Functional regulation of an intrinsically disordered protein via a conformationally excited state

Increasing the accuracy of exchange parameters reporting on slow dynamics by performing CEST experiments with 'high' B1 fields

Over the last decade chemical exchange saturation transfer (CEST) NMR methods have emerged as powerful tools to characterize biomolecular conformational dynamics occurring between a visible major state and 'invisible' minor states. The ability of the CEST experiment to detect these minor states, and provide precise exchange parameters, hinges on using appropriate B1 field strengths during the saturation period. Typically, a pair of B1 fields with ω1 (=2πB1) values around the exchange rate kex are chosen. Here we show that the transverse relaxation rate of the minor state resonance (R2,B) also plays a crucial role in determining the B1 fields that lead to the most informative datasets. Using [Formula: see text]  ≥ kex, to guide the choice of B1, instead of kex, leads to data wherefrom substantially more accurate exchange parameters can be derived. The need for higher B1 fields, guided by K, is demonstrated by studying the conformational exchange in two mutants of the 71 residue FF domain with kex ∼ 11 s-1 and ∼ 72 s-1, respectively. In both cases analysis of CEST datasets recorded using B1 field values guided by kex lead to imprecise exchange parameters, whereas using B1 values guided by K resulted in precise site-specific exchange parameters. The conclusions presented here will be valuable while using CEST to study slow processes at sites with large intrinsic relaxation rates, including carbonyl sites in small to medium sized proteins, amide 15N sites in large proteins and when the minor state dips are broadened due to exchange among the minor states.

A finely balanced order-disorder equilibrium sculpts the folding-binding landscape of an antibiotic sequestering protein

TipA, a MerR family transcription factor from Streptomyces lividans, promotes antibiotic resistance by sequestering broad-spectrum thiopeptide-based antibiotics, thus counteracting their inhibitory effect on ribosomes. TipAS, a minimal binding motif which is expressed as an isoform of TipA, harbors a partially disordered N-terminal subdomain that folds upon binding multiple antibiotics. The extent and nature of the underlying molecular heterogeneity in TipAS that shapes its promiscuous folding-function landscape is an open question and is critical for understanding antibiotic-sequestration mechanisms. Here, combining equilibrium and time-resolved experiments, statistical modeling, and simulations, we show that the TipAS native ensemble exhibits a pre-equilibrium between binding-incompetent and binding-competent substates, with the fully folded state appearing only as an excited state under physiological conditions. The binding-competent state characterized by a partially structured N-terminal subdomain loses structure progressively in the physiological range of temperatures, swells on temperature increase, and displays slow conformational exchange across multiple conformations. Binding to the bactericidal antibiotic thiostrepton follows a combination of induced-fit and conformational-selection-like mechanisms, via partial binding and concomitant stabilization of the binding-competent substate. These ensemble features are evolutionarily conserved across orthologs from select bacteria that infect humans, underscoring the functional role of partial disorder in the native ensemble of antibiotic-sequestering proteins belonging to the MerR family.

Beyond slow two-state protein conformational exchange using CEST: applications to three-state protein interconversion on the millisecond timescale

Although NMR spectroscopy is routinely used to study the conformational dynamics of biomolecules, robust analyses of the data are challenged in cases where exchange is more complex than two-state, such as when a 'visible' major conformer exchanges with two 'invisible' minor states on the millisecond timescale. It is becoming increasingly clear that chemical exchange saturation transfer (CEST) NMR experiments that were initially developed to study systems undergoing slow interconversion are also sensitive to intermediate-fast timescale biomolecular conformational exchange. Here we investigate the utility of the amide 15N CEST experiment to characterise protein three-state exchange occurring on the millisecond timescale by studying the interconversion between the folded (F) state of the FF domain from human HYPA/FBP11 (WT FF) and two of its folding intermediates I1 and I2. Although 15N CPMG experiments are consistent with the F state interconverting with a single minor state on the millisecond timescale, 15N CEST data clearly establish an exchange process between F and a pair of minor states. A unique three-state exchange model cannot be obtained by analysis of 15N CEST data recorded at a single temperature. However, including the relative sign of the difference in the chemical shifts of the two minor states based on a simple two-state analysis of CEST data recorded at multiple temperatures, results in a robust three-state model in which the F, I1 and I2 states interconvert with each other on the millisecond timescale ( k e x , F I 1 ~ 550 s-1, k e x , F I 2 ~ 1200 s-1, k e x , I 1 I 2 ~ 5000 s-1), with I1 and I2 sparsely populated at ~ 0.15% and ~ 0.35%, respectively, at 15 °C. A computationally demanding grid-search of exchange parameter space is not required to extract the best-fit exchange parameters from the CEST data. The utility of the CEST experiment, thus, extends well beyond studies of conformers in slow exchange on the NMR chemical shift timescale, to include systems with interconversion rates on the order of thousands/second.

Dynamics and interactions of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are widespread in eukaryotes and participate in a variety of important cellular processes. Numerous studies using state-of-the-art experimental and theoretical methods have advanced our understanding of IDPs and revealed that disordered regions engage in a large repertoire of intra- and intermolecular interactions through their conformational dynamics, thereby regulating many intracellular functions in concert with folded domains. The mechanisms by which IDPs interact with their partners are diverse, depending on their conformational propensities, and include induced fit, conformational selection, and their mixtures. In addition, IDPs are implicated in many diseases, and progress has been made in designing inhibitors of IDP-mediated interactions. Here we review these recent advances with a focus on the dynamics and interactions of IDPs.

Molecular simulations integrated with experiments for probing the interaction dynamics and binding mechanisms of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) exploit their plasticity to deploy a rich panoply of soft interactions and binding phenomena. Advances in tailoring molecular simulations for IDPs combined with experimental cross-validation offer an atomistic view of the mechanisms that control IDP binding, function, and dysfunction. The emerging theme is that unbound IDPs autonomously form transient local structures and self-interactions that determine their binding behavior. Recent results have shed light on whether and how IDPs fold, stay disordered or drive condensation upon binding; how they achieve binding specificity and select among competing partners. The disorder-binding paradigm is now being proactively used by researchers to target IDPs for rational drug design and engineer molecular responsive elements for biosensing applications.

Transient excited states of the metamorphic protein Mad2 and their implications for function

The spindle checkpoint complex is a key surveillance mechanism in cell division that prevents premature separation of sister chromatids. Mad2 is an integral component of this spindle checkpoint complex that recognizes cognate substrates such as Mad1 and Cdc20 in its closed (C-Mad2) conformation by fastening a "seatbelt" around short peptide regions that bind to the substrate recognition site. Mad2 is also a metamorphic protein that adopts not only the fold found in C-Mad2, but also a structurally distinct open conformation (O-Mad2) which is incapable of binding substrates. Here, we show using chemical exchange saturation transfer (CEST) and relaxation dispersion (CPMG) NMR experiments that Mad2 transiently populates three other higher free energy states with millisecond lifetimes, two in equilibrium with C-Mad2 (E1 and E2) and one with O-Mad2 (E3). E1 is a mimic of substrate-bound C-Mad2 in which the N-terminus of one C-Mad2 molecule inserts into the seatbelt region of a second molecule of C-Mad2, providing a potential pathway for autoinhibition of C-Mad2. E2 is the "unbuckled" conformation of C-Mad2 that facilitates the triage of molecules along competing fold-switching and substrate binding pathways. The E3 conformation that coexists with O-Mad2 shows fluctuations at a hydrophobic lock that is required for stabilizing the O-Mad2 fold and we hypothesize that E3 represents an early intermediate on-pathway towards conversion to C-Mad2. Collectively, the NMR data highlight the rugged free energy landscape of Mad2 with multiple low-lying intermediates that interlink substrate-binding and fold-switching, and also emphasize the role of molecular dynamics in its function.

Cell phenotypes can be predicted from propensities of protein conformations

Proteins exist as dynamic conformational ensembles. Here we suggest that the propensities of the conformations can be predictors of cell function. The conformational states that the molecules preferentially visit can be viewed as phenotypic determinants, and their mutations work by altering the relative propensities, thus the cell phenotype. Our examples include (i) inactive state variants harboring cancer driver mutations that present active state-like conformational features, as in K-Ras4BG12V compared to other K-Ras4BG12X mutations; (ii) mutants of the same protein presenting vastly different phenotypic and clinical profiles: cancer and neurodevelopmental disorders; (iii) alterations in the occupancies of the conformational (sub)states influencing enzyme reactivity. Thus, protein conformational propensities can determine cell fate. They can also suggest the allosteric drugs efficiency.

Machine Learning Subtle Conformational Change due to Phosphorylation in Intrinsically Disordered Proteins

Phosphorylation of intrinsically disordered proteins/regions (IDPs/IDRs) has a profound effect in biological functions such as cell signaling, protein folding or unfolding, and long-range allosteric effects. However, here we focus on two IDPs, namely 83-residue IDR transcription factor Ash1 and 92-residue long N-terminal region of CDK inhibitor Sic1 protein, found in Saccharomyces cerevisiae, for which experimental measurements of average conformational properties, namely, radius of gyration and structure factor, indicate negligible changes upon phosphorylation. Here, we show that a judicious dissection of conformational ensemble via combination of unsupervised machine learning and extensive molecular dynamics (MD) trajectories can highlight key differences and similarities among the phosphorylated and wild-type IDP. In particular, we develop Markov state model (MSM) using the latent-space dimensions of an autoencoder, trained using multi-microsecond long MD simulation trajectories. Examination of structural changes among the states, prior to and upon phosphorylation, captured several similarities and differences in their backbone contact maps, secondary structure, and torsion angles. Hydrogen bonding analysis revealed that phosphorylation not only increases the number of hydrogen bonds but also switches the pattern of hydrogen bonding between the backbone and side chain atoms with the phosphorylated residues. We also observe that although phosphorylation introduces salt bridges, there is a loss of the cation-π interaction. Phosphorylation also improved the probability for long-range hydrophobic contacts and also enhanced interaction with water molecules and improved the local structure of water as evident from the geometric order parameters. The observations on these machine-learnt states gave important insights, as it would otherwise be difficult to determine experimentally which is important, if we were to understand the role of phosphorylation of IDPs in their biological functions.

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Probing excited state 1Hα chemical shifts in intrinsically disordered proteins with a triple resonance-based CEST experiment: Application to a disorder-to-order switch

Over 40% of eukaryotic proteomes and 15% of bacterial proteomes are predicted to be intrinsically disordered based on their amino acid sequence. Intrinsically disordered proteins (IDPs) exist as heterogeneous ensembles of interconverting conformations and pose a challenge to the structure-function paradigm by apparently functioning without possessing stable structural elements. IDPs play a prominent role in biological processes involving extensive intermolecular interaction networks and their inherently dynamic nature facilitates their promiscuous interaction with multiple structurally diverse partner molecules. NMR spectroscopy has made pivotal contributions to our understanding of IDPs because of its unique ability to characterize heterogeneity at atomic resolution. NMR methods such as Chemical Exchange Saturation Transfer (CEST) and relaxation dispersion have enabled the detection of 'invisible' excited states in biomolecules which are transiently and sparsely populated, yet central for function. Here, we develop a 1Hα CEST pulse sequence which overcomes the resonance overlap problem in the 1Hα-13Cα plane of IDPs by taking advantage of the superior resolution in the 1H-15N correlation spectrum. In this sequence, magnetization is transferred after 1H CEST using a triple resonance coherence transfer pathway from 1Hα (i) to 1HN(i + 1) during which the 15N(t1) and 1HN(t2) are frequency labelled. This approach is integrated with spin state-selective CEST for eliminating spurious dips in CEST profiles resulting from dipolar cross-relaxation. We apply this sequence to determine the excited state 1Hα chemical shifts of the intrinsically disordered DNA binding domain (CytRN) of the bacterial cytidine repressor (CytR), which transiently acquires a functional globally folded conformation. The structure of the excited state, calculated using 1Hα chemical shifts in conjunction with other excited state NMR restraints, is a three-helix bundle incorporating a helix-turn-helix motif that is vital for binding DNA.