Thermodynamics Of Ligand Binding Research Articles

Ligand Gaussian Accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides.

Binding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional molecular dynamics (cMD), due to limited simulation time scales. Based on our previously developed ligand Gaussian accelerated molecular dynamics (LiGaMD) method, we present a new approach, termed "LiGaMD3″, in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding, and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as the model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 μs simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 were in agreement with the available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligands and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.

Is the functional response of a receptor determined by the thermodynamics of ligand binding?

Is the functional response of a receptor determined by the thermodynamics of ligand binding?

Bis(N-xylyl-imino)phenyl “NCN” iridium pincer complexes. Thermodynamics of ligand binding and C[sbnd]C bond cleavage

Iridium dibromide complexes of the phenyldiimine ligand 2,6-bis(1-((2,6-dimethylphenyl)imino)ethyl)phenyl, trans-(XyPhDI)IrBr2L, have been synthesized, and relative Ir-L BDFEs have been experimentally determined for a wide range of corresponding adducts of ligands L. An estimate of the absolute enthalpy of Ir-L binding has been obtained from dynamic NMR measurements. The results of DFT calculations are in very good agreement with the relative and absolute experimental values. Computational studies were extended to the formation of adducts of (XyPhDI)IrH2 and (XyPhDI)IrI, as well as other (pincer)IrI fragments, (Phebox)IrI and (PCP)IrI, to enable a comparison of electronic and steric effects with these archetypal pincer ligands. Attempts to reduce (XyPhDI)IrBr2(MeCN) to a hydride or an IrI complex yielded a dinuclear CN-bridged complex with a methyl ligand on the cyanide-C-bound Ir center (characterized by scXRD), indicating that C-CN bond cleavage took place at that Ir center. DFT calculations indicate that the C-CN bond cleavage occurs at one Ir center with strong assistance by coordination of the CN nitrogen to the other Ir center.

Atomically precise surface chemistry of zirconium and hafnium metal oxo clusters beyond carboxylate ligands.

The effectiveness of nanocrystals in many applications depends on their surface chemistry. Here, we leverage the atomically precise nature of zirconium and hafnium oxo clusters to gain fundamental insight into the thermodynamics of ligand binding. Through a combination of theoretical calculations and experimental spectroscopic techniques, we determine the interaction between the M6O8 8+ (M = Zr, Hf) cluster surface and various ligands: carboxylates, phosphonates, dialkylphosphinates, and monosubstituted phosphinates. We refute the common assumption that the adsorption energy of an adsorbate remains unaffected by the surrounding adsorbates. For example, dialkylphosphinic acids are too sterically hindered to yield complete ligand exchange, even though a single dialkylphosphinate has a high binding affinity. Monoalkyl or monoaryl phosphinic acids do replace carboxylates quantitatively and we obtained the crystal structure of M6O8H4(O2P(H)Ph)12 (M = Zr, Hf), giving insight into the binding mode of monosubstituted phosphinates. Phosphonic acids cause a partial structural reorganization of the metal oxo cluster into amorphous metal phosphonate as indicated by pair distribution function analysis. These results rationalize the absence of phosphonate-capped M6O8 clusters and the challenge in preparing Zr phosphonate metal-organic frameworks. We thus further reinforce the notion that monoalkylphosphinates are carboxylate mimics with superior binding affinity.

Is the Functional Response of a Receptor Determined by the Thermodynamics of Ligand Binding?

For an effective drug, strong binding to the target protein is a prerequisite, but it is not enough. To produce a particular functional response, drugs need to either block the proteins' functions or modulate their activities by changing their conformational equilibrium. The binding free energy of a compound to its target is routinely calculated, but the timescales for the protein conformational changes are prohibitively long to be efficiently modeled via physics-based simulations. Thermodynamic principles suggest that the binding free energies of the ligands with different receptor conformations may infer their efficacy. However, this hypothesis has not been thoroughly validated. We present an actionable protocol and a comprehensive study to show that binding thermodynamics provides a strong predictor of the efficacy of a ligand. We apply the absolute binding free energy perturbation method to ligands bound to active and inactive states of eight G protein-coupled receptors and a nuclear receptor and then compare the resulting binding free energies. We find that carefully designed restraints are often necessary to efficiently model the corresponding conformational ensembles for each state. Our method achieves unprecedented performance in classifying ligands as agonists or antagonists across the various investigated receptors, all of which are important drug targets.

Accelerating Molecular Dynamics Simulations for Drug Discovery.

Accurate prediction of ligand binding thermodynamics and kinetics is crucial in drug design. However, it remains challenging for conventional molecular dynamics (MD) simulations due to sampling issues. Gaussian accelerated MD (GaMD) is an enhanced sampling method that adds a harmonic boost to overcome energy barriers, which has demonstrated significant benefits in exploring protein-ligand interactions. Especially, the ligand GaMD (LiGaMD) applies a selective boost potential to the ligand nonbonded potential energy, significantly improving sampling for ligand binding and dissociation. Furthermore, a selective boost potential is applied to the potential of both ligand and protein residues around binding pocket in LiGaMD2 to further increase the sampling of protein-ligand interaction. LiGaMD and LiGaMD2 simulations could capture repetitive ligand binding and unbinding events within microsecond simulations, allowing to simultaneously characterize ligand binding thermodynamics and kinetics, which is expected to greatly facilitate drug design. In this chapter, we provide a brief review of the status of LiGaMD in drug discovery and outline its usage.

The effect of denaturants on protein thermal stability analyzed through a theoretical model considering multiple binding sites

A novel mathematical development applied to protein ligand binding thermodynamics is proposed, which allows the simulation, and therefore the analysis of the effects of multiple and independent binding sites to the Native and/or Unfolded protein conformations, with different binding constant values. Protein stability is affected when it binds to a small number of high affinity ligands or to a high number of low affinity ligands. Differential scanning calorimetry (DSC) measures released or absorbed energy of thermally induced structural transitions of biomolecules. This paper presents the general theoretical development for the analysis of thermograms of proteins obtained for n-ligands bound to the native protein and m-ligands bound to their unfolded form. In particular, the effect of ligands with low affinity and with a high number of binding sites (n and/or m > 50) is analyzed. If the interaction with the native form of the protein is the one that predominates, they are considered stabilizers and if the binding with the unfolded species predominates, it is expected a destabilizing effect. The formalism presented here can be adapted to fitting routines in order to simultaneously obtain the unfolding energy and ligand binding energy of the protein. The effect of guanidinium chloride on bovine serum albumin thermal stability, was successfully analyzed with the model considering low number of middle affinity binding sites to the native state and a high number of weak binding sites to the unfolded state.

Ligand Gaussian Accelerated Molecular Dynamics 2 (LiGaMD2): Improved Calculations of Ligand Binding Thermodynamics and Kinetics with Closed Protein Pocket.

Ligand binding thermodynamics and kinetics are critical parameters for drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics from molecular simulations due to limited simulation timescales. Protein dynamics, especially in the ligand binding pocket, often plays an important role in ligand binding. Based on our previously developed Ligand Gaussian accelerated molecular dynamics (LiGaMD), here we present LiGaMD2 in which a selective boost potential was applied to both the ligand and protein residues in the binding pocket to improve sampling of ligand binding and dissociation. To validate the performance of LiGaMD2, the T4 lysozyme (T4L) mutants with open and closed pockets bound by different ligands were chosen as model systems. LiGaMD2 could efficiently capture repetitive ligand dissociation and binding within microsecond simulations of all T4L systems. The obtained ligand binding kinetic rates and free energies agreed well with available experimental values and previous modeling results. Therefore, LiGaMD2 provides an improved approach to sample opening of closed protein pockets for ligand dissociation and binding, thereby allowing for efficient calculations of ligand binding thermodynamics and kinetics.

Pressure, motion, and conformational entropy in molecular recognition by proteins

The thermodynamics of molecular recognition by proteins is a central determinant of complex biochemistry. For over a half-century, detailed cryogenic structures have provided deep insight into the energetic contributions to ligand binding by proteins. More recently, a dynamical proxy based on NMR-relaxation methods has revealed an unexpected richness in the contributions of conformational entropy to the thermodynamics of ligand binding. Here, we report the pressure dependence of fast internal motion within the ribonuclease barnase and its complex with the protein barstar. In what we believe is a first example, we find that protein dynamics are conserved along the pressure-binding thermodynamic cycle. The femtomolar affinity of the barnase-barstar complex exists despite a penalty by −TΔSconf of +11.7 kJ/mol at ambient pressure. At high pressure, however, the overall change in side-chain dynamics is zero, and binding occurs with no conformational entropy penalty, suggesting an important role of conformational dynamics in the adaptation of protein function to extreme environments. Distinctive clustering of the pressure sensitivity is observed in response to both pressure and binding, indicating the presence of conformational heterogeneity involving less efficiently packed alternative conformation(s). The structural segregation of dynamics observed in barnase is striking and shows how changes in both the magnitude and the sign of regional contributions of conformational entropy to the thermodynamics of protein function are possible.

Relating protein crystal structure to ligand-binding thermodynamics.

An important interface between biophysical chemistry and biological crystal structures involves whether it is possible to relate experimental calorimetry measurements of protein ligand binding to 3D structures. This has proved to be challenging. The probes of the structure of matter, namely X-rays, neutrons and electrons, have challenges of one type or another in their use. This article focuses on saccharide binding to lectins as a theme, yet after 25 years or so it is still a work in progress to connect 3D structure to binding energies. Whilst this study involved one type of protein (lectins) and one class of ligand (monosaccharides), i.e. it was specific, it was of general importance, as measured for instance by its wide impact. The impetus for writing this update now, as a Scientific Comment, is that a breakthrough in neutron crystal structure determinations of saccharide-bound lectins has been achieved. It is suggested here that this new research from neutron protein crystallography could improve, i.e. reduce, the errors in the estimated binding energies.

Binding Kinetics Toolkit for Analyzing Transient Molecular Conformations and Computing Free Energy Landscapes.

Understanding ligand binding kinetics and thermodynamics, which involves investigating the free, transient, and final complex conformations, is important in fundamental studies and applications for chemical and biomedical systems. Examining the important but transient ligand-protein-bound conformations, in addition to experimentally determined structures, also provides a more accurate estimation for drug efficacy and selectivity. Moreover, obtaining the entire picture of the free energy landscape during ligand binding/unbinding processes is critical in understanding binding mechanisms. Here, we present a Binding Kinetics Toolkit (BKiT) that includes several utilities to analyze trajectories and compute a free energy and kinetics profile. BKiT uses principal component space to generate approximated unbinding or conformational transition coordinates for accurately describing and easily visualizing the molecular motions. We implemented a new partitioning approach to assign indexes along the approximated coordinates that can be used as milestones or microstates. The program can generate input files to run many short classical molecular dynamics simulations and uses milestoning theory to construct the free energy profile and estimate binding residence time. We first validated the method with a host-guest system, aspirin unbinding from β-cyclodextrin, and then applied the protocol to pyrazolourea compounds and cyclin-dependent kinase 8 and cyclin C complexes, a kinase system of pharmacological interest. Overall, our approaches yielded good agreement with published results and suggest ligand design strategies. The computed unbinding free energy landscape also provides a more complete picture of ligand-receptor binding barriers and stable local minima for deepening our understanding of molecular recognition. BKiT is easy to use and has extensible features for future expansion of utilities for postanalysis and calculations.

Bell-Evans model and steered molecular dynamics in uncovering the dissociation kinetics of ligands targeting G-protein-coupled receptors

Recently, academic and industrial scientific communities involved in kinetics-based drug development have become immensely interested in predicting the drug target residence time. Screening drug candidates in terms of their computationally predicted residence times, which is a measure of drug efficacy in vivo, and simultaneously assessing computational binding affinities are becoming inevitable. Non-equilibrium molecular simulation approaches are proven to be useful in this purpose. Here, we have implemented an optimized approach of combining the data derived from steered molecular dynamics simulations and the Bell-Evans model to predict the absolute residence times of the antagonist ZMA241385 and agonist NECA that target the A2A adenosine receptor of the G-protein-coupled receptor (GPCR) protein family. We have predicted the absolute ligand residence times on the timescale of seconds. However, our predictions were many folds shorter than those determined experimentally. Additionally, we calculated the thermodynamics of ligand binding in terms of ligand binding energies and the per-residue contribution of the receptor. Subsequently, binding pocket hotspot residues that would be important for further computational mutagenesis studies were identified. In the experiment, similar sets of residues were found to be in significant contact with both ligands under study. Our results build a strong foundation for further improvement of our approach by rationalizing the kinetics of ligand unbinding with the thermodynamics of ligand binding.

G-Tetrad-Selective Ligand Binding Kinetics in G-Quadruplex DNA Probed with Fluorescence Correlation Spectroscopy.

Probing the kinetics of ligand binding to biomolecules is of paramount interest in biology and pharmacology. Measurements of such kinetic processes provide information on the rate-determining steps that control the binding affinity of ligands to biomolecules, thereby predicting the mechanism of the molecular interaction. In this context, ligand binding to G-quadruplex DNA (GqDNA) structures has attracted tremendous attention primarily because of their use in possible anticancer therapy. Although a large number of G-quadruplex-specific ligands have been proposed, probing the kinetics of G-tetrad-selective binding of (multiple) ligands within a G-quadruplex DNA (GqDNA) structure remains challenging. Most of the earlier studies focused on the thermodynamics of ligand binding; however, the kinetics of ligand association and dissociation with GqDNA, particularly binding of multiple ligands within a GqDNA structure, have not been explored. Here, we propose a simple fluorescence correlation spectroscopy-based method that measures the G-tetrad-selective association and dissociation rates of ligands within a GqDNA structure by correlating the fluorescence fluctuations of a site-specific (5' or 3' end-labeled) fluorophore (Cy3) in GqDNA due to quenching of Cy3 fluorescence, induced by the ligand binding to the G-tetrads. We show that well-known GqDNA ligands, BRACO19, TMPyP4, Hoechst 33258, and Hoechst 33342, have G-tetrad-selective association and dissociation rates, which suggest site-dependent variation of free energy barriers for binding/unbinding of the ligands with GqDNA. We also show that the measured kinetic rates depend not only on the G-tetrad site (5' vs 3' end) but also on the ligand and GqDNA structures.

Probing the ligand-binding pocket of recombinant β-lactoglobulin: Calorimetric and spectroscopic studies

β-Lactoglobulin (BLG), a member of the lipocalin family, is a well-studied model protein. It is also widely used as a scaffold for the development of novel proteins. Our previous work adopted a rational approach based on homolog structure alignment to obtain several BLG variants with point mutations inside the binding pocket. To investigate the effect of mutation on ligand binding thermodynamics, we chose a set of aliphatic ligands and performed a study based on isothermal titration calorimetry. In addition, the circular dichroism spectra observed for the protein–ligand complexes were analyzed. The ligand binding thermodynamics was compared between wild-type and mutated BLG as well as between two ligands. The findings pointed to factors that can be responsible for the mutation-induced changes in the thermodynamics of the complexes.

Entropy-Entropy Compensation between the Protein, Ligand, and Solvent Degrees of Freedom Fine-Tunes Affinity in Ligand Binding to Galectin-3C.

Molecular recognition is fundamental to biological signaling. A central question is how individual interactions between molecular moieties affect the thermodynamics of ligand binding to proteins and how these effects might propagate beyond the immediate neighborhood of the binding site. Here, we investigate this question by introducing minor changes in ligand structure and characterizing the effects of these on ligand affinity to the carbohydrate recognition domain of galectin-3, using a combination of isothermal titration calorimetry, X-ray crystallography, NMR relaxation, and computational approaches including molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). We studied a congeneric series of ligands with a fluorophenyl-triazole moiety, where the fluorine substituent varies between the ortho, meta, and para positions (denoted O, M, and P). The M and P ligands have similar affinities, whereas the O ligand has 3-fold lower affinity, reflecting differences in binding enthalpy and entropy. The results reveal surprising differences in conformational and solvation entropy among the three complexes. NMR backbone order parameters show that the O-bound protein has reduced conformational entropy compared to the M and P complexes. By contrast, the bound ligand is more flexible in the O complex, as determined by 19F NMR relaxation, ensemble-refined X-ray diffraction data, and MD simulations. Furthermore, GIST calculations indicate that the O-bound complex has less unfavorable solvation entropy compared to the other two complexes. Thus, the results indicate compensatory effects from ligand conformational entropy and water entropy, on the one hand, and protein conformational entropy, on the other hand. Taken together, these different contributions amount to entropy–entropy compensation among the system components involved in ligand binding to a target protein.

Ligand Gaussian Accelerated Molecular Dynamics (LiGaMD) for Characterization of Ligand Binding Thermodynamics and Kinetics

Calculations of ligand binding free energies and kinetic rates are important for drug design. However, such tasks have proven challenging in computational chemistry and biophysics. To address this challenge, we have developed a new computational method “LiGaMD”, which selectively boosts the ligand non-bonded interaction potential energy based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique. Another boost potential could be applied to the remaining potential energy of the entire system in a dual-boost algorithm (LiGaMD_Dual) to facilitate ligand binding.

Submolecular probing of the complement C5a receptor\u2013ligand binding reveals a cooperative two-site binding mechanism

A current challenge to produce effective therapeutics is to accurately determine the location of the ligand-biding site and to characterize its properties. So far, the mechanisms underlying the functional activation of cell surface receptors by ligands with a complex binding mechanism remain poorly understood due to a lack of suitable nanoscopic methods to study them in their native environment. Here, we elucidated the ligand-binding mechanism of the human G protein-coupled C5a receptor (C5aR). We discovered for the first time a cooperativity between the two orthosteric binding sites. We found that the N-terminus C5aR serves as a kinetic trap, while the transmembrane domain acts as the functional site and both contributes to the overall high-affinity interaction. In particular, Asp282 plays a key role in ligand binding thermodynamics, as revealed by atomic force microscopy and steered molecular dynamics simulation. Our findings provide a new structural basis for the functional and mechanistic understanding of the GPCR family that binds large macromolecular ligands.

Ligand Gaussian Accelerated Molecular Dynamics (LiGaMD): Characterization of Ligand Binding Thermodynamics and Kinetics.

Calculations of ligand binding free energies and kinetic rates are important for drug design. However, such tasks have proven challenging in computational chemistry and biophysics. To address this challenge, we have developed a new computational method, ligand Gaussian accelerated molecular dynamics (LiGaMD), which selectively boosts the ligand nonbonded interaction potential energy based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique. Another boost potential could be applied to the remaining potential energy of the entire system in a dual-boost algorithm (LiGaMD_Dual) to facilitate ligand binding. LiGaMD has been demonstrated on host-guest and protein-ligand binding model systems. Repetitive guest binding and unbinding in the β-cyclodextrin host were observed in hundreds-of-nanosecond LiGaMD_Dual simulations. The calculated guest binding free energies agreed excellently with experimental data with <1.0 kcal/mol errors. Compared with converged microsecond-time scale conventional molecular dynamics simulations, the sampling errors of LiGaMD_Dual simulations were also <1.0 kcal/mol. Accelerations of ligand kinetic rate constants in LiGaMD simulations were properly estimated using Kramers' rate theory. Furthermore, LiGaMD allowed us to capture repetitive dissociation and binding of the benzamidine inhibitor in trypsin within 1 μs simulations. The calculated ligand binding free energy and kinetic rate constants compared well with the experimental data. In summary, LiGaMD provides a powerful enhanced sampling approach for characterizing ligand binding thermodynamics and kinetics simultaneously, which is expected to facilitate computer-aided drug design.

Life under Extreme Conditions: Aeropyrum pernix and Pernisine

Life under Extreme Conditions: Aeropyrum pernix and Pernisine

Ligand binding free energy and kinetics calculation in 2020

AbstractLigand/protein binding (LPB) is a major topic in medicine, chemistry and biology. Since the advent of computers, many scientists have put efforts in developing theoretical models that could decode the alphabet of the LPB interaction. The success of this task passes by the resolution of the molecular mechanism of LPB. In the past century, major attention was dedicated to the thermodynamics of LPB, while more recent studies have revealed that ligand (un)binding kinetics is at least as important as ligand binding thermodynamics in determining the drug in vivo efficacy. In the present review, we introduce the most widely used computational methods to study LPB thermodynamics and kinetics. It is important to say that no method outperforms another, they all have pros and cons and the choice of the user should take carefully into account the system under investigation, the available structural and experimental data, and the goal of the research. A perspective on future directions of method development and research on LPB concludes the discussion.This article is categorized under: Molecular and Statistical Mechanics &gt; Free Energy Methods Structure and Mechanism &gt; Computational Biochemistry and Biophysics Molecular and Statistical Mechanics &gt; Molecular Dynamics and Monte‐Carlo Methods