Distribution Of Protein Conformations Research Articles

High-throughput prediction of protein conformational distributions with subsampled AlphaFold2

This paper presents an innovative approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins’ ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against nuclear magnetic resonance experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, analysis of experimental results, and predicting evolution.

Predicted and Experimental NMR Chemical Shifts at Variable Temperatures: The Effect of Protein Conformational Dynamics.

NMR chemical shifts provide a sensitive probe of protein structure and dynamics but remain challenging to predict and interpret. We examine the effect of protein conformational distributions on 15N chemical shifts for dihydrofolate reductase (DHFR), comparing QM/MM predicted shifts with experimental shifts in solution as well as frozen distributions. Representative snapshots from MD trajectories exhibit variation in predicted 15N chemical shifts of up to 25 ppm. The average over the fluctuations is in significantly better agreement with room temperature solution experimental values than the prediction for any single optimal conformations. Meanwhile, solid-state NMR (SSNMR) measurements of frozen solutions at 105 K exhibit broad lines whose widths agree well with the widths of distributions of predicted shifts for samples from the trajectory. The backbone torsion angle ψi-1 varies over 60° on the picosecond time scale, compensated by φi. These fluctuations can explain much of the shift variation.

End-to-end protein–ligand complex structure generation with diffusion-based generative models

BackgroundThree-dimensional structures of protein–ligand complexes provide valuable insights into their interactions and are crucial for molecular biological studies and drug design. However, their high-dimensional and multimodal nature hinders end-to-end modeling, and earlier approaches depend inherently on existing protein structures. To overcome these limitations and expand the range of complexes that can be accurately modeled, it is necessary to develop efficient end-to-end methods.ResultsWe introduce an equivariant diffusion-based generative model that learns the joint distribution of ligand and protein conformations conditioned on the molecular graph of a ligand and the sequence representation of a protein extracted from a pre-trained protein language model. Benchmark results show that this protein structure-free model is capable of generating diverse structures of protein–ligand complexes, including those with correct binding poses. Further analyses indicate that the proposed end-to-end approach is particularly effective when the ligand-bound protein structure is not available.ConclusionThe present results demonstrate the effectiveness and generative capability of our end-to-end complex structure modeling framework with diffusion-based generative models. We suppose that this framework will lead to better modeling of protein–ligand complexes, and we expect further improvements and wide applications.

Accessing protein conformational distributions in mammalian cells with fast, bio-orthogonal spin-labeling and DEER spectroscopy

The ability to measure protein structure and dynamics directly within the cellular environment is fundamental to understanding the molecular mechanisms of protein function and dysfunction. Site-directed spin-labeling, in combination with double electron-electron resonance (DEER) spectroscopy, is a powerful method for determining both the structural states and the conformational equilibria of biomacromolecules. The application of DEER to expressed proteins within cells, however, has been hindered by issues of sensitivity, toxicity, specificity and extent of labeling, and spin-label stability.

Thermal Adaptation of Enzymes: Impacts of Conformational Shifts on Catalytic Activation Energy and Optimum Temperature.

Thermal adaptation of enzymes is essential for both living organism development in extreme conditions and efficient biocatalytic applications. However, the molecular mechanisms leading to a shift in catalytic activity optimum temperatures remain unclear, and there is increasing experimental evidence that thermal adaptation involves complex changes in both structural and reactive properties. Here, a combination of enhanced protein conformational sampling with an explicit chemical reaction description was applied to mesophilic and thermophilic homologues of the dihydrofolate reductase enzyme, and a quantitative description of the stability and catalytic activity shifts between homologues was obtained. The key role played by temperature-induced shifts in protein conformational distributions is revealed. In contrast with pictures focusing on protein flexibility and dynamics, it is shown that while the homologues' reaction free energies are similar, the striking discrepancy between their activation energies is caused by their different conformational changes with temperature. An analytic model is proposed that combines catalytic activity and structural stability, and which quantitatively predicts the shift in homologue optimum temperatures. It is shown that this general model provides a molecular explanation of changes in optimum temperatures for several other enzymes.

Kinetic regulation of multi-ligand binding proteins

BackgroundSecond messengers, such as calcium, regulate the activity of multisite binding proteins in a concentration-dependent manner. For example, calcium binding has been shown to induce conformational transitions in the calcium-dependent protein calmodulin, under steady state conditions. However, intracellular concentrations of these second messengers are often subject to rapid change. The mechanisms underlying dynamic ligand-dependent regulation of multisite proteins require further elucidation.ResultsIn this study, a computational analysis of multisite protein kinetics in response to rapid changes in ligand concentrations is presented. Two major physiological scenarios are investigated: i) Ligand concentration is abundant and the ligand-multisite protein binding does not affect free ligand concentration, ii) Ligand concentration is of the same order of magnitude as the interacting multisite protein concentration and does not change. Therefore, buffering effects significantly influence the amounts of free ligands. For each of these scenarios the influence of the number of binding sites, the temporal effects on intermediate apo- and fully saturated conformations and the multisite regulatory effects on target proteins are investigated.ConclusionsThe developed models allow for a novel and accurate interpretation of concentration and pressure jump-dependent kinetic experiments. The presented model makes predictions for the temporal distribution of multisite protein conformations in complex with variable numbers of ligands. Furthermore, it derives the characteristic time and the dynamics for the kinetic responses elicited by a ligand concentration change as a function of ligand concentration and the number of ligand binding sites. Effector proteins regulated by multisite ligand binding are shown to depend on ligand concentration in a highly nonlinear fashion.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell.

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

The importance of ensemble averaging in enzyme kinetics.

ConspectusThe active site of an enzyme is surrounded by a fluctuating environment of protein and solvent conformational states, and a realistic calculation of chemical reaction rates and kinetic isotope effects of enzyme-catalyzed reactions must take account of this environmental diversity. Ensemble-averaged variational transition state theory with multidimensional tunneling (EA-VTST/MT) was developed as a way to carry out such calculations. This theory incorporates ensemble averaging, quantized vibrational energies, energy, tunneling, and recrossing of transition state dividing surfaces in a systematic way. It has been applied successfully to a number of hydrogen-, proton-, and hydride-transfer reactions. The theory also exposes the set of effects that should be considered in reliable rate constants calculations.We first review the basic theory and the steps in the calculation. A key role is played by the generalized free energy of activation profile, which is obtained by quantizing the classical potential of mean force as a function of a reaction coordinate because the one-way flux through the transition state dividing surface can be written in terms of the generalized free energy of activation. A recrossing transmission coefficient accounts for the difference between the one-way flux through the chosen transition state dividing surface and the net flux, and a tunneling transmission coefficient converts classical motion along the reaction coordinate to quantum mechanical motion. The tunneling calculation is multidimensional, accounting for the change in vibrational frequencies along the tunneling path and shortening of the tunneling path with respect to the minimum energy path (MEP), as promoted by reaction-path curvature. The generalized free energy of activation and the transmission coefficients both involve averaging over an ensemble of reaction paths and conformations, and this includes the coupling of protein motions to the rearrangement of chemical bonds in a statistical mechanically correct way. The standard deviations of the transmissions coefficients provide information on the diversity of the distribution of reaction paths, barriers, and protein conformations along the members of an ensemble of reaction paths passing through the transition state.We first illustrate the theory by discussing the application to both wild-type and mutant Escherichia coli dihydrofolate reductase and hyperthermophilic Thermotoga maritima dihydrofolate reductase (DHFR); DHFR is of special interest because the protein conformational changes have been widely studied. Then we present shorter discussions of several other applications of EA-VTST/MT to transfer of protons, hydrogen atoms, and hydride ions and their deuterated analogs. Systems discussed include hydride transfer in alcohol dehydrogenase, xylose isomerase, and thymidylate synthase, proton transfer in methylamine dehydrogenase, hydrogen atom transfer in methylmalonyl-CoA mutase, and nucleophilic substitution in haloalkane dehalogenase and two-dimensional potentials of mean force for potentially coupled proton and hydride transfer in the β-oxidation of butyryl-coenzyme A catalyzed by short-chain acyl-CoA dehydrogenase and in the pyruvate to lactate transformation catalyzed by lactate dehydrogenase.

What is the shape of the distribution of protein conformations at equilibrium?

According to the thermodynamic hypothesis, the native state of proteins is that in which the free energy of the system is at its lowest, so that at normal temperature and pressure, proteins evolve to that state. We selected four proteins representative of each of the four classes, and for each protein make four simulations, one starting from the native structure and the other three starting from the structure obtained by threading the sequence of one protein onto the native backbone fold of the other three proteins. Because of their large conformational distances with respect to the native structure, the three alternative initial structures cannot be considered as local minima within the native ensemble of the corresponding protein. As expected, the initial native states are preserved in the .5 μs simulations performed here and validate the simulations. On the other hand, when the initial state is not native, an analysis of the trajectories does not reveal any evolution towards the native state, during that time. These results indicate that the distribution of protein conformations is multipeak shaped, so that apart from the peak corresponding to the native state, there are other peaks associated with average structures that are very different from the native and that can last as long as the native state.

Exploring regions of conformational space occupied by two-domain proteins.

The presence of heterogeneity in the interdomain arrangement of several biomolecules is required for their function. Here we present a method to obtain crucial clues to distinguish between different kinds of protein conformational distributions based on experimental NMR data. The method explores subregions of the conformational space and provides both upper and lower bounds of probability for the system to be in each subregion.

Distribution, Transition and Thermodynamic Stability of Protein Conformations in the Denaturant-Induced Unfolding of Proteins

BackgroundExtensive and intensive studies on the unfolding of proteins require appropriate theoretical model and parameter to clearly illustrate the feature and characteristic of the unfolding system. Over the past several decades, four approaches have been proposed to describe the interaction between proteins and denaturants, but some ambiguity and deviations usually occur in the explanation of the experimental data.Methodology/Principal FindingsIn this work, a theoretical model was presented to show the dependency of the residual activity ratio of the proteins on the molar denaturant concentration. Through the characteristic unfolding parameters k i and Δm i in this model, the distribution, transition and thermodynamic stability of protein conformations during the unfolding process can be quantitatively described. This model was tested with the two-state unfolding of bovine heart cytochrome c and the three-state unfolding of hen egg white lysozyme induced by both guanidine hydrochloride and urea, the four-state unfolding of bovine carbonic anhydrase b induced by guanidine hydrochloride and the unfolding of some other proteins induced by denaturants. The results illustrated that this model could be used accurately to reveal the distribution and transition of protein conformations in the presence of different concentrations of denaturants and to evaluate the unfolding tendency and thermodynamic stability of different conformations. In most denaturant-induced unfolding of proteins, the unfolding became increasingly hard in next transition step and the proteins became more unstable as they attained next successive stable conformation.Conclusions/SignificanceThis work presents a useful method for people to study the unfolding of proteins and may be used to describe the unfolding and refolding of other biopolymers induced by denaturants, inducers, etc.

The Cysteine-rich Region of Type VII Collagen Is a Cystine Knot with a New Topology

Collagens are a group of extracellular matrix proteins with essential functions for skin integrity. Anchoring fibrils are made of type VII collagen (Col7) and link different skin layers together: the basal lamina and the underlying connective tissue. Col7 has a central collagenous domain and two noncollagenous domains located at the N and C terminus (NC1 and NC2), respectively. A cysteine-rich region of hitherto unknown function is located at the transition of the NC1 domain to the collagenous domain. A synthetic model peptide of this region was investigated by CD and NMR spectroscopy. The peptide folds into a collagen triple helix, and the cysteine residues form disulfide bridges between the different strands. The eight cystine knot topologies that are characterized by exclusively intermolecular disulfide bridges have been analyzed by molecular modeling. Two cystine knots are energetically preferred; however, all eight disulfide bridge arrangements are essentially possible. This novel cystine knot is present in type IX collagen, too. The conserved motif of the cystine knot is CX3CP. The cystine knot is N-terminal to the collagen triple helix in both collagens and therefore probably impedes unfolding of the collagen triple helix from the N terminus.

Measuring Protein Dynamics and Mechanism using Infrared Spectroscopy

Infrared spectroscopy has long been used to deduce concentration and structural descriptions of proteins in a variety of static and time resolved experiments. Our focus is on developing new infrared methods to compare the structure, dynamics and function of nearly identical protein samples. We have developed an order parameter describing protein conformation variations around the average molecular values. Here we apply our order parameter to the problem of characterizing membrane protein function and the efficacy of membrane protein reconstitution in different environments. By comparing our order parameter and amide hydrogen/deuterium exchange methods, we explore the relationship between protein stability and the dynamics of the protein conformational distribution. Examples include lysozyme and albumin in solution, and cytochrome c interacting with lipid membranes of varying net-negative surface charge density. We have recently extended our work to the characterization of both native and crystalline forms of bacteriorhodopsin during its photocycle.

Deciphering Protein Stability in Cells

Deciphering Protein Stability in Cells

Magic-angle-spinning NMR techniques for measuring long-range distances in biological macromolecules.

The determination of molecular structures using solid-state NMR spectroscopy requires distance measurement through nuclear-spin dipole-dipole couplings. However, most dipole-coupling techniques compete with the transverse (T2) relaxation of the nuclear spins, whose time constants are at most several tens of milliseconds, which limits the ability to measure weak dipolar couplings or long distances. In the last 10 years, we have developed a number of magic-angle-spinning (MAS) solid-state NMR techniques to measure distances of 15-20 Å. These methods take advantage of the high gyromagnetic ratios of (1)H and (19)F spins, multispin effects that speed up dipolar dephasing, and (1)H and (19)F spin diffusion that probes distances in the nanometer range. Third-spin heteronuclear detection provides a method for determining (1)H dipolar couplings to heteronuclear spins. We have used this technique to measure hydrogen-bond lengths, torsion angles, the distribution of protein conformations, and the oligomeric assembly of proteins. We developed a new pulse sequence, HARDSHIP, to determine weak long-range (1)H-heteronuclear dipolar couplings in the presence of strong short-range couplings. This experiment allows us to determine crystallite thicknesses in biological nanocomposites such as bone. The rotational-echo double-resonance (REDOR) technique allows us to detect multispin (13)C-(31)P and (13)C-(2)H dipolar couplings. Quantitative analysis of these couplings provides information about the structure of peptides bound to phospholipid bilayers and the geometry of ligand-binding sites in proteins. Finally, we also use relayed magnetization transfer, or spin diffusion, to measure long distances. z-Magnetization can diffuse over several nanometers because its long T1 relaxation times allow it to survive for hundreds of milliseconds. We developed (1)H spin diffusion to probe the depths of protein insertion into the lipid bilayer and protein-water interactions. On the other hand, (19)F spin diffusion of site-specifically fluorinated molecules allowed us to elucidate the oligomeric structures of membrane peptides.

Dual Effect of Phosphatidyl (4,5)-Bisphosphate PIP2 on Shaker K+ Channels

Dual Effect of Phosphatidyl (4,5)-Bisphosphate PIP2 on Shaker K+ Channels

Temperature and solvent dependence of the dynamical landscape of tau protein conformations.

We report the variation with temperature of the ensemble distribution of conformations spanned by the tau protein in its dynamical states measured by small-angle X-ray scattering (SAXS) using synchrotron radiation. The SAXS data show a clear temperature variation of the distribution of occupied protein conformations from 293 to 318K. More conformations with a smaller radius of gyration are occupied at higher temperature. The protein-solvent interactions are shown by computer simulation to be essential for controlling the dynamics of protein conformations, providing evidence for the key role of water solvent in the protein dynamics, as proposed by Giorgio Careri.

Modeling the Membrane Role in Ca2+-ATPase Catalytic Cycle

A deep understanding of the function of membrane proteins requires that we understand the direct and indirect effects of the lipid environment. Deformations of the bilayer to accommodate the protein induce energy penalties and potentially change the free energy between conformational states and thereby change the distribution of protein conformations. The lipid bilayer thus plays a regulatory role for the function of a membrane protein.Structures of the Ca2+-ATPase from sarcoplasmic reticulum, SERCA, have been determined by X-ray crystallography in several different functional states. These structures have provided a unique opportunity to study how the protein interacts with the membrane throughout the functional cycle by all-atom molecular dynamics (MD) simulations.MD simulations have been performed with four different structures of SERCA representing a Ca2+- and ATP-bound state (Ca2E1-ATP); a state with the luminal Ca2+-exit path open and the protein phosphorylated (E2P); and two dephosphorylated occluded states with bound protons, one with inorganic phosphor still bound (E2-Pi) and one without (E2). Our results show how the POPC-membrane and the protein in different functional states undergo mutual adaption (see figure) and how the hydrophobic mismatch and protein area profile change during the functional cycle.View Large Image | View Hi-Res Image | Download PowerPoint Slide

Peptide Conformer Acidity Analysis of Protein Flexibility Monitored by Hydrogen Exchange

The amide hydrogens that are exposed to solvent in the high-resolution X-ray structures of ubiquitin, FK506-binding protein, chymotrypsin inhibitor 2, and rubredoxin span a billion-fold range in hydroxide-catalyzed exchange rates which are predictable by continuum dielectric methods. To facilitate analysis of transiently accessible amides, the hydroxide-catalyzed rate constants for every backbone amide of ubiquitin were determined under near physiological conditions. With the previously reported NMR-restrained molecular dynamics ensembles of ubiquitin (PDB codes 2NR2 and 2K39) used as representations of the Boltzmann-weighted conformational distribution, nearly all of the exchange rates for the highly exposed amides were more accurately predicted than by use of the high-resolution X-ray structure. More strikingly, predictions for the amide hydrogens of the NMR relaxation-restrained ensemble that become exposed to solvent in more than one but less than half of the 144 protein conformations in this ensemble were almost as accurate. In marked contrast, the exchange rates for many of the analogous amides in the residual dipolar coupling-restrained ubiquitin ensemble are substantially overestimated, as was particularly evident for the Ile 44 to Lys 48 segment which constitutes the primary interaction site for the proteasome targeting enzymes involved in polyubiquitylation. For both ensembles, “excited state” conformers in this active site region having markedly elevated peptide acidities are represented at a population level that is 102 to 103 above what can exist in the Boltzmann distribution of protein conformations. These results indicate how a chemically consistent interpretation of amide hydrogen exchange can provide insight into both the population and the detailed structure of transient protein conformations.

Curvature Dependence of Viral Protein Structures on Encapsidated Nanoemulsion Droplets

Virus-like particles are biomimetic delivery vehicles that cloak nanoscale cores inside coatings of viral capsid proteins, offering the potential for protecting their contents and targeting them to particular tissues and cells. To date, encapsidation has been demonstrated only for a relatively limited variety of core materials, such as compressible polymers and facetted nanocrystals, over a narrow range of cores sizes and of pH and ionic strength. Here, we encapsidate spherical nanodroplets of incompressible oil stabilized by adsorbed anionic surfactant using cationic capsid protein purified from cowpea chlorotic mottle virus. By imaging with transmission electron microscopy we show that, as the droplets become larger than the wild-type RNA core, the protein is forced to self-assemble into spherical shells that are not perfect icosahedra having special triangulation numbers characteristic of the Caspar-Klug hierarchy. Consequently, the distribution of protein conformations on larger droplets is significantly different than in the wild-type shell.