Atomistic picture of conformational exchange in a T4 lysozyme cavity mutant: an experiment-guided molecular dynamics study

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.

Studying micro to millisecond protein dynamics using simple amide 15N CEST experiments supplemented with major-state R2 and visible peak-position constraints

Over the last decade amide 15N CEST experiments have emerged as a popular tool to study protein dynamics that involves exchange between a 'visible' major state and sparsely populated 'invisible' minor states. Although initially introduced to study exchange between states that are in slow exchange with each other (typical exchange rates of, 10 to 400 s-1), they are now used to study interconversion between states on the intermediate to fast exchange timescale while still using low to moderate (5 to 350 Hz) 'saturating' B1 fields. The 15N CEST experiment is very sensitive to exchange as the exchange delay TEX can be quite long (~0.5 s) allowing for a large number of exchange events to occur making it a very powerful tool to detect minor sates populated ([Formula: see text]) to as low as 1%. When systems are in fast exchange and the 15N CEST data has to be described using a model that contains exchange, the exchange parameters are often poorly defined because the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus exchange rate ([Formula: see text]) plots can be quite flat with shallow or no minima and the analysis of such 15N CEST data can lead to wrong estimates of the exchange parameters due to the presence of 'spurious' minima. Here we show that the inclusion of experimentally derived constraints on the intrinsic transverse relaxation rates and the inclusion of visible state peak-positions during the analysis of amide 15N CEST data acquired with moderate B1 values (~50 to ~350 Hz) results in convincing minima in the [Formula: see text] versus [Formula: see text] and the [Formula: see text] versus [Formula: see text] plots even when exchange occurs on the 100 μs timescale. The utility of this strategy is demonstrated on the fast-folding Bacillus stearothermophilus peripheral subunit binding domain that folds with a rate constant ~104 s-1. Here the analysis of 15N CEST data alone results in [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots that contain shallow minima, but the inclusion of visible-state peak positions and restraints on the intrinsic transverse relaxation rates of both states during the analysis of the 15N CEST data results in pronounced minima in the [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] plots and precise exchange parameters even in the fast exchange regime ([Formula: see text]~5). Using this strategy we find that the folding rate constant of PSBD is invariant (~10,500 s-1) from 33.2 to 42.9 °C while the unfolding rates (~70 to ~500 s-1) and unfolded state populations (~0.7 to ~4.3%) increase with temperature. The results presented here show that protein dynamics occurring on the 10 to 104 s-1 timescale can be studied using amide 15N CEST experiments.

Automated Path Searching Reveals the Mechanism of Hydrolysis Enhancement by T4 Lysozyme Mutants

Bacteriophage T4 lysozyme (T4L) is a glycosidase that is widely applied as a natural antimicrobial agent in the food industry. Due to its wide applications and small size, T4L has been regarded as a model system for understanding protein dynamics and for large-scale protein engineering. Through structural insights from the single conformation of T4L, a series of mutations (L99A,G113A,R119P) have been introduced, which have successfully raised the fractional population of its only hydrolysis-competent excited state to 96%. However, the actual impact of these substitutions on its dynamics remains unclear, largely due to the lack of highly efficient sampling algorithms. Here, using our recently developed travelling-salesman-based automated path searching (TAPS), we located the minimum-free-energy path (MFEP) for the transition of three T4L mutants from their ground states to their excited states. All three mutants share a three-step transition: the flipping of F114, the rearrangement of α0/α1 helices, and final refinement. Remarkably, the MFEP revealed that the effects of the mutations are drastically beyond the expectations of their original design: (a) the G113A substitution not only enhances helicity but also fills the hydrophobic Cavity I and reduces the free energy barrier for flipping F114; (b) R119P barely changes the stability of the ground state but stabilizes the excited state through rarely reported polar contacts S117_OG:N132_ND2, E11_OE1:R145_NH1, and E11_OE2:Q105_NE2; (c) the residue W138 flips into Cavity I and further stabilizes the excited state for the triple mutant L99A,G113A,R119P. These novel insights that were unexpected in the original mutant design indicated the necessity of incorporating path searching into the workflow of rational protein engineering.

Dynamic regulation of Zn(II) sequestration by calgranulin C

Calgranulin C performs antimicrobial activity in the human immune response by sequestering Zn(II). This biological function is afforded with the aid of two structurally distinct Ca(II)-binding EF hand motifs, wherein one of which bears an unusual amino acid sequence. Here, we utilize solution state NMR relaxation measurements to investigate the mechanism of Ca(II)-modulated enhancement of Zn(II) sequestration by calgranulin C. Using C13 /N15 CPMG dispersion experiments we have measured pH-dependent major and minor state populations exchanging on micro-to-millisecond timescale. This conformational exchange takes place exclusively in the Ca(II)-bound state and can be mapped to residues located in the EF-I loop and the linker between the tandem EF hands. Molecular dynamics (MD) simulations spanning nano-to-microsecond timescale offer insights into the role of pH-dependent electrostatic interactions in EF-hand dynamics. Our results suggest a pH-regulated dynamic equilibrium of conformations that explore a range of "closed" and partially "open" sidechain configurations within the Zn(II) binding site. We propose a novel mechanism by which Ca(II) binding to a non-canonical EF loop regulates its flexibility and tunes the antimicrobial activity of calgranulin C.

Elucidating the mechanisms underlying protein conformational switching using NMR spectroscopy

How proteins switch between various ligand-free and ligand-bound structures has been a key biophysical question ever since the postulation of the Monod-Wyman-Changeux and Koshland-Nemethy-Filmer models over six decades ago. The ability of NMR spectroscopy to provide structural and kinetic information on biomolecular conformational exchange places it in a unique position as an analytical tool to interrogate the mechanisms of biological processes such as protein folding and biomolecular complex formation. In addition, recent methodological developments in the areas of saturation transfer and relaxation dispersion have expanded the scope of NMR for probing the mechanics of transitions in systems where one or more states constituting the exchange process are sparsely populated and 'invisible' in NMR spectra. In this review, we highlight some of the strategies available from NMR spectroscopy for examining the nature of multi-site conformational exchange, using five case studies that have employed NMR, either in isolation, or in conjunction with other biophysical tools.

The A39G FF domain folds on a volcano-shaped free energy surface via separate pathways

Conformational dynamics play critical roles in protein folding, misfolding, function, misfunction, and aggregation. While detecting and studying the different conformational states populated by protein molecules on their free energy surfaces (FESs) remain a challenge, NMR spectroscopy has emerged as an invaluable experimental tool to explore the FES of a protein, as conformational dynamics can be probed at atomic resolution over a wide range of timescales. Here, we use chemical exchange saturation transfer (CEST) to detect "invisible" minor states on the energy landscape of the A39G mutant FF domain that exhibited "two-state" folding kinetics in traditional experiments. Although CEST has mostly been limited to studies of processes with rates between ∼5 to 300 s^-1 involving sparse states with populations as low as ∼1%, we show that the line broadening that is often associated with minor state dips in CEST profiles can be exploited to inform on additional conformers, with lifetimes an order of magnitude shorter and populations close to 10-fold smaller than what typically is characterized. Our analysis of CEST profiles that exploits the minor state linewidths of the 71-residue A39G FF domain establishes a folding mechanism that can be described in terms of a four-state exchange process between interconverting states spanning over two orders of magnitude in timescale from ∼100 to ∼15,000 μs. A similar folding scheme is established for the wild-type domain as well. The study shows that the folding of this small domain proceeds through a pair of sparse, partially structured intermediates via two discrete pathways on a volcano-shaped FES.

Energy penalties enhance flexible receptor docking in a model cavity

Protein flexibility remains a major challenge in library docking because of difficulties in sampling conformational ensembles with accurate probabilities. Here, we use the model cavity site of T4 lysozyme L99A to test flexible receptor docking with energy penalties from molecular dynamics (MD) simulations. Crystallography with larger and smaller ligands indicates that this cavity can adopt three major conformations: open, intermediate, and closed. Since smaller ligands typically bind better to the cavity site, we anticipate an energy penalty for the cavity opening. To estimate its magnitude, we calculate conformational preferences from MD simulations. We find that including a penalty term is essential for retrospective ligand enrichment; otherwise, high-energy states dominate the docking. We then prospectively docked a library of over 900,000 compounds for new molecules binding to each conformational state. Absent a penalty term, the open conformation dominated the docking results; inclusion of this term led to a balanced sampling of ligands against each state. High ranked molecules were experimentally tested by Tm upshift and X-ray crystallography. From 33 selected molecules, we identified 18 ligands and determined 13 crystal structures. Most interesting were those bound to the open cavity, where the buried site opens to bulk solvent. Here, highly unusual ligands for this cavity had been predicted, including large ligands with polar tails; these were confirmed both by binding and by crystallography. In docking, incorporating protein flexibility with thermodynamic weightings may thus access new ligand chemotypes. The MD approach to accessing and, crucially, weighting such alternative states may find general applicability.

Assessing the Performance of Traveling-salesman based Automated Path Searching (TAPS) on Complex Biomolecular Systems

Though crucial for understanding the function of large biomolecular systems, locating the minimum free energy paths (MFEPs) between their key conformational states is far from trivial due to their high-dimensional nature. Most existing path-searching methods require a static collective variable space as input, encoding intuition or prior knowledge of the transition mechanism. Such information is, however, hardly available a priori and expensive to validate. To alleviate this issue, we have previously introduced a Traveling-salesman based Automated Path Searching method (TAPS) and demonstrated its efficiency on simple peptide systems. Having implemented a parallel version of this method, here we assess the performance of TAPS on three realistic systems (tens to hundreds of residues) in explicit solvents. We show that TAPS successfully located the MFEP for the ground/excited state transition of the T4 lysozyme L99A variant, consistent with previous findings. TAPS also helped identifying the important role of the two polar contacts in directing the loop-in/loop-out transition of the mitogen-activated protein kinase kinase (MEK1), which explained previous mutant experiments. Remarkably, at a minimal cost of 126 ns sampling, TAPS revealed that the Ltn40/Ltn10 transition of lymphotactin needs no complete unfolding/refolding of its β-sheets and that five polar contacts are sufficient to stabilize the various partially unfolded intermediates along the MFEP. These results present TAPS as a general and promising tool for studying the functional dynamics of complex biomolecular systems.

A suite of 19F based relaxation dispersion experiments to assess biomolecular motions

Proteins and nucleic acids are highly dynamic bio-molecules that can populate a variety of conformational states. NMR relaxation dispersion (RD) methods are uniquely suited to quantify the associated kinetic and thermodynamic parameters. Here, we present a consistent suite of ¹⁹F-based CPMG, on-resonance R_1ρ and off-resonance R_1ρ RD experiments. We validate these experiments by studying the unfolding transition of a 7.5 kDa cold shock protein. Furthermore we show that the ¹⁹F RD experiments are applicable to very large molecular machines by quantifying dynamics in the 360 kDa half-proteasome. Our approach significantly extends the timescale of chemical exchange that can be studied with ¹⁹F RD, adds robustness to the extraction of exchange parameters and can determine the absolute chemical shifts of excited states. Importantly, due to the simplicity of ¹⁹F NMR spectra, it is possible to record complete datasets within hours on samples that are of very low costs. This makes the presented experiments ideally suited to complement static structural information from cryo-EM and X-ray crystallography with insights into functionally relevant motions.

A CEST NMR experiment to obtain glycine 1Hα chemical shifts in 'invisible' minor states of proteins

Chemical exchange saturation transfer (CEST) experiments are routinely used to study protein conformational exchange between a 'visible' major state and 'invisible' minor states because they can detect minor states with lifetimes varying from ~ 3 to ~ 100 ms populated to just ~ 0.5%. Consequently several ¹H, ¹⁵N and ¹³C CEST experiments have been developed to study exchange and obtain minor state chemical shifts at almost all backbone and sidechain sites in proteins. Conspicuously missing from this extensive set of CEST experiments is a ¹H CEST experiment to study exchange at glycine (Gly) ¹H^α sites as the existing ¹H CEST experiments that have been designed to study dynamics in amide ¹H-¹⁵N spin systems and methyl ¹³CH₃ groups with three equivalent protons while suppressing ¹H-¹H NOE induced dips are not suitable for studying exchange in methylene ¹³CH₂ groups with inequivalent protons. Here a Gly ¹H^α CEST experiment to obtain the minor state Gly ¹H^α chemical shifts is presented. The utility of this experiment is demonstrated on the L99A cavity mutant of T4 Lysozyme (T4L L99A) that undergoes conformational exchange between two compact conformers. The CEST derived minor state Gly ¹H^α chemical shifts of T4L L99A are in agreement with those obtained previously using CPMG techniques. The experimental strategy presented here can also be used to obtain methylene proton minor state chemical shifts from protein sidechain and nucleic acid backbone sites.

Dynamic design: manipulation of millisecond timescale motions on the energy landscape of cyclophilin A

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they interconvert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov state modelling (MSM) to explore these 'excited' conformational states. Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics, whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By efficiently exploring functionally relevant, but sparsely populated conformations with millisecond lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.

A Double-Resonance CEST Experiment To Study Multistate Protein Conformational Exchange: An Application to Protein Folding

Despite the importance of protein dynamics to function, studying exchange between multiple conformational states remains a challenge because sparsely populated states are invisible to conventional techniques. CEST NMR experiments can detect minor states with lifetimes between 5 and 200 ms populated to a level of just ∼1%. However, CEST often cannot provide the exchange mechanism for processes involving three or more states, leaving the role of the detected minor states unknown. Here a double-resonance CEST experiment to determine the kinetics of multistate exchange is presented. The approach that involves irradiating resonances from two minor states simultaneously is used to study the exchange of T4 lysozyme (T4L) between the dominant native state and two minor states, the unfolded state and a second minor state (B), each populated to only ∼4%. Regular CEST does not provide the folding mechanism, but double-resonance CEST clearly shows that T4L can fold directly without going through B.

Characterizing micro-to-millisecond chemical exchange in nucleic acids using off-resonance R1ρ relaxation dispersion

This review describes off-resonance R1ρ relaxation dispersion NMR methods for characterizing microsecond-to-millisecond chemical exchange in uniformly 13C/15N labeled nucleic acids in solution. The review opens with a historical account of key developments that formed the basis for modern R1ρ techniques used to study chemical exchange in biomolecules. A vector model is then used to describe the R1ρ relaxation dispersion experiment, and how the exchange contribution to relaxation varies with the amplitude and frequency offset of an applied spin-locking field, as well as the population, exchange rate, and differences in chemical shifts of two exchanging species. Mathematical treatment of chemical exchange based on the Bloch-McConnell equations is then presented and used to examine relaxation dispersion profiles for more complex exchange scenarios including three-state exchange. Pulse sequences that employ selective Hartmann-Hahn cross-polarization transfers to excite individual 13C or 15N spins are then described for measuring off-resonance R1ρ(13C) and R1ρ(15N) in uniformly 13C/15N labeled DNA and RNA samples prepared using commercially available 13C/15N labeled nucleotide triphosphates. Approaches for analyzing R1ρ data measured at a single static magnetic field to extract a full set of exchange parameters are then presented that rely on numerical integration of the Bloch-McConnell equations or the use of algebraic expressions. Methods for determining structures of nucleic acid excited states are then reviewed that rely on mutations and chemical modifications to bias conformational equilibria, as well as structure-based approaches to calculate chemical shifts. Applications of the methodology to the study of DNA and RNA conformational dynamics are reviewed and the biological significance of the exchange processes is briefly discussed.

Escape of a Small Molecule from Inside T4 Lysozyme by Multiple Pathways

The T4 lysozyme L99A mutant is often used as a model system to study small-molecule binding to proteins, but pathways for ligand entry and exit from the buried binding site and the associated protein conformational changes have not been fully resolved. Here, molecular dynamics simulations were employed to model benzene exit from its binding cavity using the weighted ensemble (WE) approach to enhance sampling of low-probability unbinding trajectories. Independent WE simulations revealed four pathways for benzene exit, which correspond to transient tunnels spontaneously formed in previous simulations of apo T4 lysozyme. Thus, benzene unbinding occurs through multiple pathways partially created by intrinsic protein structural fluctuations. Motions of several α-helices and side chains were involved in ligand escape from metastable microstates. WE simulations also provided preliminary estimates of rate constants for each exit pathway. These results complement previous works and provide a semiquantitative characterization of pathway heterogeneity for binding of small molecules to proteins.

On identifying collective displacements in apo-proteins that reveal eventual binding pathways

Binding of small molecules to proteins often involves large conformational changes in the latter, which open up pathways to the binding site. Observing and pinpointing these rare events in large scale, all-atom, computations of specific protein-ligand complexes, is expensive and to a great extent serendipitous. Further, relevant collective variables which characterise specific binding or un-binding scenarios are still difficult to identify despite the large body of work on the subject. Here, we show that possible primary and secondary binding pathways can be discovered from short simulations of the apo-protein without waiting for an actual binding event to occur. We use a projection formalism, introduced earlier to study deformation in solids, to analyse local atomic displacements into two mutually orthogonal subspaces—those which are “affine” i.e. expressible as a homogeneous deformation of the native structure, and those which are not. The susceptibility to non-affine displacements among the various residues in the apo- protein is then shown to correlate with typical binding pathways and sites crucial for allosteric modifications. We validate our observation with all-atom computations of three proteins, T4-Lysozyme, Src kinase and Cytochrome P450.

Designing drugs which target specific proteins involved in diseases consumes a lot of time and effort in the pharmaceutical industry. In recent times, in silico design of drugs using all-atom molecular modelling has started to provide crucial inputs. Even so, discovery of binding pathways of small molecules both at the primary binding site, as well as sites for allosteric control, is time consuming and often fortuitous. We provide here a framework within which critical conformational changes likely to occur during binding are quantified from statistical analysis of configurations of proteins in their apo, or inactive form, greatly simplifying identification of target residues. We illustrate this idea by analysing ligand binding pathways for three proteins T4- Lysozyme, P450 and Src kinase, which are active respectively in the immune system, metabolism and cancer.

A methyl 1H double quantum CPMG experiment to study protein conformational exchange

Protein conformational changes play crucial roles in enabling function. The Carr-Purcell-Meiboom-Gill (CPMG) experiment forms the basis for studying such dynamics when they involve the interconversion between highly populated and sparsely formed states, the latter having lifetimes ranging from ~ 0.5 to ~ 5 ms. Among the suite of experiments that have been developed are those that exploit methyl group probes by recording methyl ¹H single quantum (Tugarinov and Kay in J Am Chem Soc 129:9514-9521, 2007) and triple quantum (Yuwen et al. in Angew Chem Int Ed Engl 55:11490-11494, 2016) relaxation dispersion profiles. Here we build upon these by developing a third experiment in which methyl ¹H double quantum coherences evolve during a CPMG relaxation element. By fitting single, double, and triple quantum datasets, akin to recording the single quantum dataset at static magnetic fields of B_o, 2B_o and 3B_o, we show that accurate exchange values can be obtained even in cases where exchange rates exceed 10,000 s^-1. The utility of the double quantum experiment is demonstrated with a pair of cavity mutants of T4 lysozyme (T4L) with ground and excited states interchanged and with exchange rates differing by fourfold (~ 900 s^-1 and ~ 3600 s^-1), as well as with a fast-folding domain where the unfolded state lifetime is ~ 80 µs.

Biomolecular Simulations of Halogen Bonds with a GROMOS Force Field

Halogen bonds (XBs) are non-covalent interactions in which halogens (X), acting as electrophiles, interact with Lewis bases. XBs are able to mediate protein-ligand recognition and therefore play an important role in rational drug design. In this context, the development of molecular modeling tools that can tackle XBs is paramount. XBs are predominantly explained by the existence of a positive region on the electrostatic potential of X named the σ-hole. Typically, with molecular mechanics force fields, this region is modeled using a charged extra point (EP) linked to X along the R-X covalent bond axis. In this work, we developed the first EP-based strategy for GROMOS force fields (specifically GROMOS 54A7) using bacteriophage T4 lysozyme in complex with both iodobenzene and iodopentafluorobenzene as a prototype system. Several EP parametrization schemes were tested by adding a virtual interaction site to ligand topologies retrieved from the Automated Topology Builder (ATB) and Repository. Contrary to previous approaches using other force fields, our analysis is based on the capability of each parametrization scheme to sample XBs during MD simulations. Our results indicate that the implementation of an EP at a distance from iodine corresponding to R_min provides a good qualitative description of XBs in MD simulations, supporting the compatibility of our approach with the GROMOS 54A7 force field.

Atomic resolution mechanism of ligand binding to a solvent inaccessible cavity in T4 lysozyme

Ligand binding sites in proteins are often localized to deeply buried cavities, inaccessible to bulk solvent. Yet, in many cases binding of cognate ligands occurs rapidly. An intriguing system is presented by the L99A cavity mutant of T4 Lysozyme (T4L L99A) that rapidly binds benzene (~106 M-1s-1). Although the protein has long served as a model system for protein thermodynamics and crystal structures of both free and benzene-bound T4L L99A are available, the kinetic pathways by which benzene reaches its solvent-inaccessible binding cavity remain elusive. The current work, using extensive molecular dynamics simulation, achieves this by capturing the complete process of spontaneous recognition of benzene by T4L L99A at atomistic resolution. A series of multi-microsecond unbiased molecular dynamics simulation trajectories unequivocally reveal how benzene, starting in bulk solvent, diffuses to the protein and spontaneously reaches the solvent inaccessible cavity of T4L L99A. The simulated and high-resolution X-ray derived bound structures are in excellent agreement. A robust four-state Markov model, developed using cumulative 60 μs trajectories, identifies and quantifies multiple ligand binding pathways with low activation barriers. Interestingly, none of these identified binding pathways required large conformational changes for ligand access to the buried cavity. Rather, these involve transient but crucial opening of a channel to the cavity via subtle displacements in the positions of key helices (helix4/helix6, helix7/helix9) leading to rapid binding. Free energy simulations further elucidate that these channel-opening events would have been unfavorable in wild type T4L. Taken together and via integrating with results from experiments, these simulations provide unprecedented mechanistic insights into the complete ligand recognition process in a buried cavity. By illustrating the power of subtle helix movements in opening up multiple pathways for ligand access, this work offers an alternate view of ligand recognition in a solvent-inaccessible cavity, contrary to the common perception of a single dominant pathway for ligand binding.

Measuring the signs of the methyl 1H chemical shift differences between major and 'invisible' minor protein conformational states using methyl 1H multi-quantum spectroscopy

Carr-Purcell-Meiboom-Gill (CPMG) type relaxation dispersion experiments are now routinely used to characterise protein conformational dynamics that occurs on the μs to millisecond (ms) timescale between a visible major state and 'invisible' minor states. The exchange rate(s) ([Formula: see text]), population(s) of the minor state(s) and the absolute value of the chemical shift difference [Formula: see text] (ppm) between different exchanging states can be extracted from the CPMG data. However the sign of [Formula: see text] that is required to reconstruct the spectrum of the 'invisible' minor state(s) cannot be obtained from CPMG data alone. Building upon the recently developed triple quantum (TQ) methyl [Formula: see text] CPMG experiment (Yuwen in Angew Chem 55:11490-11494, 2016) we have developed pulse sequences that use carbon detection to generate and evolve single quantum (SQ), double quantum (DQ) and TQ coherences from methyl protons in the indirect dimension to measure the chemical exchange-induced shifts of the SQ, DQ and TQ coherences from which the sign of [Formula: see text] is readily obtained for two state exchange. Further a combined analysis of the CPMG data and the difference in exchange induced shifts between the SQ and DQ resonances and between the SQ and TQ resonances improves the estimates of exchange parameters like the population of the minor state. We demonstrate the use of these experiments on two proteins undergoing exchange: (1) the ~ 18 kDa cavity mutant of T4 Lysozyme ([Formula: see text]) and (2) the [Formula: see text] kDa Peripheral Sub-unit Binding Domain (PSBD) from the acetyl transferase of Bacillus stearothermophilus ([Formula: see text]).

Dynamic basis for dG•dT misincorporation via tautomerization and ionization

Tautomeric and anionic Watson-Crick-like mismatches have important roles in replication and translation errors through mechanisms that are not fully understood. Here, using NMR relaxation dispersion, we resolve a sequence-dependent kinetic network connecting G•T/U wobbles with three distinct Watson-Crick mismatches: two rapidly exchanging tautomeric species (Genol•T/UG•Tenol/Uenol; population less than 0.4%) and one anionic species (G•T-/U-; population around 0.001% at neutral pH). The sequence-dependent tautomerization or ionization step was inserted into a minimal kinetic mechanism for correct incorporation during replication after the initial binding of the nucleotide, leading to accurate predictions of the probability of dG•dT misincorporation across different polymerases and pH conditions and for a chemically modified nucleotide, and providing mechanisms for sequence-dependent misincorporation. Our results indicate that the energetic penalty for tautomerization and/or ionization accounts for an approximately 10-2 to 10-3-fold discrimination against misincorporation, which proceeds primarily via tautomeric dGenol•dT and dG•dTenol, with contributions from anionic dG•dT- dominant at pH 8.4 and above or for some mutagenic nucleotides.

Ab Initio Prediction of NMR Spin Relaxation Parameters from Molecular Dynamics Simulations

¹H-¹⁵N NMR spin relaxation and relaxation dispersion experiments can reveal the time scale and extent of protein motions across the ps-ms range, where the ps-ns dynamics revealed by fundamental quantities R₁, R₂, and heteronuclear NOE can be well-sampled by molecular dynamics simulations (MD). Although the principles of relaxation prediction from simulations are well-established, numerous NMR-MD comparisons have hitherto focused upon the aspect of order parameters S² due to common artifacts in the prediction of transient dynamics. We therefore summarize here all necessary components and highlight existing and proposed solutions, such as the inclusion of quantum mechanical zero-point vibrational corrections and separate MD convergence of global and local motions in coarse-grained and all-atom force fields, respectively. For the accuracy of the MD prediction to be tested, two model proteins GB3 and Ubiquitin are used to validate five atomistic force fields against published NMR data supplemented by the coarse-grained force field MARTINI+EN. In Amber and CHARMM-type force fields, quantitative agreement was achieved for structured elements with minimum adjustment of global parameters. Deviations from experiment occur in flexible loops and termini, indicating differences in both the extent and time scale of backbone motions. The lack of systematic patterns and water model dependence suggests that modeling of the local environment limits prediction accuracy. Nevertheless, qualitative accuracy in a 2 μs CHARMM36m Stam2 VHS domain simulation demonstrates the potential of MD-based interpretation in combination with NMR-measured dynamics, increasing the utility of spin relaxation in integrative structural biology.

Biomolecular conformational changes and ligand binding: from kinetics to thermodynamics

The behaviour of biomolecular systems is governed by their thermodynamic and kinetic properties. It is thus important to be able to calculate, for example, both the affinity and rate of binding and dissociation of a protein-ligand complex, or the populations and exchange rates between distinct conformational states. Because these are typically rare events, calculating these properties from long molecular dynamics simulations remains extremely difficult. Instead, one often adopts a divide-and-conquer strategy in which equilibrium free-energy differences and the fastest state-to-state transition (e.g. ligand association or minor-to-major state conversion) are combined to estimate the slow rate (e.g. ligand dissociation) using a two-state assumption. Here we instead address these problems by using a previously developed method to calculate both the forward and backward rates directly from simulations. We then estimate the thermodynamics from the rates, and validate these values by independent means. We applied the approach to three systems of increasing complexity, including the association and dissociation of benzene to a fully buried cavity inside the L99A mutant variant of T4 lysozyme. In particular, we were able to determine both millisecond association and dissociation rates, and the affinity, of the protein-ligand system by directly observing dozens of rare events in atomic detail. Our approach both sheds light on the precision of methods for calculating kinetics and further provides a generally useful test for the internal consistency of kinetics and thermodynamics. We also expect our route to be useful for obtaining both the kinetics and thermodynamics at the same time in more challenging cases.

Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A

Proteins commonly sample a number of conformational states to carry out their biological function, often requiring transitions from the ground state to higher-energy states. Characterizing the mechanisms that guide these transitions at the atomic level promises to impact our understanding of functional protein dynamics and energy landscapes. The leucine-99-to-alanine (L99A) mutant of T4 lysozyme is a model system that has an experimentally well characterized excited sparsely populated state as well as a ground state. Despite the exhaustive study of L99A protein dynamics, the conformational changes that permit transitioning to the experimentally detected excited state (∼3%, ΔG ∼2 kcal/mol) remain unclear. Here, we describe the transitions from the ground state to this sparsely populated excited state of L99A as observed through a single molecular dynamics (MD) trajectory on the Anton supercomputer. Aside from detailing the ground-to-excited-state transition, the trajectory samples multiple metastates and an intermediate state en route to the excited state. Dynamic motions between these states enable cavity surface openings large enough to admit benzene on timescales congruent with known rates for benzene binding. Thus, these fluctuations between rare protein states provide an atomic description of the concerted motions that illuminate potential path(s) for ligand binding. These results reveal, to our knowledge, a new level of complexity in the dynamics of buried cavities and their role in creating mobile defects that affect protein dynamics and ligand binding.

Mapping transiently formed and sparsely populated conformations on a complex energy landscape

Determining the structures, kinetics, thermodynamics and mechanisms that underlie conformational exchange processes in proteins remains extremely difficult. Only in favourable cases is it possible to provide atomic-level descriptions of sparsely populated and transiently formed alternative conformations. Here we benchmark the ability of enhanced-sampling molecular dynamics simulations to determine the free energy landscape of the L99A cavity mutant of T4 lysozyme. We find that the simulations capture key properties previously measured by NMR relaxation dispersion methods including the structure of a minor conformation, the kinetics and thermodynamics of conformational exchange, and the effect of mutations. We discover a new tunnel that involves the transient exposure towards the solvent of an internal cavity, and show it to be relevant for ligand escape. Together, our results provide a comprehensive view of the structural landscape of a protein, and point forward to studies of conformational exchange in systems that are less characterized experimentally.

DOI:http://dx.doi.org/10.7554/eLife.17505.001

Proteins are the workhorses of cells, where they perform a wide range of roles. To do so, they adopt specific three-dimensional structures that enable them to interact with other molecules as necessary. Often a protein needs to be able to shift between different states with distinct structures as it goes about its job. To fully understand how a protein works, it is important to be able to characterize these different structures and how the protein changes between them.

Many of the experimental techniques used to study protein structure rely on isolating the individual structural forms of a protein. Since many structures only exist briefly, this can be very difficult. To complement experimental results, computer simulations allow researchers to model how atoms behave within a molecule. However, a number of factors limit how well these models represent what happens experimentally, such as the accuracy of the physical description used for the modeling.

Wang et al. set out to test and benchmark how well computer simulations could model changes in structure for a protein called T4 lysozyme, which has been studied extensively using experimental techniques. T4 lysozyme exists in two different states that have distinct structures. By comparing existing detailed experimental measurements with the results of their simulations, Wang et al. found that the simulations could capture key aspects of how T4 lysozyme changes its shape.

The simulations described the structure of the protein in both states and accurately determined the relative proportion of molecules that are found in each state. They could also determine how long it takes for a molecule to change its shape from one state to the other. The findings allowed Wang et al. to describe in fine detail – down to the level of individual atoms – how the protein changes its shape and how mutations in the protein affect its ability to do so. A key question for future studies is whether these insights can be extended to other proteins that are less well characterized experimentally than T4 lysozyme.

DOI:http://dx.doi.org/10.7554/eLife.17505.002