Dynamic Allostery Research Articles

Load-based divergence in the dynamic allostery of two TCRs recognizing the same pMHC.

Increasing evidence suggests that mechanical load on the αβ T cell receptor (TCR) is crucial for recognizing the antigenic peptide-loaded major histocompatibility complex (pMHC) molecule. Our recent all-atom molecular dynamics (MD) simulations revealed that the inter-domain motion of the TCR is responsible for the load-induced catch bond behavior of the TCR-pMHC complex and peptide discrimination. To further examine the generality of the mechanism, we perform all-atom MD simulations of the B7 TCR under different conditions for comparison with our previous simulations of the A6 TCR. The two TCRs recognize the same pMHC and have similar interfaces with pMHC in crystal structures. We find that the B7 TCR-pMHC interface stabilizes under ∼15-pN load using a conserved dynamic allostery mechanism that involves the asymmetric motion of the TCR chassis. However, despite forming comparable contacts with pMHC as A6 in the crystal structure, B7 has fewer high-occupancy contacts with pMHC during the simulation. These results suggest that the dynamic allostery common to the TCR αβ chassis can amplify slight differences in interfacial contacts into distinctive mechanical responses and potentially nuanced biological outcomes.

Dynamic allostery drives autocrine and paracrine TGF-β signaling

TGF-β, essential for development and immunity, is expressed as a latent complex (L-TGF-β) non-covalently associated with its prodomain and presented on immune cell surfaces by covalent association with GARP. Binding to integrin αvβ8 activates L-TGF-β1/GARP. The dogma is that mature TGF-β must physically dissociate from L-TGF-β1 for signaling to occur. Our previous studies discovered that αvβ8-mediated TGF-β autocrine signaling can occur without TGF-β1 release from its latent form. Here, we show that mice engineered to express TGF-β1 that cannot release from L-TGF-β1 survive without early lethal tissue inflammation, unlike those with TGF-β1 deficiency. Combining cryogenic electron microscopy with cell-based assays, we reveal a dynamic allosteric mechanism of autocrine TGF-β1 signaling without release where αvβ8 binding redistributes the intrinsic flexibility of L-TGF-β1 to expose TGF-β1 to its receptors. Dynamic allostery explains the TGF-β3 latency/activation mechanism and why TGF-β3 functions distinctly from TGF-β1, suggesting that it broadly applies to other flexible cell surface receptor/ligand systems.

N-terminal domain of polypyrimidine-tract binding protein is a dynamic folding platform for adaptive RNA recognition.

The N-terminal RNA recognition motif domain (RRM1) of polypyrimidine tract binding protein (PTB) forms an additional C-terminal helix α3, which docks to one edge of the β-sheet upon binding to a stem-loop RNA containing a UCUUU pentaloop. Importantly, α3 does not contact the RNA. The α3 helix therefore represents an allosteric means to regulate the conformation of adjacent domains in PTB upon binding structured RNAs. Here we investigate the process of dynamic adaptation by stem-loop RNA and RRM1 using NMR and MD in order to obtain mechanistic insights on how this allostery is achieved. Relaxation data and NMR structure determination of the free protein show that α3 is partially ordered and interacts with the domain transiently. Stem-loop RNA binding quenches fast time scale dynamics and α3 becomes ordered, however microsecond dynamics at the protein-RNA interface is observed. MD shows how RRM1 binding to the stem-loop RNA is coupled to the stabilization of the C-terminal helix and helps to transduce differences in RNA loop sequence into changes in α3 length and order. IRES assays of full length PTB and a mutant with altered dynamics in the α3 region show that this dynamic allostery influences PTB function in cultured HEK293T cells.

The immune response of nano carbon-based photic-driving vaccines to severe acute respiratory syndrome coronavirus 2

As the most severe novel infectious disease in this century, coronavirus disease 2019 (COVID-19) faces tremendous challenges due to the hysteresis of drugs and vaccine development. Elucidating the panoramic mechanism of coronavirus-host immune interaction is a strategy for disease surveillance, diagnosis, treatment, prevention, and immunity assessment of COVID-19. A robust carbon nanotube (CNT)-based photic vaccine technology contributes to address the core scientific issues of these challenges. This perspective states the latest prevention and control strategy of CNT-based photic vaccine and its broad-spectrum resistance to high transmissible and pathogenic variants. Furthermore, this perspective covers the potential immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) under the CNT-based photic vaccine intervention and finally evaluates its efficacy and the underlying interactive mechanisms. In the future, findings of the highly efficient and conservative T cell epitopes depending on an intelligent chem-physical modulation would provide a promising basis for the development of next generation vaccines. Ideally, these next generation vaccines are prone to be with the function of dynamic allostery responding to the chem-physical changing and present the allosteric epitopes which are affinity to the viral variation.

Calcium mediated static and dynamic allostery in S100A12: Implications for target recognition by S100 proteins.

Structure and functions of S100 proteins are regulated by two distinct calcium binding EF hand motifs. In this work, we used solution-state NMR spectroscopy to investigate the cooperativity between the two calcium binding sites and map the allosteric changes at the target binding site. To parse the contribution of the individual calcium binding events, variants of S100A12 were designed to selectively bind calcium to either the EF-I (N63A) or EF-II (E31A) loop, respectively. Detailed analysis of the backbone chemical shifts for wildtype protein and its mutants indicates that calcium binding to the canonical EF-II loop is the principal trigger for the conformational switch between 'closed' apo to the 'open' Ca2+ -bound conformation of the protein. Elimination of binding in S100-specific EF-I loop has limited impact on the calcium binding affinity of the EF-II loop and the concomitant structural rearrangement. In contrast, deletion of binding in the EF-II loop significantly attenuates calcium affinity in the EF-I loop and the structure adopts a 'closed' apo-like conformation. Analysis of experimental amide nitrogen (15 N) relaxation rates (R1 , R2 , and 15 N-{1 H} NOE) and molecular dynamics (MD) simulations demonstrate that the calcium bound state is relatively floppy with pico-nanosecond motions induced in functionally relevant domains responsible for target recognition such as the hinge domain and the C-terminal residues. Experimental relaxation studies combined with MD simulations show that while calcium binding in the EF-I loop alone does not induce significant motions in the polypeptide chain, EF-I regulates fluctuations in the polypeptide in the presence of bound calcium in the EF-II loop. These results offer novel insights into the dynamic regulation of target recognition by calcium binding and unravels the role of cooperativity between the two calcium binding events in S100A12.

Dynamic allostery through the lens of protein evolution

Dynamic allostery through the lens of protein evolution

Dynamic allostery and thrombin: Insights from modeling mutants, ions and binding using molecular dynamics, statistical analysis and machine learning

Dynamic allostery and thrombin: Insights from modeling mutants, ions and binding using molecular dynamics, statistical analysis and machine learning

Dynamic correlations: exact and approximate methods for mutual information.

Proteins are dynamic entities that undergo conformational changes critical for their functions. Understanding the communication pathways and information transfer within proteins is crucial for elucidating allosteric interactions in their mechanisms. This study utilizes mutual information (MI) analysis to probe dynamic allostery. Using two cases, Ubiquitin and PLpro, we have evaluated the accuracy and limitations of different approximations including the exact anisotropic and isotropic models, multivariate Gaussian model, isotropic Gaussian model, and the Gaussian Network Model (GNM) in revealing allosteric interactions. Our findings emphasize the required trajectory length for capturing accurate mutual information profiles. Long molecular dynamics trajectories, 1 ms for Ubiquitin and 100 µs for PLpro are used as benchmarks, assuming they represent the ground truth. Trajectory lengths of approximately 5 µs for Ubiquitin and 1 µs for PLpro marked the onset of convergence, while the multivariate Gaussian model accurately captured mutual information with trajectories of 5 ns for Ubiquitin and 350 ns for PLpro. However, the isotropic Gaussian model is less successful in representing the anisotropic nature of protein dynamics, particularly in the case of PLpro, highlighting its limitations. The GNM, however, provides reasonable approximations of long-range information exchange as a minimalist network model based on a single crystal structure. Overall, the optimum trajectory lengths for effective Gaussian approximations of long-time dynamic behavior depend on the inherent dynamics within the protein's topology. The GNM, by showcasing dynamics across relatively diverse time scales, can be used either as a standalone method or to gauge the adequacy of MD simulation lengths. Mutual information codes are available at https://github.com/kemaldemirtas/prc-MI.git.

Dynamic allostery of rhodopsin activation in lipid membranes

Dynamic allostery of rhodopsin activation in lipid membranes

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors.

G-protein-coupled receptors (GPCRs) make up the largest superfamily of human membrane proteins and represent primary targets of ∼1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon the binding of positive and negative allosteric modulators (PAMs and NAMs). The mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy prOfiling Workflow (GLOW). GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence and absence of the modulator. DL and free energy calculations revealed significantly reduced dynamic fluctuations and conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G-protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes. Therefore, GPCR allostery exhibits a dynamic "conformational selection" mechanism. In the absence of available modulator-bound structures as for most current GPCRs, it is critical to use a structural ensemble of representative GPCR conformations rather than a single structure for compound docking ("ensemble docking"), which will potentially improve structure-based design of novel allosteric drugs of GPCRs.

Relation between flexibility and intrinsically disorder regions in thermosensitive TRP channels reveal allosteric effects.

How a protein propagates the conformational changes throughout its structure remains largely unknown. In thermosensitive TRP channels, this allosteric communication is triggered by ligand interaction or in response to temperature changes. Because dynamic allostery suggests a dynamic role of disordered regions, in this work we set out to thoroughly evaluate these regions in six thermosensitive TRP channels. Thus, by contrasting the intrinsic flexibility of the transmembrane region as a function of the degree of disorder in those proteins, we discovered several residues that do not show a direct correlation in both parameters. This kind of structural discrepancy revealed residues that are either reported to be dynamic, functionally relevant or are involved in signal propagation and probably part of allosteric networks. These discrepant, potentially dynamic regions are not exclusive of TRP channels, as this same correlation was found in the Kv Shaker channel.

Dynamic allostery in thrombin-a review.

Thrombin is a serine protease that catalyzes a large number of different reactions including proteolytic cleave of fibrinogen to make the fibrin clot (procoagulant activity), of the protease activated receptors (for cell signaling) and of protein C generating activated protein C (anticoagulant activity). Thrombin has an effector binding site called the anion binding exosite 1 that is allosterically coupled to the active site. In this review, we survey results from thermodynamic characterization of the allosteric coupling as well as hydrogen-deuterium exchange mass spectrometry to reveal which parts of the thrombin structure are changed upon effector binding and/or mutagenesis, and finally NMR spectroscopy to characterize the different timescales of motions elicited by the effectors. We also relate the experimental work to computational network analysis of the thrombin-thrombomodulin complex.

Perspective: How Fast Dynamics Affect Slow Function in Protein Machines.

Internal motions in proteins take place on a broad range of time- and space-scales. The potential roles of these dynamics in the biochemical functions of proteins have intrigued biophysicists for many years, and multiple mechanisms to couple motions to function have been proposed. Some of these mechanisms have relied on equilibrium concepts. For example, the modulation of dynamics was proposed to change the entropy of a protein, hence affecting processes such as binding. This so-called dynamic allostery scenario has been demonstrated in several recent experiments. Perhaps even more intriguing may be models that involve out-of-equilibrium operation, which by necessity require the input of energy. We discuss several recent experimental studies that expose such potential mechanisms for coupling dynamics and function. In Brownian ratchets, for example, directional motion is promoted by switching a protein between two free energy surfaces. An additional example involves the effect of microsecond domain-closure dynamics of an enzyme on its much slower chemical cycle. These observations lead us to propose a novel two-time-scale paradigm for the activity of protein machines: fast equilibrium fluctuations take place on the microsecond-millisecond time scale, while on a slower time scale, free energy is invested in order to push the system out of equilibrium and drive functional transitions. Motions on the two time scales affect each other and are essential for the overall function of these machines.

Human versus mouse Beta 2 microglobulin alters TCR antigen recognition kinetics with mouse MHCI

Abstract There are three isoforms of Beta2 microglobulin (B2m) identified in mice and they differ by a single amino acid residue. To study how B2m can modify the peptide binding pocket of MHCI we turned to the comparison of mouse (mB2m) and human (hB2m). It is known that hB2m forms more stable with mouse MHCI heavy chain as compared to mb2m and hB2m is often the choice for most pMHCI tetramer production. Analysis of mB2m and hB2m tetramer (GP33 41M) following LCMV infection revealed no difference in percentage of tetramer positive cells but an increase was observed in staining intensity (MFI) of hB2m. Using steered molecular dynamics we found that there were allosteric effects with mB2m displaying more movement within the binding pocket than hB2m. Consistent with this we saw increased 2D affinity for antigen MHC D band K bhB2m complexes for OT1 and P14 TCRs, respectively. We also measured the force effects on bond lifetime between TCR and pMHC using biomembrane force probe (BFP) and DNA tension sensor. For OTI, we found that mB2m complexes had a longer bond lifetime measured by both methods. We observed signaling and functional effects consistent with the 2D affinity and bond lifetime measurements in mouse verses human B2m. For example, mB2m leads to increased levels of activated LCK (pY394/505) in OT1 T cells. Therefore, alterations in B2m effect the distal peptide binding domain of MHCI and suggests dynamic allostery may influence antigen recognition by TCR. 5T32NS115664-03 5R01AI147641-03

Rhodopsin is a dynamically active receptor in lipid membranes.

G-protein-coupled receptors transmit signals across cellular membranes and regulate multiple biological functions with rhodopsin as an important prototype. Here we investigated the distribution of substates in rhodopsin activation unavailable by X-ray crystallography due to use of cryogenic temperatures and absence of the membrane environment [1]. Our hypothesis was that activation involves dynamic allostery whereby an ensemble of states is affected by the membrane soft matter (lipids and water) as well as pH and temperature [1-3]. We investigated rhodopsin in native retinal disk membranes and POPC or DOPC lipids using FTIR and UV-visible spectroscopy. By observing the pH dependence of the activating transition for various spectroscopic bands, we determined the distributions of states upon photoactivation. Data reduction and analysis of pH titration curves revealed equilibrium constants and thermodynamic parameters for the transition from inactive Meta-I to the active Meta-II state. Furthermore, we calculated the distribution of pKa and alkaline end-point values at all wave numbers of FTIR spectra where intensities change upon activation. We discovered that temperature not only shifts the rhodopsin equilibrium to the active state, but also enables coexistence of multiple inactive and active states. Our data support the concept of a dynamically active receptor, where the equilibrium of substates facilitates the high reaction rate for the next vision step (transducin activation). The calculated enthalpy and entropy values suggest partial unfolding of the receptor when forming of the active Meta-II state. Our results are consistent with the idea of activated rhodopsin as a conformational ensemble of states representing different tiers of the energy landscape, which are partially determined by an enthalpy-entropy folding funnel.

Influential nodes drive dynamic allostery in protein tyrosine phosphatases.

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study we employ this perspective to answer a basic question: in enzyme superfamilies where the catalytic mechanism, active site, and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? In this work, we focus on Protein Tyrosine Phosphatases as exemplified by the prototypical PTP1B, showing that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We compare PTP1B's dynamics with another popular superfamily member YopH (from Yersinia pestis) and a lesser-known member TbPTP1 (from Trypanasoma brucei). While the catalytic rate of PTP1B places its amongst the most active mammalian PTPs, its turnover rate is dwarfed in comparison to both YopH and TbPTP1. We use molecular dynamics simulations to address the root of their catalytic differences and to understand why the mammalian enzyme is consigned to lower activity rates. Through a dynamics-based network approach, we identify variations of residue communities within PTP active sites that contribute to catalytic differences, as well as individual residues that exact influence on the dynamic landscape of the enzymes and play a role in their allosteric regulation. Importantly, we detail how PTP1B is regulated through its own protein dynamics, relegating its activity to a lower, albeit biologically appropriate, catalytic rate.

Correlated Evolution of Low-Frequency Vibrations and Function in Enzymes.

Previous studies of the flexibility of ancestral proteins suggest that proteins evolve their function by altering their native state ensemble. Here, we propose a more direct method to analyze such changes during protein evolution by comparing thermally activated vibrations at frequencies below 6 THz, which report on the dynamics of collective protein modes. We analyzed the backbone vibrational density of states of ancestral and extant β-lactamases and thioredoxins and observed marked changes in the vibrational spectrum in response to evolution. Coupled with previously observed changes in protein flexibility, the observed shifts of vibrational mode densities suggest that protein dynamics and dynamical allostery are critical factors for the evolution of enzymes with specialized catalytic and biophysical properties.

Combining structural and coevolution information to unveil allosteric sites.

Understanding allosteric regulation in biomolecules is of great interest to pharmaceutical research and computational methods emerged during the last decades to characterize allosteric coupling. However, the prediction of allosteric sites in a protein structure remains a challenging task. Here, we integrate local binding site information, coevolutionary information, and information on dynamic allostery into a structure-based three-parameter model to identify potentially hidden allosteric sites in ensembles of protein structures with orthosteric ligands. When tested on five allosteric proteins (LFA-1, p38-α, GR, MAT2A, and BCKDK), the model successfully ranked all known allosteric pockets in the top three positions. Finally, we identified a novel druggable site in MAT2A confirmed by X-ray crystallography and SPR and a hitherto unknown druggable allosteric site in BCKDK validated by biochemical and X-ray crystallography analyses. Our model can be applied in drug discovery to identify allosteric pockets.

Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations.

We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

Investigating the allosteric response of the PICK1 PDZ domain to different ligands with all-atom simulations.

The PDZ family is comprised of small modular domains that play critical roles in the allosteric modulation of many cellular signaling processes by binding to the C-terminal tail of different proteins. As dominant modular proteins that interact with a diverse set of peptides, it is of particular interest to explore how different binding partners induce different allosteric effects on the same PDZ domain. Because the PICK1 PDZ domain can bind different types of ligands, it is an ideal test case to answer this question and explore the network of interactions that give rise to dynamic allostery. Here, we use all-atom molecular dynamics simulations to explore dynamic allostery in the PICK1 PDZ domain by modeling two PICK1 PDZ systems: PICK1 PDZ-DAT and PICK1 PDZ-GluR2. Our results suggest that ligand binding to the PICK1 PDZ domain induces dynamic allostery at the αA helix that is similar to what has been observed in other PDZ domains. We found that the PICK1 PDZ-ligand distance is directly correlated with both dynamic changes of the αA helix and the distance between the αA helix and βB strand. Furthermore, our work identifies a hydrophobic core between DAT/GluR2 and I35 as a key interaction in inducing such dynamic allostery. Finally, the unique interaction patterns between different binding partners and the PICK1 PDZ domain can induce unique dynamic changes to the PICK1 PDZ domain. We suspect that unique allosteric coupling patterns with different ligands may play a critical role in how PICK1 performs its biological functions in various signaling networks.