived... (Review)
Review
We review the key steps leading to an improved analysis of thermal protein unfolding. Thermal unfolding is a dynamic cooperative process with many short-lived intermediates. Protein unfolding has been measured by various spectroscopic techniques that reveal structural changes, and by differential scanning calorimetry (DSC) that provides the heat capacity change C(T). The corresponding temperature profiles of enthalpy ΔH(T), entropy ΔS(T), and free energy ΔG(T) have thus far been evaluated using a chemical equilibrium two-state model. Taking a different approach, we demonstrated that the temperature profiles of enthalpy ΔH(T), entropy ΔS(T), and free energy ΔG(T) can be obtained directly by a numerical integration of the heat capacity profile C(T). DSC thus offers the unique possibility to assess these parameters without resorting to a model. These experimental parameters now allow us to examine the predictions of different unfolding models. The standard two-state model fits the experimental heat capacity peak quite well. However, neither the enthalpy nor entropy profiles (predicted to be almost linear) are congruent with the measured sigmoidal temperature profiles, nor is the parabolic free energy profile congruent with the experimentally observed trapezoidal temperature profile. We introduce three new models, an empirical two-state model, a statistical-mechanical two-state model and a cooperative statistical-mechanical multistate model. The empirical model partially corrects for the deficits of the standard model. However, only the two statistical-mechanical models are thermodynamically consistent. The two-state models yield good fits for the enthalpy, entropy and free energy of unfolding of small proteins. The cooperative statistical-mechanical multistate model yields perfect fits, even for the unfolding of large proteins such as antibodies.
Topics: Protein Denaturation; Thermodynamics; Protein Unfolding; Entropy; Proteins; Calorimetry, Differential Scanning; Protein Folding
PubMed: 36982534
DOI: 10.3390/ijms24065457 -
Molecules (Basel, Switzerland) May 2019The MgAlO-spinel has wide applications in various industries and in geosciences. It shows a significant inter-site Mg-Al cation exchange (denoted by the inversion... (Review)
Review
The MgAlO-spinel has wide applications in various industries and in geosciences. It shows a significant inter-site Mg-Al cation exchange (denoted by the inversion parameter ), which modifies structural features, such as the unit-cell parameters and the sizes of the component polyhedra, and influences the physical and chemical properties. Previous studies mainly focused on the kinetics and thermodynamics of the Mg-Al exchange reaction, with the aim to ascertain the correlation between the inversion parameter and temperature; these studies, however, reached conflicting results. Here, we first reviewed the kinetics studies on the Mg-Al cation exchange reaction, and then reviewed all thermodynamic experiments, with special attention paid to the Mg-Al cation exchange equilibrium and the quench process, which might have modified the cation distributions once attained at high temperatures. We also assessed the accuracies in the temperature measurements and in the quantifications of the by different analytical methods. With some necessary temperature correction and data removal, we have landed with a generally reliable - dataset covering the - space of 873 < < 1887 K and 0.18(1) < < 0.357(60) (71 data pairs in total). Fitting these - data to three most commonly used thermodynamic models, we have obtained more accurate model parameters. Further, we also evaluated the constituent items of the Gibbs free energy for the Mg-Al cation exchange reaction with experimental results from different research fields and reached the conclusion that highly possibly the T Δ S D should not be neglected. Based on this review, we suggest that: (1) Further kinetics study on the Mg-Al exchange reaction should be performed at both low (<~973 K) and high (>~1173 K); (2) further Mg-Al exchange equilibrium studies should be carried out at relatively low and ambient , as well as in vast ranges of simultaneous high and high ; and (3) direct experimental measures about the entropies or the enthalpies of the MgAlO-spinels disordered to different extents should be conducted with full characterization of the starting materials and detailed description of the experimental procedures.
Topics: Aluminum Oxide; Entropy; Hydrogen-Ion Concentration; Kinetics; Magnesium Oxide; Molecular Structure; Thermodynamics
PubMed: 31052437
DOI: 10.3390/molecules24091704 -
The Journal of Physical Chemistry. B Sep 2022While it is known since the early work by Edsall, Frank and Evans, Kauzmann, and others that the thermodynamics of solvation of nonpolar solutes in water is unusual and... (Review)
Review
While it is known since the early work by Edsall, Frank and Evans, Kauzmann, and others that the thermodynamics of solvation of nonpolar solutes in water is unusual and has implications for the thermodynamics of protein folding, only recently have its connections with the unusual temperature dependence of the density of solvent water been illuminated. Such density behavior is, in turn, one of the manifestations of a nonstandard thermodynamic pattern contemplating a second, liquid-liquid critical point at conditions of temperature and pressure at which water exists as a deeply supercooled liquid. Recent experimental and computational work unambiguously points toward the existence of such a critical point, thereby providing concrete answers to the questions posed by the 1976 pioneering experiments by Speedy and Angell and the associated "liquid-liquid transition hypothesis" posited in 1992 by Stanley and co-workers. Challenges of this phenomenology to the branch of Statistical Mechanics remain.
Topics: Chemistry, Physical; Humans; Solvents; Temperature; Thermodynamics; Water
PubMed: 36001372
DOI: 10.1021/acs.jpcb.2c05274 -
Annual Review of Biophysics May 2021Cooperativity is a hallmark of protein folding, but the thermodynamic origins of cooperativity are difficult to quantify. Tandem repeat proteins provide a unique... (Review)
Review
Cooperativity is a hallmark of protein folding, but the thermodynamic origins of cooperativity are difficult to quantify. Tandem repeat proteins provide a unique experimental system to quantify cooperativity due to their internal symmetry and their tolerance of deletion, extension, and in some cases fragmentation into single repeats. Analysis of repeat proteins of different lengths with nearest-neighbor Ising models provides values for repeat folding ([Formula: see text]) and inter-repeat coupling (Δ). In this article, we review the architecture of repeat proteins and classify them in terms of Δ and Δ; this classification scheme groups repeat proteins according to their degree of cooperativity. We then present various statistical thermodynamic models, based on the 1D-Ising model, for analysis of different classes of repeat proteins. We use these models to analyze data for highly and moderately cooperative and noncooperative repeat proteins and relate their fitted parameters to overall structural features.
Topics: Models, Molecular; Protein Folding; Tandem Repeat Sequences; Thermodynamics
PubMed: 33606943
DOI: 10.1146/annurev-biophys-102220-083020 -
Journal of the Royal Society, Interface Aug 2020An approach to implementing variational Bayesian inference in biological systems is considered, under which the thermodynamic free energy of a system directly encodes...
An approach to implementing variational Bayesian inference in biological systems is considered, under which the thermodynamic free energy of a system directly encodes its variational free energy. In the case of the brain, this assumption places constraints on the neuronal encoding of generative and recognition densities, in particular requiring a stochastic population code. The resulting relationship between thermodynamic and variational free energies is prefigured in mind-brain identity theses in philosophy and in the Gestalt hypothesis of psychophysical isomorphism.
Topics: Bayes Theorem; Brain; Neurons; Thermodynamics
PubMed: 32752995
DOI: 10.1098/rsif.2020.0370 -
International Journal of Molecular... Apr 2022Attempts to find and quantify the supposed low entropy of organisms and its preservation are revised. The absolute entropy of the mixed components of non-living biomass... (Review)
Review
Attempts to find and quantify the supposed low entropy of organisms and its preservation are revised. The absolute entropy of the mixed components of non-living biomass (approximately -1.6 × 10 J K L) is the reference to which other entropy decreases would be ascribed to life. The compartmentation of metabolites and the departure from the equilibrium of metabolic reactions account for reductions in entropy of 1 and 40-50 J K L, respectively, and, though small, are distinctive features of living tissues. DNA and proteins do not supply significant decreases in thermodynamic entropy, but their low informational entropy is relevant for life and its evolution. No other living feature contributes significantly to the low entropy associated with life. The photosynthetic conversion of radiant energy to biomass energy accounts for most entropy (2.8 × 10 J K carbon kg) produced by living beings. The comparatively very low entropy produced in other processes (approximately 4.8 × 10 J K L day in the human body) must be rapidly exported outside as heat to preserve low entropy decreases due to compartmentation and non-equilibrium metabolism. Enzymes and genes are described, whose control minimizes the rate of production of entropy and could explain selective pressures in biological evolution and the rapid proliferation of cancer cells.
Topics: Biochemical Phenomena; Biology; Biomass; Entropy; Humans; Thermodynamics
PubMed: 35456917
DOI: 10.3390/ijms23084098 -
Proceedings of the National Academy of... Nov 2021Microbial growth is a clear example of organization and structure arising in nonequilibrium conditions. Due to the complexity of the microbial metabolic network,...
Microbial growth is a clear example of organization and structure arising in nonequilibrium conditions. Due to the complexity of the microbial metabolic network, elucidating the fundamental principles governing microbial growth remains a challenge. Here, we present a systematic analysis of microbial growth thermodynamics, leveraging an extensive dataset on energy-limited monoculture growth. A consistent thermodynamic framework based on reaction stoichiometry allows us to quantify how much of the available energy microbes can efficiently convert into new biomass while dissipating the remaining energy into the environment and producing entropy. We show that dissipation mechanisms can be linked to the electron donor uptake rate, a fact leading to the central result that the thermodynamic efficiency is related to the electron donor uptake rate by the scaling law [Formula: see text] and to the growth yield by [Formula: see text] These findings allow us to rederive the Pirt equation from a thermodynamic perspective, providing a means to compute its coefficients, as well as a deeper understanding of the relationship between growth rate and yield. Our results provide rather general insights into the relation between mass and energy conversion in microbial growth with potentially wide application, especially in ecology and biotechnology.
Topics: Bacteria; Biomass; Entropy; Models, Biological; Thermodynamics
PubMed: 34799445
DOI: 10.1073/pnas.2107668118